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Page 1: UNIVERSITY OF CINCINNATI -  · PDF fileof the University of Cincinnati ... The use of an energy absorbing seat in conjunction with vehicle armor plating ... especially Kevlar©,

UNIVERSITY OF CINCINNATI Date:___________________

I, _________________________________________________________, hereby submit this work as part of the requirements for the degree of:

in:

It is entitled:

This work and its defense approved by:

Chair: _______________________________ _______________________________ _______________________________ _______________________________ _______________________________

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DESIGN AND DEVELOPMENT OF AN ENERGY ABSORBING SEAT AND

BALLISTIC FABRIC MATERIAL MODEL TO REDUCE CREW INJURY

CAUSED BY ACCELERATION FROM MINE/IED BLAST

A Thesis submitted to the

Division of Research and Advanced Studies

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

MASTER OF SCIENCE

in the Department of Mechanical, Industrial and Nuclear Engineering

of the College of Engineering

2006

by

Gaurav Nilakantan

Bachelor of Engineering (B.E.)

Visveswaraiah Technological University, India, 2003

Committee Chair: Dr. Ala Tabiei

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Abstract

Anti tank (AT) mines pose a serious threat to the occupants of armored vehicles.

High acceleration pulses and impact forces are transmitted to the occupant

through vehicle-occupant contact interfaces, such as the floor and seat, posing

the risk of moderate injury to fatality.

The use of an energy absorbing seat in conjunction with vehicle armor plating

greatly improves occupant survivability during such an explosion. The axial

crushing of aluminum tubes over a steel rail constitutes the principal energy

absorption mechanism. Concepts to further reduce the shock pulse transmitted

to the occupant are introduced during the study, such as the use of a foam

cushion and an inflatable airbag cushion.

The explicit non-linear finite element software LS-DYNA© is used to perform all

numerical simulations. Vertical drop testing of the seat structure with the

occupant are performed for comparison with experimental data after which

simulations are run, that utilize input acceleration pulses comparable to a mine

blast under an armored vehicle. The occupant is modeled using a 5th percentile

HYBRID III dummy. Data such as lumbar load, neck moments, hip and knee

moments, and head and torso accelerations are collected for comparison with

known injury threshold values to assess injury.

Numerical simulations are also conducted of the impact of a dummy’s feet by

a rigid wall whose upward motion is comparable to an armored vehicle’s

reaction to a mine blast directly underneath it. A 50th percentile HYBRID III

dummy is used in various seated positions. The input pulses that control the

motion of the rigid wall are varied in a step wise manner to determine the effect

on extent of injury. Data such as hip and knee moment, femoral force and foot

acceleration are collected from the dummy and compared to injury threshold

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values from various references. By numerically simulating the mine blast under a

vehicle, the significant cost of conducting destructive full scale tests can be

avoided.

A simple numerical formulation is presented, to predict the deceleration

response during dynamic axial crushing of cylindrical tubes. The formulation

uses an energy balance approach and is coded in the high level language

MATLAB©. It can track the histories of plastic work, kinetic energy, and dynamic

crushing load during the crushing process, and finally yields the peak

acceleration magnitude, which can then be calibrated and used for injury

assessment and survivability studies by comparing with allowable values for

human occupants. Further, the geometric and material properties of the tube

can be varied to study its response during the dynamic axial crushing.

The impact resistance of high strength fabrics makes them desirable in

applications such as protective clothing for military and law enforcement

personnel, protective layering in turbine fragment containment, armor plating of

vehicles, and other similar applications involving protection resistance against a

high velocity projectile. Such fabrics, especially Kevlar©, Zylon©, and Spectra©,

can be used in the energy absorbing seat as a cushion cover for the high

density foam, to prevent tearing by unexpected shrapnel during an explosion

underneath the armored vehicle. The protective fabric can also be used as a

protective vest for the dummy occupant and as a liner inside the vehicle hull. A

material model has been developed to realistically simulate ballistic impact of

loose woven fabrics with elastic crimped fibers. It is based upon a

micromechanical approach that includes the architecture of the fabric and the

phenomenon of fiber reorientation, and excludes strain rate sensitivity as the

yarns are simplified as elastic members. The material model is implemented as

a FORTRAN© subroutine and integrated into the explicit, non-linear dynamic

finite element code LSDYNA© as a user-defined material model (UMAT). Results

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of axial fabric tests run in LSDYNA© using this material model agree well with

other models. This justifies the use of a simplistic, computationally inexpensive

material model to realistically simulate ballistic impact.

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Acknowledgements

I am indebted to my advisor Prof. Ala Tabiei for giving me a chance to work with

him on all his fascinating research, for believing in me and constantly guiding

and encouraging me.

I express my utmost gratitude to my parents S. Nilakantan and Nirmala

Nilakantan for all that they have done for me, for all their love, support, sacrifice,

and encouragement.

I sincerely thank committee members, Prof. Jay Kim, and Prof. David Thompson

for their presence on my committee and their suggestions.

I am also grateful to the University of Las Vegas-Nevada for funding part of this

research, as well as the Ohio Supercomputing Center for their high-speed

computing support.

I thank my colleague Srinivasa Vedagiri Aminijikarai for all his technical advice

and support.

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Contents

a. List of Figures…………………………………………………………………………….... i

b. List of Tables……………………………………………………………………………….. vi

1. Introduction 1

1.1 Background………………………………………………………………………….. 1

1.2 Literature Review…………………………………………………………………….. 2

1.2.1 Energy Absorbing Seat………………………………………………….. 2

1.2.2 Foot Impact during IED/Mine blast…………………………………….. 4

1.2.3 Human Injury Criteria……………………………………………………. 5

1.2.4 Dynamic Axial Crushing of Circular Tubes……………………………. 13

1.2.5 Ballistic Impact of Dry Woven Fabrics…………………………………. 14

1.3 Scope of Work……………………………………………………………………….. 26

1.4 Outline of Thesis……………………………………………………………………… 27

2. Energy Absorbing Seat 29

2.1 Preliminary Design…………………………………………………………………… 29

2.2 Dynamic Axial Crushing of the Aluminum Tubes………………………………… 32

2.2.1 Techniques to reduce the initial crushing load of a tube…………... 36

2.3 Additional energy absorbing elements…………………………………………… 39

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2.3.1 Low Density Foam Cushion…………………………………………….. 39

2.3.2 Airbag Cushion………………………………………………………….. 42

2.4 Shock Pulses Applied to the Structure…………………………………………….. 44

2.4.1 Impact After Free Fall…………………………………………………… 44

2.4.2 Mine Blast………………………………………………………………… 45

2.5 Filtering of Data……………………………………………………………………… 46

2.6 Validation of Initial EA Seat Simulations…………………………………………… 47

3. Results and Discussion: Energy Absorbing Seat 49

3.1 Test Matrix…………………………………………………………………………….. 49

3.2 Simulation Setup…………………………………………………………………….. 50

3.3 EA seat with GEBOD dummy subjected to vertical drop testing………………. 51

3.4 EA seat with HYBRID III dummy subjected to vertical drop testing…………….. 54

3.5 EA seat with GEBOD dummy subjected to mine blast testing…………………. 56

3.6 EA seat with HYBRID III dummy subjected to mine blast testing……………….. 59

3.7 Improved Modeling of the EA seat structure…………………………………….. 60

3.8 Effect of Aluminum Yield Strength on the Simulations…………………………... 61

3.9 Stages of Crushing of the Aluminum Crush Tube………………………………... 62

3.9.1 Stages of crushing for the original EA seat model…………………… 63

3.9.2 Stages of crushing for the improved EA seat model………………... 64

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3.9.3 Shape of the Crushed Tube when Modeled with Solid Elements….. 64

3.10 Final EA Seat Design for use in full scale Vertical Drop Testing and mine

Blast Testing……………………………………………………………………………….

65

3.10.1 Vertical Drop Testing…………………………………………………… 66

3.10.2 Mine Blast Testing………………………………………………………. 68

3.11 New EA Mechanism……………………………………………………………….. 69

3.12 Conclusions………………………………………………………………………… 71

3.13 Scope for Further Work…………………………………………………………….. 73

4. Impact of Foot during IED/Mine Blast 74

4.1 Numerical Setup and Methodology………………………………………………. 74

4.2 Numerical Results and Discussion…………………………………………………. 78

4.2.1 Hybrid III dummy in a sitting straight position…………………………. 80

4.2.2 Hybrid III dummy in a driving position…………………………………. 84

4.3 Parametric Study…………………………………………………………………….. 89

4.4 Conclusions………………………………………………………………………….. 93

4.5 Scope for Further Work……………………………………………………………… 94

5. Dynamic Axial Crushing of Circular Tubes: Numerical Formulation 95

5.1 Need for a Simple Numerical Formulation……………………………………….. 95

5.2 Theory and Formulation…………………………………………………………….. 97

5.3 Results and Discussion……………………………………………………………… 107

5.4 Conclusions………………………………………………………………………….. 114

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5.5 Scope for further work………………………………………………………………. 115

6. Ballistic Impact of Woven Fabrics 116

6.1 Description of the Material Model………………………………………………… 116

6.2 The Representative Volume Cell of the Model…………………………………... 116

6.3 Elastic Model………………………………………………………………………… 118

6.4 Numerical Results - Fabric Strip Testing…………………………………………… 125

6.4.1 Elastic model fabric strip test………………………………………….. 127

6.4.2 Viscoelastic model fabric strip test……………………………………. 129

6.4.3 Comparison between Elastic and Viscoelastic model results……… 130

6.5 Conclusions………………………………………………………………………….. 132

6.6 Scope for Further Work……………………………………………………………… 133

Appendix I

Source code for the numerical formulation of dynamic axial crushing of circular

tubes………………………………………………………………………………………. 134

Appendix II

Source code for the incremental constitutive equation used in the Elastic

material model to derive the stress-strain relationship………………………………. 146

References……………………………………………………………….. 148

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i

List of Figures

Chapter 1

1.1 Crashworthy seat for commuter aircraft………………………………... 3

1.2 Evaluation of an OH-58 pilot’s seat……………………………………… 4

1.3 Dummy lower leg models used in the lower leg impact studies…….. 5

1.4 Numerical dummies developed by LSTC………………………………. 5

1.5 Axially crushed aluminum tube………………………………………….. 14

1.6 Numerical simulation of ballistic impact of fabric in LSDYNA………… 22

Chapter 2

2.1 Preliminary EA seat design………………………………………………... 29

2.2 Specifications of the rail substructure…………………………………… 31

2.3 Stress Vs. Strain curve for the aluminum crush tubes………………….. 32

2.4 Static and dynamic axial crushing load of cylindrical aluminum

tubes with a D/t ratio of 30.7……………………………………………...

35

2.5 Annular grooves on a circular crush tube………………………………. 36

2.6 Weakening the FE mesh of the crush tube…………………………….. 37

2.7 Heat treatment curve used during the annealing process…………… 38

2.8 Static performance of plain and wasted tubes……………………….. 38

2.9 Nominal stress Vs. strain curve for the low density foam material……. 39

2.10 Gravity settling of the dummy against the foam cushion…………….. 40

2.11 Contoured foam cushion headrest to minimize head injury…………. 41

2.12 Effect of foam cushion on HYRBID III head acceleration……………... 41

2.13 FE mesh of the EA seat with airbag cushion and GEBOD dummy…... 43

2.14 Input parameters of the airbag cushion………………………………... 44

2.15 Acceleration pulse used in vertical drop testing………………………. 45

2.16 Acceleration pulse representing a mine blast…………………………. 46

2.17 Filtering of data……………………………………………………………. 47

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List of Figures… continued

2.18 Validation of initial EA seat simulations………………………………….. 48

Chapter 3

3.1 EA seat with a GEBOD dummy………………………………………….. 50

3.2 EA seat with a HYBRID III dummy………………………………………… 51

3.3 Results of EA Seat with GEBOD dummy subject to vertical drop

testing……………………………………………………………………….. 53

3.4 Results of EA Seat with HYBRID III dummy subject to vertical drop

testing……………………………………………………………………… 56

3.5 Results of EA Seat with GEBOD dummy subject to mine blast testing.. 58

3.6 Results of EA Seat with HYBRID III dummy subject to mine blast

testing……………………………………………………………………….. 60

3.7 Improved modeling of the EA seat structure…………………………… 61

3.8 Effect of Aluminum yield strength on the simulations…………………. 62

3.9 Stages of tube crushing for original seat model………………………. 63

3.10 Stages of tube crushing for improved seat model……………………. 64

3.11 Shape of the crushed tube modeled with solid elements……………. 65

3.12 Final model of the EA seat structure…………………………………….. 66

3.13 Deceleration pulses………………………………………………………. 66

3.14 Dynamic axial crushing force of the tube, and Dummy-seat

contact force……………………………………………………………… 67

3.15 Contact force between the foot and floor…………………………….. 67

3.16 Acceleration pulses……………………………………………………….. 68

3.17 Dynamic axial crushing force of the tube, and Dummy-seat

contact force……………………………………………………………… 68

3.18 Contact force between the foot and floor…………………………….. 69

3.19 New honeycomb EA mechanism………………………………………. 70

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iii

List of Figures… continued

3.20 Interior view of the EA mechanism……………………………………… 71

Chapter 4

4.1 Experimental setup of lower leg impact……………………………….. 74

4.2 Numerical setup in ‘Sitting Straight’ position……………………………. 75

4.3 Numerical setup in ‘Driving’ position…………………………………….. 76

4.4 Prescribed velocity of the wall…………………………………………… 77

4.5 Validation of femur axial compressive force with test db2a…………. 78

4.6 Validation of foot acceleration with test db2a………………………… 79

4.7 Validation of femur axial compressive force with test db3a…………. 79

4.8 Validation of foot acceleration with test db3a………………………… 80

4.9 Foot (z) acceleration……………………………………………………… 81

4.10 Hip flexion-extension moment for wall speeds 1 ft/s - 15 ft/s…………. 82

4.11 Hip flexion-extension moment for wall speeds 25 ft/s - 35 ft/s………... 82

4.12 Lower leg (z) acceleration………………………………………………... 83

4.13 Femur axial compressive force………………………………………….. 83

4.14 Knee flexion-extension moment………………………………………… 84

4.15 Foot (z) acceleration……………………………………………………… 85

4.16 Hip flexion-extension moment…………………………………………… 86

4.17 Lower leg (z) acceleration………………………………………………... 86

4.18 Femur axial compressive force………………………………………….. 87

4.19 Knee flexion-extension moment…………………………………………. 87

4.20 Ankle dorsi-plantar flexion moment for wall speeds 1 ft/s - 10 ft/s…… 88

4.21 Ankle dorsi-plantar flexion moment for wall speeds 15 ft/s - 35 ft/s….. 88

4.22 Variables used in the parametric study…………………………………. 89

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iv

List of Figures… continued

4.23 Variation of peak foot acceleration with peak wall speed for a

dummy in a driving position……………………………………………… 91

4.24 Variation of peak femur force with peak wall speed for a dummy in

a driving position…………………………………………………………... 92

4.25 Variation of peak femur force with wall speed and knee angle for

various dummy positions…………………………………………………. 92

Chapter 5

5.1 Applied deceleration pulse simulating impact after freefall…………. 98

5.2 Formation of a basic folding element………………………………….. 100

5.3 Comparison of impactor velocity time history…………………………. 108

5.4 Comparison of energy transformation during the impact event……. 109

5.5 Comparison of dynamic crushing load………………………………... 110

5.6 Velocities from the numerical formulation……………………………… 111

5.7 Unfiltered EA seat acceleration data…………………………………… 111

5.8 FFT of the relative velocity of the EA seat………………………………. 112

5.9 Comparison of acceleration response…………………………………. 112

5.10 Comparison of peak acceleration magnitude………………………... 113

Chapter 6

6.1 Representative Volume Cell (RVC) of the model……………………… 117

6.2 Pin-joint bar mechanism………………………………………………….. 118

6.3 One Element Elasticity Model……………………………………………. 118

6.4 Equilibrium position of the central nodes……………………………….. 120

6.5 Yarn stress-strain response of viscoelastic model……………………… 124

6.6 Yarn stress-strain response of elastic model……………………………. 124

6.7 Numerical setup of fabric axial strip test………………………………... 125

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v

List of Figures… continued

6.8 Von-Mises stress distribution for strip with 30 s-1 strain rate…………… 126

6.9 Axial strip tests of Elastic model………………………………………….. 128

6.10 Bias strip tests of Elastic model…………………………………………… 129

6.11 Axial strip tests of Viscoelastic model……………………………………. 129

6.12 Bias strip tests of Viscoelastic model…………………………………….. 130

6.13 Comparison of bias tests of elastic and viscoelastic models at

different strain rates……………………………………………………….. 131

6.14 Comparison of axial tests of elastic and viscoelastic models at

different strain rates……………………………………………………….. 132

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vi

List of Tables

Chapter 1

1.1 Human tolerance limits to acceleration ……………………………….. 6 1.2 Abbreviated Injury Scale (AIS) and sample injury types for two body

regions……………………………………………………………………….

7

1.3 HIC for various dummy sizes……………………………………………… 9 1.4 Critical values for various dummies used in the calculation of NIC…. 11

1.5 Recommended injury criteria for landmine testing……………………. 13

Chapter 2

2.1 Dimensions and material properties of the cylindrical aluminum

tubes used…………………………………………………………………..

33

2.2 Axial crushing parameters of the cylindrical aluminum tubes used…. 35

Chapter 3

3.1 Test matrix for EA seat design…………………………………………….. 49

Chapter 5

5.1 Human tolerance limits to acceleration………………………………… 96 5.2 Characteristics of the shell and impactor………………………………. 107

Chapter 6 6.1 Material and geometric properties of the Kevlar© fabric strip……….. 127

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Chapter 1

Introduction

1.1 Background

Efforts are continually underway to maximize occupant safety during

peacekeeping efforts. Anti Tank (AT) mines and Improvised Explosive Devices

(IED) pose a serious threat to the occupants of armored vehicles. High

acceleration pulses and impact forces are transmitted to the occupant through

vehicle-occupant contact interfaces, such as the floor and seat, posing the risk

of moderate to fatal injury. The use of an energy absorbing (EA) seat in

conjunction with vehicle armor plating greatly improves occupant survivability

during such an explosion. The U.S. Army does not currently have an effective EA

seat in use. The only additional protection offered to the occupant so far is the

seat cushion.

The design of such an EA seat will need to include a suitable energy absorbing

device that proves to be both effective and feasible to incorporate into current

armored vehicle designs. The EA seat will then need to be rigorously tested

against explosive ordnance. The dynamic axial crushing of aluminum tubes is

an extensively used energy absorbing element in crashworthiness studies

because of numerous advantages such as high energy absorption and a

reasonably constant operating force.

The occupant lower leg impact by the vehicle floor during an IED explosion is

also of interest in occupant survivability studies. There currently exists very little

experimental data of lower leg impact, and consequently the injury

mechanisms are still not fully understood and validation of numerical studies

becomes difficult.

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Efforts are also on to accurately model the ballistic impact of high strength

fabrics and to understand their complex behavior by virtue of their fabric

architecture. Such fabrics have high applicability to occupant safety, especially

for their anti-penetration resistance to projectiles. Different models have been

presented over the years, but a single comprehensive model that captures all

the fabric phenomena during ballistic impact does not currently exist. Simplistic

models however have been presented that capture the most important

features with good accuracy and at the least computational expense.

With the advent of supercomputing and advanced commercial finite element

codes, the emphasis is on conducting numerical simulations of real world

phenomena, to reduce the high costs of destructive testing while still preserving

the accuracy of the problem. This is the rationale behind this research which

involves conducting numerical simulations of mine blast testing of the energy

absorbing seat, occupant lower leg impact by the vehicle floor during the

explosion of an IED, and the development of a material model to realistically

simulate ballistic impact.

1.2 Literature Review

1.2.1 Energy Absorbing Seat

Concepts that are used in the crashworthiness analysis of aircraft seats are quite

similar to those used in crew protection against mine blasts. In 1988, Fox [1]

performed a feasibility study for an OH-58 helicopter energy attenuating crew

seat. Energy attenuating concepts included a pivoting seat pan, a guided

bucket, and a tension seat. In 1989, Simula Inc. prepared an Aircraft Crash

Survival Design Guide [2] for the Aviation Applied Technology Directorate. The

guide outlined various injury criteria, and energy absorbing devices amongst

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other such related topics. In 1990, Gowdy [3] designed a crashworthy seat for

commuter aircraft using a wire bending energy absorber design as seen in

Figure 1.3. This design was sub-optimal but provided satisfactory results for

vertical decelerations between 15-32 Gs.

Figure 1.1 Crashworthy seat for commuter aircraft [3]

In 1993, Laananen [4] performed a crashworthiness analysis of commuter

aircraft seats during full scale impact using SOM-LA (Seat Occupant Model –

Light Aircraft). He concluded that those current designs did not meet the then

standards for occupant safety and that vertical direction energy absorbing

devices needed to be implemented. In 1994, Haley Jr. [5] evaluated a retrofit

OH-58 pilot’s seat to study its effectiveness in preventing back injury, as seen in

Figure 1.2. In 1996, Alem et al. [6] evaluated an energy absorbing truck seat to

evaluate its effectiveness in protection against landmine blasts. In 1998, the

Night Vision and Electronic Sensors Directorate published a report on Tactical

Wheeled Vehicles and Crew Survivability in Landmine Explosions [7]. Keeman [8]

has briefly summarized the approach adopted during the design of vehicle

crashworthy structures that utilize joints and thin walled beams. In 2002, Kellas [9]

designed an energy absorbing seat for an agricultural aircraft using the axial

crushing of aluminum tubes as the primary energy absorber.

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Figure 1.2 Evaluation of an OH-58 pilot’s seat [5]

1.2.2 Foot Impact during IED/Mine blast

Joss [10] described how anti-personnel landmines have become a global

epidemic. Khan et al. [11] studied the type of hind foot injuries caused by

landmine blasts and surgical techniques available to treat it. Horst et al. [12]

experimentally and numerically studied occupant lower leg injury due to

landmine detonations under a vehicle. Horst and Leerdam [13] presented

further research being conducted into occupant safety for blast mine

detonations under vehicles. Dummies are used to study the lower leg impact,

and data such as accelerations and forces are measured along the lower leg,

from which injury criteria are assessed. Figure 1.3 shows some of the dummy leg

models used during these studies.

(a) (b) (c)

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(d) (e)

Figure 1.3 a) Prosthetic leg model b) MADYMI detailed leg c) MADYMO Thor Lx

leg d) Interior view of the modeled leg e) HYBRID III Denton leg [13] 1.2.3 Human Injury Criteria

In order to determine the effectiveness of a design that protects occupants

against injury caused by crash and mine blasts, certain injury criteria need to be

defined. Occupant crash data such as forces, moments and accelerations are

collected from dummies used experimental tests and simulations and then

compared to these injury criteria to assess Occupant Survivability and Human

Injury. Figure 1.4 displays numerical dummies developed by LSTC for use in the

commercial finite element code LSDYNA©.

(a) (b)

Figure 1.4 a) GEBOD dummy b) HYBRID III dummy

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a) Generalized Human Tolerance Limits to Acceleration

Table 1.1 displays the human tolerance limits for typical crash pulses along

three mutually orthogonal axes, for a well restrained young male. These values

provide a general outline of the safe acceleration limit for a human during a

typical crash. However, the time duration of the applied acceleration pulse has

not been specified. Higher acceleration pulses can be sustained for shorter

durations compare to lower acceleration pulses for longer durations, thus the

time duration in question is important [14].

Direction of Accelerative Force

Occupant’s Inertial Response Tolerance Level

Headward (+Gz) Eyeballs Down 25 G Tailward (-Gz) Eyeballs Up 15 G Lateral Right (+Gy) Eyeballs Left 20 G Lateral Left (-Gy) Eyeballs Right 20 G Back to Chest (+Gx) Eyeballs-in 45 G Chest to Back (-Gx) Eyeballs-out 45 G

Table 1.1 Human tolerance limits to acceleration [14]

b) Injury Scaling

Injury scaling is a technique for assigning a numerical assessment or severity

score to traumatic injuries in order to quantify the severity of a particular injury.

The most extensively used injury scale is the Abbreviated Injury Scale (AIS)

developed by the American Association for Automotive Medicine and originally

published in 1971. The AIS assigns an injury severity of “one” to “six” to each injury

according to the severity of each separate anatomical injury. Table 1.2 provides

the AIS designations and gives examples of injuries for two body regions. The

primary limitation of the AIS is that it looks at each injury in isolation and does not

provide an indication of outcome for the individual as a whole. Consequently,

the Injury Severity Score (ISS) was developed in 1974 to predict probability of

survival.

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AIS Severity Head Spine 0 None - - 1 Minor Headache or Dizziness Acute Strain (no fracture or

dislocation)

2 Moderate Unconsciousness less than 1 hr., Linear fracture

Minor fracture without any cord involvement

3 Serious Unconscious, 1-6 hrs., Depressed fracture

Ruptured disc with nerve root damage

4 Severe Unconscious, 6-24 hrs., Open fracture

Incomplete cervical cord syndrome

5 Critical Unconscious more than 24 hr, Large hematoma , (100cc)

C4 or below cervical complete cord syndrome

6 Maximum Injury (virtually non-survivable)

Crush of Skull

C3 or above complete cord syndrome

Table 1.2 Abbreviated Injury Scale (AIS) and sample injury types

for two body regions [14]

The ISS is a numerical scale that is derived by summing the squares of the three

highest body region AIS values. This gives a score ranging from 1 to 75. The

maximal value of 75 results from three AIS 5 injuries, or one or more AIS 6 injuries.

Probabilities of death have been assigned to each possible score. Table 1.2

provides the AIS designations and gives examples of injuries for two body

regions. [14]

c) Dynamic Response Index (DRI)

The DRI is representative of the maximum dynamic compression of the vertebral

column and is calculated by describing the human body in terms of an

analogous, lumped-mass parameter, mechanical model consisting of a mass,

spring and damper. The DRI model assesses the response of the human body

to transient acceleration-time profiles. DRI has been effective in predicting

spinal injury potential for + Gz acceleration environments in ejection seats. DRI is

acceptable for evaluation of crash resistant seat performance relative to spinal

injury, if used in conjunction with other injury criteria including Eiband and

Lumbar Load thresholds. [14]

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d) Lumbar Load Criterion

The maximum compressive load shall not exceed 1500 pounds (6672 N)

measured between the pelvis and lumbar spine of a 50th-percentile test

dummy for a crash pulse in which the predominant impact vector is parallel to

the vertical axis of the spinal column. This is one of the most widely used

criterions in vertical crash and impact testing. If the spinal cord is severely

compressed or severed, it can lead to either instant paralysis or fatality. [1, 9, 13-

16]

e) Head Injury Criterion (HIC)

HIC was proposed by the National Highway Traffic Safety Administration (NHTSA)

in 1972 and is an alternative interpretation to the Wayne State Tolerance Curve

(WSTC).[14, 15] It is used to assess forehead impact against unyielding surfaces.

Basically, the acceleration-time response is experimentally measured and the

data is related to skull fractures. Gadd [17] had suggested a weighted-impulse

criterion (GADD Severity Index, GSI) as an evaluator of injury potential defined as:

(1.1)

where

SI = GADD Severity Index

a = acceleration as a function of time

n = weighting factor greater than 1

t = time

Gadd plotted the WSTC data in log paper and an approximate straight line

function was developed for the weighted impulse criterion that eventually

became known as GSI. The Head Injury Criteria is given by

n

tSI a dt= ∫

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(1.2)

where

a(t) = acceleration as a function of time of the head center

of gravity

t1,t2 = time limits of integration that maximize HIC

FMVSS 208 (Federal Motor Vehicle Safety and Standards) originally set a

maximum value of 1000 for the HIC and specified a time interval not exceeding

36 milliseconds. HIC equal to 1000 represents a 16% probability of a life

threatening brain injury. HIC suggests that a higher acceleration for a shorter

period is less injurious than a lower level of acceleration for a higher period of

time. As of 2000, the NHTSA final rule specified the maximum time limit for

calculating the HIC as 15 milliseconds. [4, 9, 17-23] Table 1.3 shows the HIC for

various dummy sizes.

Dummy Type

Large size Male

Mid size Male

Small size Female

6 year old child

3 year old child

1 year old infant

HIC15 Limit 700 700 700 700 570 390

Table 1.3 HIC for various dummy sizes [15]

f) Head Impact Power (HIP)

A recent report included the proposal of a new HIC entitled Head Impact Power

(HIP) It considers not only kinematics of the head (rigid body motion of the skull)

but also the change in kinetic energy of the skull which may result in

deformation of and injury to the non-rigid brain matter. The Head Impact Power

(HIP) is based on the general rate of change of the translational and rotational

kinetic energy. The HIP is an extension of previously suggested “Viscous Criterion”

1

2

2.5

2 1( ) ( )t

t

HIC t t a t dt⎡ ⎤

= − ⎢ ⎥⎢ ⎥⎣ ⎦∫

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first proposed by Lau and Viano in 1986, which states that a certain level or

probability of injury will occur to a viscous organ if the product of its compression

‘C’ and the rate of compression ‘V’ exceeds some limiting value [14].

g) Injury Assessment Reference Values (IARS)

This rule adopts new requirements for specifications, instrumentation, test

procedures and calibration for the Hybrid III test dummy. [14]. The regulation’s

preamble has a detailed discussion of the injury mechanisms and the relevant

automotive mishap data for each of the injury criteria associated with the Hybrid

III ATD. Military test plans should implement these criteria.

h) Neck Injury Criterion (NIC)

The NIC considers relative acceleration between the C1 and T1 vertebra and is

given by [24]:

(1.3)

with

(1.4)

NIC must not exceed 15 m2/s2. [25]Another criteria NIC50 refers to NIC at 50mm

of C1-T1 (cervical-thoracic) retraction. Newly proposed Nij criteria by NHTSA

combines effects of forces and moments measured at occipital condyles and

is a better predictor of cranio-cervical injuries. Nij takes into account NTE (tension-

extension), NTF (tension-flexion), NCE (compression-extension), NCF (compression-

flexion). FMVSS specification No.208 requires that none of the four Nij values

exceed 1.4 at any point. The generalized NIC is given by [26]:

2( ) 0.2 ( ) [ ( )]rel relNIC t xa t V t= +

1

1

( ) ( ) ( )

( ) ( ) ( )

T Headrel x x

T Headrel x x

a t a t a t

v t a t a t

= −

= −∫ ∫

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(1.5)

where

Fz = Upper Neck Axial Force (N),

My = Moment about Occipital Condyle

Fzn = Axial Force Critical Value (N), and

Myn = Moment Critical Value (N-m).

In FMVSS 208 (2000) final rule a neck injury criterion, designated Nij, is used. This

criterion is based on the belief that the occipital condoyle-head junction can

be approximated by a prismatic bar and that the failure for the neck is related

to the stress in the ligament tissue spanning the area between the neck and the

head. Nij must not exceed 1.0. [16, 22, 24, 26] Table 1.4 displays the critical

values for various dummies used in the calculation of Nij [15].

Dummy Type

Fzc (N) Flexion

Fzc (N) Extension

Myc (Nm) Flexion

Myc (Nm) Extension

Comments

3 year old dummy

2120 2120 68 27

Peak tension force < 1130 N Peak compression force < 1380 N

50th percentile

6806 6160 310 135

Peak tension (Fz) < 4170 N Peak extension (Fz) < 4000 N

Table 1.4 Critical values for various dummies used in the calculation of NIC [15]

i) Chest Criteria

Peak resultant acceleration will not exceed 60 G’s for more than 3 milliseconds

(Mertz, 1971) as measured by a Tri-axial accelerometer in upper thorax. Also, the

chest compression will be less than 3 inches for the Hybrid III dummy as

measured by a chest potentiometer behind the sternum [14, 15].

Z Yij

ZC YC

F MN F M⎛ ⎞ ⎛ ⎞= +⎜ ⎟ ⎜ ⎟⎝ ⎠ ⎝ ⎠

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j) Viscous Criterion

Viscous Criterion (V*C) – defined as the chest compression velocity (derived by

differentiating the measured chest compression) multiplied by the chest

compression and divided by the chest depth. This criterion has been mentioned

for the sake of completeness of information; however it is not widely used [14].

k) Femur Force Criterion

This criterion states that the compressive force transmitted axially through each

upper leg should not exceed 2,250 pounds or 10,000 N. Impulse loads that

exceed this limit can cause complete fracture of the femoral bone as well as

sever major arteries that can cause excessive bleeding. In numerical dummies,

discrete spring elements of known stiffness are included within the leg model,

from which the femur axial compressive force is easily extracted. In actual

dummies, load cells are placed on the dummy’s leg, which are calibrated to

provide the compressive force at the femur. [12, 13, 14, 27].

l) Thoracic Trauma Index (TTI)

The Thoracic Trauma Index is given by:

(1.6)

GR is the greater of the peak accelerations of either the upper or lower rib,

expressed in G’s. GLS is the lower spine peak acceleration, expressed in G’s. The

pelvic acceleration must not exceed 130 G’s [14].

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m) Mine Blast Injury Criteria

U.S. Army’s Aberdeen Test Center has established injury criteria for mine blast

testing of high mobility wheeled vehicles. The injury criteria can also provide

guidance in standard crash impact testing orientations. These criteria are

comprehensive and provide a good assessment of injury that takes into

account the entire occupant’s body subject to any combination of external

stimuli associated with a mine blast. A few criteria are listed in Table 1.5 [14].

HYBRID III Simulant Response Parameter

Symbol (units) Assessment Reference Values

Head Injury Criteria HIC 750 ~5% risk of brain injury Lumbar spine axial compression force Fz (N) 3800 N (30ms) Femur or Tibia axial compression force Fz (N) 7562 N (10ms) Seat (Pelvis) vertical DRI DRI – Z(G) 15, 18, 23 G (low, med, high risk) Tibia axial compressive force combined with Tibia bending moment

F (N) M (N-m)

F/Fc – M/Mc < 1 where Fc=35,584N and Mc=225N-m

Table 1.5 Recommended injury criteria for landmine testing [14]

1.2.4 Dynamic Axial Crushing of Circular Tubes

The axial crushing of circular tubes by progressive plastic buckling has been the

subject of an extensive study over the years [28-47]. Perhaps one of the most

widely referred to technical paper in this field is that of Abramowicz and Jones

[29]. Gupta et al. [46, 47] studied the axisymmetric folding of tubes under axial

compression and incorporated both the change in tube thickness and yield

stress values of tension and compression into their model. Karagiozova et al.

[37, 38] studied the inertia effects, and dynamic effects on the buckling and

energy absorption of cylindrical shells under axial impact.

Galib and Limam [35] investigated the static and dynamic crushing of circular

aluminum tubes both experimentally and numerically using the commercial

software RADIOSS©. Bardi et al. [33] compared experimental results of tubes

under axial compression to nuemerical studies using the commercial software

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ABAQUS©. Numerical analyses sometimes contain inaccuracies due to the high

mesh-sensitivity of the impact simulation. There is a difference in shell response

when simulating impact as a moving mass striking the stationery shell as

commonly observed in laboratory conditions, and as a the moving shell striking

a stationery rigid wall. Also, inappropriately filtering the data can lead to

significant under estimation of results such as crushing load [38]. Alghamdi [48]

reviewed common shapes of collapsible energy absorbers and different modes

of deformation of the most common ones. Nilakantan [49] presented a

numerical formulation to study the dynamic axial crushing of circular tubes

based on an energy balance approach. Figure 1.9 displays an axially crushed

aluminum tube, modeled in LSDYNA© [49, 50].

Figure 1.5 Axially crushed aluminum tube

1.2.5 Ballistic impact of dry woven fabrics

I) Modeling of the ballistic impact

Over the past few decades, many different techniques have been used to

derive the constitutive relations and model the overall fabric behaviour for use in

ballistic impact applications. Different models include various effects and

phenomena associated with the ballistic impact of fabrics, however there is no

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single comprehensive model that reproduces and represents all phenomena at

the same time. However many simplistic models have been found to yield

results that are realistic.

a) Classification according to underlying theory

Researchers adopt different ways to approach the modeling of ballistic

response of dry woven fabrics. The methodology is discussed in later

paragraphs. This section simply enlists the approaches adopted by various

authors over time.

i) Analytical

Analytical methods make use of general continuum mechanics equations and

laws such as the conservation of energy and momentum. Governing equations

are set up using various parameters involved during the impact process.

Analytical methods are useful to handle simple physical phenomena, but

become increasingly complicated as the phenomena become more complex

and involve many variables.

This includes work by Vinson et al. [51], Taylor et al. [52], Parga-Landa et al.[53],

Chocron-Benloulo et al.[54], Navarro [55], Billon et al. [56], Gu [57], Hetherington

[58], Cox et al. [59], Naik et al. [60], Phoenix and Porwal [61, 62], Walker [63],

and Xue et al. [64].

ii) Semi-Empirical and empirical

Empirical studies rely on the analysis of data obtained through experimental

work in order to examine the fabric response and obtain constitutive relations

and failure criterion. This includes curve fitting, non-linear regression analysis of

experimental data, and the use of statistical distributions. Parametric equations

relate the various parameters studied during the experiment. The method is

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useful when there are small numbers of variables to correlate [65]. Further, the

shortcoming is that the accuracy of the obtained model will depend on the

accuracy and completeness of the collected data. This includes work by

Cunniff [66], Shim et al. [67], and Gu [68].

iii) Numerical

This approach relies on techniques such as finite element and finite difference

methods, and the use of commercial packages such as ABAQUS©, DYNA3D©,

and LSDYNA© to conduct the analysis or simulation. Contact between and

amongst the yarns and projectile is better handled through the use of

commercial software. Further the fabric yarns may be modeled explicitly. This

includes work by Lomov et al. [69], Johnson et al. [70], Billon et al. [56], Lim et al.

[71], Shim et al. [72], Tan et al. [73, 74], Lim et al. [71], Roylance [75, 76], Hearle

[77], Boisse et al.[78], D’Amato et al. [79, 80], Duan et al. [81], Gu et al. [82],

Simons et al. [83], Teng et al. [84], Tarfaoui et al.[85, 86].

iv) Micromechanical

In a micromechanical approach, the fabric geometry is usually represented by

a representative volume cell or RVC, which by repeated translation will yield the

entire fabric structure. This RVC is then analyzed through equilibrium of forces,

variational potential energy methods, et cetera. to compute displacements,

stresses and strains. This includes work by Tabiei et al. [87, 88], Sheng et al. [89],

Dasgupta et al. [90], Tan et al. [91], Vandeurzen et al. [92] and Xue et al. [93].

v) Multi-scale constitutive

Multi-scale approaches make different assumptions of fabric behavior at

different scales. This arises due to the inherent multi-scale nature of fabrics which

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are constructed from micro-scale fibrils. For example, the fabric behaves as a

continuum membrane at the macro scale; and at the micro scale, the

behavior is accounted for by constitutive modeling of the yarns as elastic or

viscoelastic members. This includes work by Nadler et al. [94] and Zohdi and

Powell [95].

vi) Variational

Variational principles include the Reissner variational principle, Galerkin method,

Rayleigh-Ritz method, and principal of minimum potential energy. These yield

governing differential equations which can then be solved using finite element

and finite difference methods. This includes work by Leech et al. [96], Roy et al.

[97], Sheng et al. [89], and Sihn et al. [98].

vii) Experimental

In order to validate the results from theoretical approaches, experimental data

is required. Further, by experimentally studying the ballistic impact of woven

fabrics, many new mechanisms of energy absorption and failure become

apparent, and effect of various parameters on the ballistic response can be

studied. This includes work by Starratt et al. [99], Susich et al. [100], Field et al.

[101], Wilde et al. [102], Prosser [103, 104], Cunniff [105], Shockey et al. , Wang

et al. [106, 107], Shim et al. [108], Lundin [109], Rupert [110], Orphal et al. [111],

and Manchor et al. [112].

b) Research based on number of fabric plies studied

Majority of the literature available today dealing with ballistic impact of fabrics

focuses on experimental and theoretical work of a single fabric layer. Few

literature deals with the ballistic impact of armor composed of multiple identical

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layers of fabric such as Chocron-Benloulo et al.[54], Hearle et al. [77], Parga-

Landa et al. [53], Vinson et al. [51], Taylor et al. [52], Barauskas et al. [113],

Porwal and Phoenix [62], Sheng et al. [89], Vandeurzen et al. [92], Zohdi et al.

[114], Lomov et al. [69], Navarro et al. [55], Billon et al. [56], Tan et al. [74], Lim et

al. [74], Cunniff [115-117] and Schweizerhof et al. [118]. There is very limited work

on ballistic impact of fabrics composed of multiple layers of different fiber

material such as Cunniff et al. [119], Hearle [120] and Porwal and Phoenix [62].

c) Commercial finite element software packages used for analysis

With the advent of supercomputing, commercial finite element packages are

gaining popularity, because of the low cost alternative offered to costly

experimentation and destructive testing, as well as the potential testing of

materials not yet developed. Finite element packages also offer the option of

using of user-defined material models in place of the standard material models

and thereby provide a useful platform for the testing of new theories utilizing a

numerical form of solution. Finite element codes also can handle interaction

between the projectile and fabric, penetration, contact and friction between

yarns, and the deformation and failure of the fabric. Thus it is a very useful tool

for the simulation of ballistic impact of woven fabrics.

In the ballistic impact testing of fabrics, the most commonly used commercial

finite element packages are ABAQUS© by ABAQUS Inc. which involves the

ABAQUS/Standard and ABAQUS/Explicit solvers, DYNA3D© which is a part of a set

of public codes developed in the Methods Development Group at Lawrence

Livermore National Laboratory (LLNL) [121], and LS-DYNA© by Livermore Software

Technology Corporation [122, 123].

A few examples of research into ballistic impact of woven fabrics that use

these finite element packages are; ABAQUS© used by Xue et al. [64] and Diehl

et al. [124], DYNA3D© used by Shockey et al. [125, 126] and Lim et al. [71], and

LSDYNA© used by Tabiei et al. [87, 88, 127, 128], Gu et al. [57, 68], Shockey et

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al. [129-131] and Duan et al. [81, 132-134], Shahkarami et al. [135], and

Schweizerhof et al [118].

d) Computer software and codes for solid modeling and computing

properties of textile composites

Brown et al. [136] describes a technique to automatically generate a solid

model of the representative volume element (RVE) of the fabric structure. The

solid model is generated using a program file written in I-deas® Open

Language. Cox et al. [59] lists various codes used in the computation of textile

composites properties, especially macroscopic stiffness, strength and

occasionally damage tolerance. These include μTEX-10 and μTEX-20 by Marrey,

R. V. et al, TEXCAD by Naik, Rajiv A., PW, SAT5, SAT8 by Raju, I. S., SAWC by

Whitcomb, J., CCM-TEX by Pochiraju, K., WEAVE by Cox, B., and BINMOD by

Cox, B. et al.

e) Approaches to modeling, based on author(s)

Vinson and Zukas [51] and Taylor and Vinson [52] modeled the fabric as conical

isotropic shells. The model treated the fabric as isotropic and did not

differentiate between warp and weft directions leading to a conical shaped

transverse deflection of the fabric, which is contrary to experimental findings.

Leech et al. [96] and Hearle et al. [77] modeled the fabric as a net. Prosser

[103] derived a mathematical model for the FSP-nylon system in his study of

ballistic impact of nylon panels by 0.22 caliber FSPs. He stated that for a set of

Vc determinations, plots of Vr (residual) and Vs (striking) can be adequately

represented by parabolas. There are periods in the plots of the squared V50

velocities and number of layers, where the plot linearity signifies that the

mechanism of penetration is constant. Cunniff [119] examined system effects

that occur during ballistic impact of woven fabrics by developing a conceptual

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framework that relates ballistic impact mechanics of a single yarn to ballistic

impact mechanics of the fabric. Ting J. et al. [137] extended on the work of

Roylance et al. [138] and provided for contact between adjacent plies of a

multi-ply target and introduced slippage at yarn cross over points. Their model

predicted an increase in the ballistic limit when the friction of slippage

increases. Cunniff and Ting [139] developed a numerical model that treated

yarns as elastic rod elements, based on the work of [76]. Walker [63] developed

a constitutive model for an anisotropic fabric sheet based on elastic

deformations of the fibers. The centerline deflection of the fabric sheet was

solved with an approximate analytical solution that yields the final deformed

fabric shape and a simple equation for the force-displacement curve. Ting et

al. [137] and Shim et al. [72] modeled the fabric material as an orthogonal grid

of pin-jointed member elements. Shim et al. [67] used a three-element spring-

dashpot model to represent the viscoelastic behavior of the fibers and capture

its strain-rate sensitivity. The model accounts for yarn crimp. Roylance et al. [75]

modeled the fabric as an orthogonal mesh assembly of nodes interconnected

by flexible fiber members. A finite difference method was applied at the yarn

crossover points to simulate ballistic impact. Artificial buck up springs in the

transverse direction play a significant role in the ballistic limit determination. The

model lacks contact surfaces to interact with the projectile. Johnson et al. [70]

modeled the fabric with both pin-jointed members and thin membrane shells.

The computational model used a constitutive strength and fracture model that

depended on individual fiber characteristics. Bi-linear stress strain relationship is

assumed for the bar members to simulate yarn crimp. Shell elements provide

the contact surface and shear stiffness.

Shockey et al. [125, 126, 129-131] used finite solid elements to explicitly model

individual yarns and combined them in an orthogonal weave to form the fabric.

The model was found to be computationally very expensive; and became

unstable as the number of elements used to discretize the yarns crosses a

certain value. However the explicit yarn modeling allowed for observation of

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phenomena such as yarn-yarn interaction and yarn pull-out. Chou et al. [140]

reviewed recent advances in the fabrication and design of three dimensional

textile preforms. Their review detailed advances made towards realizing an

integrated approach in the design and manufacture of three dimensional

textile preforms. Rao et al. [141] experimentally and theoretically studied the

influence of twist on the mechanical properties of high performance fiber yarns

including Kevlar© 29, Kevlar© 49, Kevlar© 149, Vectran© HS, Spectra© 900,

and Technora©. A model based on composite theory was developed to

highlight the decrease in modulus as a function of degree of twist and elastic

constants of the fibers. They concluded the existence of an optimal twist angle

of around 7° where all fibers exhibit their maximum tensile strength. At higher

angles of twist, the fibers get damaged reducing their tensile strength. The study

of Gasser et al. [142] aimed at recalling the specificity of the mechanical

behavior of dry fabrics and to understand the local phenomena that influence

the macroscopic behavior. A 3-d finite element analyses was compared to

biaxial tests on several fabrics. The developed model helped understand the

main aspects that lead to the specific behavior of woven fabrics and also help

design new fabrics by varying mechanical and geometric parameters. Billon et

al. [56] considered the fabric to be a collection of pin jointed members. Both an

analytical method and direct step finite element method were used and their

results were compared to experimental results. The input to the analytical model

includes fabric material properties, a constitutive relation and a failure criterion.

The model then predicts the ballistic limit and residual velocity. Lim et al. [71]

modeled fabric armor composed of Twaron© fibers in the finite element code

DYNA3D, using membrane elements under the continuum assumption of fabric.

A standard isotropic strain-rate dependant elastic-plastic model was used to

incorporate the strain-rate dependency of the Twaron fibers studied in [67].

Since the fabric architecture such as yarn crimp and cross section was not

considered, and the material was treated as isotropic, the deformation of the

fabric was conical when in fact it should have been pyramidal. Cheeseman

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and Bogetti [143] reviewed the factors that influence ballistic performance,

specifically, the material properties of the yarn, fabric structure, projectile

geometry and velocity, far field boundary conditions, multiple plies and friction.

Ivanov and Tabiei [144] considered the fabric to be a grid of pin jointed bar

elements in their micromechanical approach. Tabiei et al.[87, 88, 144-146]

modeled the fabric as thin shells and developed their own material model for

use with the shell elements, that included effects of fiber reorientation and

locking angle, and fabric architecture such as crimp. The trellis mechanism

behavior of the flexible fabric in a free state before the packing of the yarns is

achieved by discounting the shear moduli of the yarn material. The fibers were

treated as viscoelastic members with a strain-rate based failure. The model was

implemented as a user defined subroutine in LSDYNA©. Contact forces at the

fiber cross over points were used to determine the rotational friction that

dissipated a part of the energy during reorientation.

Figure 1.10 Numerical simulation of ballistic impact of fabric in LSDYNA© by

Tabiei [144]

Gu [68] explicitly modeled individual yarns and combined them to form the

fabric mesh. A bimodal Weibull distribution was used to form the tensile

constitutive equations of the Twaron© yarn at high strain rates. Diehl et al. [124]

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used ABAQUS/Standard and ABAQUS/Explicit to model structural performance of

systems containing woven fabrics. They investigated the limitations and

numerical problems of classical orthotropic lamina models, and introduced an

improved generalized cargo-net approach, models for membrane-only and

general shell behaviors, and experimental measurements utilized to obtain

effective modeling constants and parameters. Termonia [147] formulates the

mechanics of wave propagation in terms of impulse-momentum balance

equations, which are solved at each fiber cross over using a finite difference

technique. The model accounts for projectile characteristics such as shape,

mass and velocity, and also fiber properties such as denier, modulus and tensile

strength. The model also considers yarn slippage through the clamps, which is

often seen in experimental work. Termonia [148] also numerically investigates

the puncture resistance of fibrous structures by driving a needle shaped

projectile through a single fabric ply at a constant velocity of 100 m/s. Termonia

et al. [149] theoretically studied the influence of the molecular weight on the

maximum tensile strength of polymer fibers.

Barauskas and Kuprys [150] developed a model that could handle the collision

between fabric yarns in woven structures, where the longitudinal elastic

properties of each yarn are presented as a system of non-volumetric springs.

Their collision and response algorithm worked in a 3-d space and was based on

tight fitting of the yarns by using oriented bounding boxes, with a separation axis

theorem to handle collision detection between the oriented bounding boxes.

They assumed the yarn cross-sectional area to be constant and elliptical in

shape, with changing lengths of axes. Their system is characterized by a

significant reduction in degrees of freedom while still preserving the volumetric

behavior of the structure, when compared to traditional models that consider

yarns as fully deformable volumetric bodies. Phoenix and Porwal [61] developed

a membrane model based on an analytical approach to study the ballistic

response and V50 performance of multi-ply fibrous systems. They developed

solution forms for the tensile wave and curved cone wave considering constant

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projectile velocity, and obtained an approximate solution for the membrane

response using matching boundary conditions at the cone wave front. Then

projectile deceleration due to membrane reactive forces was considered to

obtain other results such as cone velocity, displacement, and strain

concentration versus time. A later study by Porwal and Phoenix [62] based on

the above membrane model, studied the system effects in ballistic impact of a

cylindrical projectile into flexible, multi-layered targets with no bonding between

the layers. Each layer was assumed to have in-plane, isotropic, and elastic

mechanical properties.

II) Constitutive modeling of yarn

The fibers used in the ballistic impact resistant fabrics are viscoelastic. During

their constitutive modeling, it is important to account for their strain-rate

sensitivity. Properties such as the elastic modulus are dynamic and vary non-

linearly with strain. If static values are used during the analysis of the ballistic

impact of fabrics, it will lead to inconsistencies between numerical and

experimental results, as was observed in [76].

i) Based on the three element spring-dashpot model

Lim et al. [71] and Ivanov et al. [144] used a three-element spring dashpot

model to represent the viscoelastic behavior of the Twaron fibers. Twaron© fibers

are very similar to Kevlar© fibers as both belong to the Aramid family and have

identical static properties.

The viscoelasticity exists as a property of all materials but it is significant at room

temperature for polymeric materials mainly. The creep and the stress relaxation

are the results of the viscoelastic behavior of materials. For impact simulations,

we do not need the long-term effects of the viscoelasticity, so that the material

behavior can be simply described by a combination of one Maxwell element

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without the dashpot and one Kelvin-Voigt element. The differential equation of

viscoelasticity can be derived from the model equilibrium in the form

(1.7)

where σ , ε , and ε are the stress, strain and strain rate respectively. Constants

Ka, Kb and μb can be derived experimentally and vary according to the material.

The principal behind the response of the fibers at different strain rates is as

follows. At low strain rate, below the transition strain rate, the dashpot offers little

resistance as damping is proportional to the velocity. The dashpot and parallel

connected spring are free to move according to spring stiffness Kb. Since Ka >

Kb, spring A remains rigid and spring B displaces preferentially. However at higher

strain rates, above the transition strain rate, the dashpot offers a resistance

higher than the stiffness of spring A. Now spring A moves preferentially

compared to the dashpot-spring B assembly, which remains rigid. In reality,

spring A represents the primary or intramolecular covalent bonds of the fiber

microstructure while spring B represents the secondary bonds which are the Van

der Waal forces and hydrogen bonds. The failure associated with these bonds is

discussed in later sections. The transition strain rate for Twaron© CT716 was

experimentally observed by [71] to be 410s-1. Based on their numerical

modeling, Ivanov et al. [144] observed the transition strain rate of 840 denier

Kevlar© 129 to be 100s-1.

ii) Based on Weibull distribution

Gu used a Weibull distribution of yarn strength to describe the stress-strain

response of Twaron fibers, based on [151, 152]. He used a two modal Weibull

distribution using the observation form [153] that aramids have a distinct skin-

core structure and that defects in the skin and core are the two main factors

( )a b b a b b aK K K K Kσ μ σ ε μ ε+ + = +

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that influence the yarn strength composed of filaments without twist. From this

Gu obtained the following constitutive relation

(1.8)

The scale (m) and shape (σ) parameters were calculated from tensile

experimental data of yarn filaments [57] with the Levenberg-Marquardt

nonlinear least square estimation method [154]. Different constitutive relations

were obtained based on the strain rate. Wang et al. [106, 107] also used a

bimodal Weibull statistical distribution model to describe the strain-rate

dependence of Kevlar© 49 aramid fiber bundles for strain rates varying from

10-4 s-1 to 103 s-1.

1.3 Scope of Work

The stages involved in this research are as follows, but not necessarily in that

order

1) Extensive review of literature

2) Preliminary design of energy absorbing seat

a. Modeling and meshing of structure in HYPERMESH©

b. Setup of simulation inputfile in LS-PREPOST©

3) Validation of design by comparing simulation data with experimental

data of vertical drop testing of energy absorbing seat

4) Conducting numerical simulations of the mine blast on the energy seat

and studying occupant survivability

a. Use of prescribed acceleration pulses simulating a mine blast

b. Extraction of dummy data and comparison with injury criteria

1 2

01 02

expm m

E EE ε εσ εσ σ

⎡ ⎤⎛ ⎞ ⎛ ⎞⎢ ⎥= − −⎜ ⎟ ⎜ ⎟⎢ ⎥⎝ ⎠ ⎝ ⎠⎣ ⎦

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5) Final energy absorbing seat design including additional energy absorbing

concepts

a. High density foam / airbag cushion

b. Use of GEBOD and HYBRID III dummy

6) Conducting numerical simulations of the impact of occupant lower leg

by the vehicle floor during IED explosion under an armored vehicle

a. Use of GEBOD and HYBRID III dummy

b. Variation of wall speed – 1, 5, 10, 15, 25, 35 ft/s

c. Seated Straight and Driving position

7) Development of a numerical formulation to study the response of

dynamic axial crushing of circular tubes and to predict occupant

survivability during impact events

a. Program coded in MATLAB©

b. Comparison with experimental data for validation

c. Used in two different configurations

8) Development of a material model to realistically simulate ballistic impact

of loose woven fabric with elastic crimped fibers, and integration of the

material model into LS-DYNA©

a. Utilizes a micromechanical approach

b. Subroutine coded in FORTRAN© and integrated into LS-DYNA© as

a User Defined Material Model.

c. Comparison of axial testing of the elastic fabric model with the

viscoelastic fabric model.

1.4 Outline of Thesis

Chapter 1 introduces the subject of this research and extensively reviews the

previous literature. The steps followed during the course of this research are

briefly presented.

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Chapter 2 looks at the design of the energy absorbing seat and the setup of the

numerical model. The various components of the design and the input pulses

used are studied. Initial simulation results of vertical drop testing are compared

with experimental results for validation.

Chapter 3 presents the detailed results of all the numerical simulations

conducted with the energy absorbing seat in accordance with the test matrix.

The crushing of aluminum tubes is studied. The final EA seat design is then

presented. A new mechanism using a honeycomb structure is briefly

introduced.

Chapter 4 studies the occupant lower leg impact during a mine blast. The

numerical setup is explained. A series of floor impact simulations are conducted

and numerical results are studied. A parametric study is also introduced.

Chapter 5 presents a numerical formulation using an energy balance approach

to study the dynamic axial crushing of circular tubes. The formulation is

implemented as a program and results are compared to experiments.

Chapter 6 presents a micromechanical model to study the ballistic impact of

loose woven fabrics with elastic crimped fibers. Fabric axial tests at various strain

rates are numerically simulated and results are compared to the viscoelastic

model.

Appendix I lists the source code for the dynamic axial crushing of circular tubes

and Appendix II lists the source code used to derive the incremental stress-strain

relationship for the elastic material model.

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Chapter 2

Energy Absorbing Seat

2.1 Preliminary Design

The crashworthy commuter aircraft seat used in [9] forms the basis for this

design. Figure 2.1 displays the preliminary design of the energy absorbing seat

structure.

Figure 2.1 Preliminary EA seat design

The support structure rigidly holds two cylindrical steel rails inclined at a 20° angle

to the vertical. A set of upper and lower cylindrical brackets which slide along

the rails are attached to the seat. A steel collar is rigidly attached to each rail.

The aluminum crush tubes are coaxial with the steel rails and are positioned

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between the upper bracket and collar. During vertical drop testing, the upper

brackets move downwards causing the crushing of the aluminum tubes against

the collars, which is the primary energy absorption principal used here. During a

mine blast, the entire support structure along with the attached collars move

upwards causing the crushing of the tubes against the upper brackets. For the

initial testing without a numerical dummy, the density of the seat material is

scaled to include the weight of an occupant. Later on, the occupant is

modeled using both a GEBOD dummy and a 5th percentile HYBRID III dummy.

An initial time delay of 50 ms in all simulations allows for gravity settling of the

dummy against the seat to ensure proper contact. In addition to the aluminum

crush tubes, further energy absorbing elements such as high density foam

cushions and airbag cushions are added to the design.

While modeling the structure in LSDYNA, certain simplifications are made to the

model. This facilitates the replacement of detailed structures and designs with

equivalent simplistic representations. The two inclined steel rails are attached to

the support structure by creating a ‘Node Set’ consisting of nodes belonging to

the rail and structure at the joint location and then using this node set in the

*CONSTRAINED_NODAL_RIGID_BODY keyword definition which ensures a rigid

joint between the rail and structure. The seat structure is modeled using shell

elements and a rigid material model. The reason for using rigid material defined

by the *MAT_RIGID keyword is that they are computationally efficient when

representing parts that do not deform or do not need to be monitored during

the study. Rigid elements are bypassed during the element processing in

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LSDYNA. The set of four brackets are also attached to the seat by creating a

node set and then using this node set in a nodal rigid body definition. Figure 2.2

displays the linear dimensions of the rail, brackets, collar and crush tube.

Figure 2.2 Specifications of the rail substructure

Contact definitions are created in LSDYNA to specify contact between the rail,

crush tube, brackets, and collar. *CONTACT_AUTOMATIC_SURFACE_TO_SURFACE

and *CONTACT_AUTOMATIC_GENERAL are used to this effect. By using the

AUTOMATIC specification, the orientation of the shell segment normals is

automatic. The SOFT=2 option can be used to activate a different contact

formulation and causes the contact stiffness to be calculated considering the

global time step and nodal masses. This approach is generally more effective

when creating contact definitions between components of different mesh

densities and material stiffness.

The crush tube has the finest mesh as it deforms the most during the simulation

thus controlling the time step, and constitutes the energy absorbing member. If

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Stress Vs. Strain for *Mat 24 - Aluminum

440004500046000470004800049000500005100052000

0 0.1 0.2 0.3 0.4 0.5 0.6

Strain (%)

Stre

ss (M

Pa)

*Mat 24 - Aluminum

the mesh is too fine, the time step falls to very small values causing the

simulation to run indefinitely. However LSDYNA Material Model 24 which is

*MAT_PIECEWISE_LINEAR_PLASTICITY allows the user to specify a minimum time

step for the material and when the simulation time step falls below this defined

value, the controlling element with this material model is deleted. Thus the

overall minimum time step of the problem can be controlled without using Mass

Scaling which adds mass to the component to prevent the time step from

falling below a certain value. Also, this material model allows an arbitrary stress

versus strain curve as well as arbitrary strain rate dependency to be defined,

which is illustrated by the curve shown in Figure 2.3 below. The yield stress needs

be specified for this model and is given a value of 145 MPa corresponding to

Aluminum 3003.

Figure 2.3 Stress Vs. Strain curve for the aluminum crush tubes

2.2 Dynamic Axial Crushing of the Aluminum Tubes

Axial crushing of cylindrical tubes became a very popular choice of impact

energy absorber because of its energy absorption capacity. It provides a

reasonably constant operating force, has high energy absorption capacity and

stroke length per unit mass. Further a tube subjected to axial crushing can

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ensure that all of its material participates in the absorption of energy by plastic

work. [33, 35]. Classification of axial crushing of cylindrical tubes under quasi

static loading includes sequential concertina mode, sequential diamond

mode, Euler mode, concertina and diamond mode, simultaneous concertina

mode, simultaneous diamond mode, and tilting of tube axis mode. [155] The

D/t ratio of the cylindrical tubes used in the design determines the mode in

which the tubes will crush. Experimental observations of Alghamdi [48] showed

that thick cylinders (small D/t ratio, D/t<80-90) undergo a concertina

(axisymmetric) mode of deformation. Table 2.1 lists the dimensions and material

properties of the cylindrical aluminum tubes used in our design.

Inner diameter (Di) 26.437 mm Outer diameter (Do) 28.215 mm Mean diameter (D) 27.326 mm

Thickness (t) 0.889 mm Yield Strength (Y) 145 MPa

Length (L) 228.6 mm Density (ρ) 2.610E-09 ton/mm3

Young’s modulus of Elasticity 68948.000 N/mm2 Poisson’s ratio 0.33

Tangent modulus Refer Figure [1] LSDYNA Material model Piecewise Linear Plasticity Material model number 24

TABLE 2.1 Dimensions and material properties of the cylindrical aluminum tubes

used

Figure 2.3 displays the stress-strain plot of the aluminum material used for the

cylindrical tube, from which the Tangent modulus can be computed.

Substituting the mean diameter and thickness values, we obtain the D/t ratio as

30.7 which is much less than 80. Thus the tubes are classified as thick and will

deform in a concertina mode. It has been reported that the concertina mode

of deformation results in a higher specific energy absorption than the diamond

mode of deformation (high D/t ratios, non-axisymmetric) [48].

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According to Alexander [31], the mean crushing load of a cylindrical tube is

given by the following expression:

(2.1)

where

Pav = Mean crushing load

Y = Yield strength

t = Tube thickness

D = mean tube diameter

It provides a good prediction for D/t<30. This equation is the most famous in

axial crushing of tubes. Abramowicz and Jones [29] improved Alexander’s

analysis and proposed the following expression:

1 2(6( ) 3.44 )avP Yt Dt t= + (2.2)

As can be seen from Equations 2.1 and 2.2, there is a dependence of the

mean crushing load on the yield strength and geometric properties of the crush

tubes. This is important in the design of the aluminum crush tubes as the

dynamic crushing load must not exceed the critical value that can cause

crushing of the lumbar column. Table 2.2 displays a few parameters associated

with the axial crushing of the cylindrical aluminum tubes, such as static and

dynamic crushing load, number of folds possible during crushing, total plastic

energy absorbed during the formation of each fold, and effective crushing

distance, for the tubes we used whose properties are listed in Table 2.1. Four

different yield strengths were selected, whose values ranged from 100 MPa to

300 MPa. The formulae for these parameters are obtained from [29]. These

properties are useful in determining the overall energy attenuation capability of

the aluminum crush tubes and can also be used to predict the response

1 26 ( )avP Yt Dt=

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(acceleration pulse) of the EA seat during impact. The maximum compressive

lumbar load that can be sustained without injury is 6672 N. This must be kept in

careful consideration while selecting the tube material and geometric

properties.

100 MPa 145 MPa 220 MPa 300 MPa

Static crushing load (N) 3316.6 4809.1 7296.5 9949.8 Dynamic crushing load (N) 4151.1 6019.1 9132.5 12453 Number of folds possible 52 52 52 52

Total energy absorbed / fold (J) 24.54 35.58 53.98 73.61 Effective crushing distance (mm) 6.91 6.91 6.91 6.91

TABLE 2.2 Axial crushing parameters of the cylindrical aluminum tubes used

Figure 2.4 displays the static and dynamic axial crushing loads of cylindrical

aluminum tubes with a D/t ratio of 30.7 as a function of yield strength.

0

2000

4000

6000

8000

10000

12000

14000

0 50 100 150 200 250 300 350

Yield Strength (MPa)

Load

(N)

Static Crushing Load

Dynamic Crushing Load

Figure 2.4 Static and dynamic axial crushing load of cylindrical aluminum tubes

with a D/t ratio of 30.7

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2.2.1 Techniques to reduce the initial crushing load of a tube

It has been observed that while the crushing of the tubes occurs under a

reasonably constant operating force, there always exists an initial peak that

corresponds to the formation of the first plastic hinge. This peak usually is about

1.5 to 2 times larger than the average crushing load of the tube and will be

dangerous to the occupant’s survivability if not attenuated.

a) Introduction of annular grooves in the crush tube

Research conducted by Daneshi et al. [34] shows that the introduction of

annular grooves in the crush tube will force plastic deformation to occur at

regular intervals along the tube, thereby causing uniform energy absorption and

a uniform deceleration pulse thus resulting in a controllable energy absorption

element, without any spike in the load-deformation plot that is usually

associated with the initial crushing force required for plastic buckling. Thus far,

only quasi static axial crushing tests have been performed, but have yielded

promising results.

Figure 2.5 Annular grooves on a circular crush tube

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b) Weakening the finite element mesh of the crush tube

Simulations showed that by removing periodic shell elements along the

periphery of the crush tube, local buckling (and plastic deformation) can be

induced at a desired location, which will result in a lower initial deceleration

pulse. The energy absorption rate remains unaffected. By reducing the initial

deceleration pulse, we can make sure that at no point in the simulation, the

deceleration reaches the critical value causing injury. In Figure 2.6, red

elements correspond to the rail and blue elements correspond to the crush

tube.

Figure 2.6 Weakening the FE mesh of the crush tube

c) Heat treatment and wasting of the crush tube

Research conducted showed that by first subjecting the crush tube to an

Annealing cycle and then Wasting it by introducing a wrinkle around the tube’s

perimeter via a pipe cutting tool could reduce the crush initiation load and

deceleration pulse by as much as 50% as well as the initial peak in the load-

displacement curve. Figure 2.7 displays the heat treatment curve during the

annealing of the aluminum crush tube.

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Figure 2.7 Heat treatment curve used during the annealing process [9]

As can be observed from the Figure 2.8, there is a great difference in both the

Crush Initiation Load as well as the Mean Sustainable Crushing Load when the

tube is subjected to different combinations of Annealing and Wasting. The tube

that was annealed and then wasted was found to be most suitable for the

simulations and had the closest desired crush initiation load [9]. When a wrinkle is

created on the tube’s periphery, strain hardening occurs due to plastic

deformation. Annealing helps remove this and restores the softness back to the

material

Figure 2.8 Static performances of plain and wasted tubes [9]

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2.3 Additional energy absorbing elements

In addition to the aluminum crush tubes, additional energy absorbing elements

are added to the design to help further attenuate and delay the shock pulse as

well as to offer the occupant additional cushioning. These are discussed below.

2.3.1 Low density foam cushion

A low density foam cushion that covers the upper and lower sections of the seat

has been utilized to provide additional cushioning. The material model used in

LS-DYNA for the foam cushion is MAT_LOW_DENSITY_FOAM. It is used for

modeling highly compressible low density foams and its main applications are

for seat cushions and padding on the Side Impact Dummies (SID) [122]. This

foam model is not crushable, thus problems usually encountered in simulations

such as negative volume, invalid Jacobian and element inversion associated

with crushable foam has been avoided. Figure 2.9 displays the nominal stress

versus strain for the low density foam material used. The data was obtained from

the NHTSA Side Impact dummy model.

Figure 2.9 Nominal stress Vs. strain curve for the low density foam material

Low Density Foam

00.20.40.60.8

11.21.41.61.8

0 0.2 0.4 0.6 0.8 1

Strain

Nom

inal

Str

ess

NominalStress Vs.Strain

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While specifying contact between the foam cushion and the seat, the card

*CONTACT_TIED_NODES_TO_SURFACE_OFFSET is also used to attach (tie) the

nodes of the bottom surface of the solid foam cushion elements to the seat so

that there is no chance of slippage during the impact, similar to how the

cushion is stitched to the seat frame in reality. The keyword

*CONSTRAINED_EXTRA_NODES can also be used to attach the foam cushion to

the seat.

As can be seen from Figure 2.10, the dummy first settles against the cushion by

the action of gravity before the acceleration pulse is applied in the simulation.

This provides proper contact between the dummy’s lower torso and the foam

cushion. The foam cushion provides additional cushioning during both the mine

blast and vehicle slam down.

Figure 2.10 Gravity settling of the dummy against the foam cushion

In order to keep the rearward head impact with the seat to a minimum, a

contoured headrest is used as displayed in Figure 2.11, which minimizes the

distance the head is thrown backwards and correspondingly any injury this may

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cause. It has resulted in a reduction of the head G-forces of impact from 123

G’s without the foam cushion, to 45 G’s with the original foam cushion design, to

a final 25 G’s with the new contoured design, as can be seen from Figure 2.12.

Figure 2.11 Contoured foam cushion headrest to minimize head injury

-20

0

20

40

60

80

100

120

140

40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

No Foam Cushion

Orig Foam Cushion

Contoured FoamHeadrest

Figure 2.12 Effect of foam cushion on HYRBID III head acceleration

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2.3.2 Airbag cushion

In addition to the aluminum crush tubes, an inflatable airbag cushion is added

to the upper surface of the rigid seat. The inflation is controlled by a sensor that

triggers inflation at a user defined acceleration level. During the mine blast and

subsequent vertical displacement of the armored vehicle and occupant, the

aluminum tubes are partly consumed. Thus, there is limited cushioning during

vehicle slam down. The purpose of the airbag cushion is provide cushioning to

the occupant during the mine blast and additional cushioning to the

occupant’s torso once the vehicle impacts the ground during slam down. The

inflation of the airbag is controlled in LS-DYNA using a user defined load curve.

LS-DYNA offers 11 airbag models as follows:

1) SIMPLE PRESSURE VOLUME

2) SIMPLE AIRBAG MODEL

3) ADIABATIC GAS MODEL

4) WANG NEFSKE

5) WANG NEFSKE JETTING

6) WANG NEFSKE MULTIPLE JETTING

7) LOAD CURVE

8) LINEAR FLUID

9) HYBRID

10) HYBRID JETTING

11) HYBRID CHEMKIN

The simple airbag [122] model in LS-DYNA has been utilized in these simulations.

Figure 2.13 displays the GEBOD dummy seated on a partially inflated airbag

cushion. The constant inflation of the airbag ensures proper contact at all times

with the dummy’s lower torso.

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Figure 2.13 FE mesh of the EA seat with airbag cushion and GEBOD dummy

The user input for the simple airbag model is the Volume Vs. Time plot which

controls the airbag inflation. An initial filled volume can be specified at time t=0,

so that the airbag remains partially inflated and acts as a seat cushion during

normal operation. Whenever a mine blast occurs, the inbuilt LSDYA sensor is

triggered and the airbag rapidly inflates, thereby providing additional

cushioning. Figure 2.14 displays some of the properties of the airbag used such

as the rate of input airflow and rate of change of mass with time.

Airbag Volume

0

1

2

3

4

5

0 0.01 0.02 0.03 0.04 0.05 0.06

Time (s)

Vol

ume

(x 1

E+0

7)

Airbag Volume

(a)

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dM/dT IN

0

5

10

15

20

0 0.01 0.02 0.03 0.04 0.05 0.06

Time (s)

dM/d

T IN

(x 1

E+03

)

dM/dT IN

(b)

Figure 2.14 a) Rate of airbag input airflow b) Rate of change of airbag mass

with time

2.4 Shock pulses Applied to the Structure

Two types of input pulses have been used in the simulations to represent freefall

under gravity, and a mine blast under an armored vehicle. These pulses

prescribe structural accelerations that correspond to the actual physical

phenomenon. This is a more robust method compare to displacement or

velocity control. A load curve that specifies acceleration versus time is used in

LS-DYNA to prescribe the motion of the structure. There is a time delay before

the application of the input pulse to allow for gravity settling of the occupant

against the structure to ensure proper contact. The individual pulses are

explained in the following sections.

2.4.1 Impact after Free Fall

Based on data from [9], the vertical impact after free fall is simulated by

applying a deceleration pulse to the base of the structure. This is accomplished

in LS-DYNA by applying the load curve that prescribes acceleration versus time

to all nodes at the lowermost surface of the structure. The structure is also given

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an initial velocity in the downward direction corresponding to the vertical impact

velocity. The shock waves propagate from the base of the structure through the

brackets, onto the seat, and finally to the occupant. Figure 2.15 displays a

sample input deceleration pulse applied to the structure.

-20

0

20

40

60

80

100

0 20 40 60 80

Time (ms)

Acc

eler

atio

n (G

)

Vertical Drop TestPulse

Figure 2.15 Acceleration pulse used in vertical drop testing

2.4.2 Mine Blast

An acceleration pulse is used to simulate the effect of a mine blast under a

vehicle. Figure 2.16 displays the acceleration pulse that is applied to the

bottom surface of the structure in the upward direction. This throws the seat and

occupant upwards and after the reaching the peak vertical displacement, the

seat and occupant return to the ground via freefall. The center of mass of the

structure is constrained against any rotation to ensure the structure displaces

vertically along a straight line. The pulse gets transmitted from the structure to

the occupant through the energy absorbing mechanism. This pulse includes a

peak acceleration of 180 G for a 5 ms duration. This is followed by a 85 ms

duration of negative acceleration to put the final velocity at zero and final

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displacement at its maximum vertical position. After that the acceleration

stabilizes at -1 G (freefall) until displacement is zero [156].

-50

0

50

100

150

200

0 50 100 150

Time (ms)

Acc

eler

atio

n (G

) Mine Blast Pulse

Figure 2.16 Acceleration pulse representing a mine blast

2.5 Filtering of Data

All numerical data contains noise and needs to be filtered to remove the high

excitations of nodal data which leads to the numerous peaks normally seen in

unfiltered data. The raw data is first subjected to a fast Fourier transform of FFT to

determine the cut-off or filtering frequency. The data is then filtered using a low

pass Butterworth filter with this cut-off frequency. The choice of filter and

frequency is important as the use of too low a filtering frequency can lead to

severe under prediction of the results and vice versa. Figure 2.17 displays

sample unfiltered data and the corresponding filtered data using a BW filter at

180 Hz.

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47

(a)

(b)

Figure 2.17 a) Unfiltered data b) Filtered data

2.6 Validation of Initial EA Seat Simulations

Before simulations are created and run according to the test matrix, the initial

test results are first validated by comparison with experimental results. Numerical

results from the Energy Absorbing seat simulations have been compared with

experimental observations and data from [9]. The results from our simulations

are in very good agreement with the experimental data as can be seen from

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48

Figure 2.18. There is high variance and correspondingly low repeatability of the

experimental curves and therefore the correspondence of results seen from the

simulation and experiment in Figure 2.18 is considered as very good validation

of the data. It is important to note the scarcity of further available experimental

data for such vertical drop testing of energy absorbing seats with a dummy

occupant.

-60

-40

-20

0

20

40

0 10 20 30 40 50 60

Time (s)

Acc

eler

atio

n (G

)

Experiment

Simulation

(a)

-20

0

20

40

0 10 20 30 40 50 60Time (s)

Acc

eler

atio

n (G

)

Experiment

Simulation

(b)

Figure 2.18 Comparison of experimental and simulation results (a) seat pulse

(b) occupant pulse

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Chapter 3

Results and Discussion: Energy Absorbing

Seat

3.1 Test matrix

The test matrix is shown in Table 3.1. Due to the high volume of test results,

individual test data for all tests are not shown; rather comparison plots have

been presented in the subsequent sections.

Test GEBOD dummy

HYBRID III dummy

Plain Seat Foam Cushion

Airbag Cushion

Vertical Drop

Mine Blast

T1 x x x

T2 x x x

T3 x x x

T4 x x x

T5 x x x

T6 x x x

T7 x x x

T8 x x x

T9 x x x

T10 x x x

Table 3.1 Test matrix for EA seat design

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The simulations were run on the Ohio Supercomputer Center using a Beowulf

cluster consisting of Intel P4 chips running on a Linux based OS. When using a

numerical dummy in the simulations, serial processing was used and in all other

simulations, parallel processing utilizing 8 nodes was used. The data was

processed using LS-PREPOST© to extract the results.

3.2 Simulation Setup

The setup of the simulation in LSDYNA is shown below. Figure 3.1 displays an EA

seat with the additional energy absorbing element which may be a foam

cushion or airbag cushion, and a GEBOD dummy occupant. Figure 3.2 displays

the same seat with a 5th percentile HYBRID III dummy.

Figure 3.1 EA seat with a GEBOD dummy

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Figure 3.2 EA seat with a HYBRID III dummy

3.3 EA seat with GEBOD dummy subjected to vertical

drop testing

Comparison between EA Plain Seat / Foam / Airbag Cushion Seat w ith Gebod dummy subject to prescribed deceleration pulse during impact after freefall

-Head (x) Acceleration

-30

-20

-10

0

10

20

30

40

0 20 40 60 80 100 120

Time (ms)

Acce

lera

tion

(G)

Foam Cushion: Head (x) Acc

Plain Seat : Head (x) Acc

Airbag Cushion Seat: Head (x) Acc

period where gravity isused to settle the dummy

(a)

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Comparison between EA Plain Seat and Foam Cushion Seat w ith Gebod dummy subject to prescribed deceleration pulse during impact after freefall

-Neck (x) Acceleration

-10

0

10

20

30

40

50

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)Plain Seat: Neck (x) Acc

Foam Cushion:Neck (x) Accperiod where gravity isused to settle the dummy

(b)

Comparison between EA Plain Seat / Foam / Airbag Cushion Seat w ith Gebod dummy subject

to prescribed deceleration pulse during impact after freefall -Head (y) Acceleration

-10-505

10152025303540

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Plain Seat: Head (y) Acc

Foam Cushion:Head (y) Acc

Airbag Cushion Seat: Head (y) Acc

period where gravity isused to settle the dummy

(c)

Comparison between EA Plain Seat / Foam / Airbag Cushion Seat w ith Gebod dummy subject to

prescribed deceleration pulse during impact after freefall -M id Torso (y) Acceleration

-60-40-20

020406080

100

0 20 40 60 80 100 120Time (ms)

Acc

eler

atio

n (G

)

Plain Seat: Mid Torso (y) Acc

Foam Cushion: Mid Torso (y) Acc

Input Pulse

Airbag Cushion: Mid Torso (y) Acc

(d)

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Comparison between EA Plain Seat and Foam Cushion Seat with Gebod dummy subject to prescribed deceleration pulse during impact after freefall

-Force (x) between the Lower Torso and Seat

-10000

100020003000400050006000

0 20 40 60 80 100 120

Time (ms)

Forc

e (N

)

Plain Seat: Low er Torso - Seat : y force

Foam Cushion: Low er Torso - Seat : yforce

(e)

Comparison between EA Plain Seat / Foam / Airbag Cushion Seat w ith Gebod dummy subject to prescribed deceleration pulse during impact after freefall

-Lower Torso (y) Acceleration

-200

204060

80100

0 20 40 60 80 100 120Time (ms)

Acc

eler

atio

n (G

)

Plain Seat: Low er Torso (y) Acc

Input Pulse

Foam Cushion: Low er Torso (y) Acc

Airbag Cushion: Low er Torso (y) Acc

(f)

Comparison between EA Plain Seat and Foam Cushion Seat with Gebod dummy subject to prescribed deceleration pulse during impact after freefall

-Force (x) between the Upper Torso and Seat

-10000

0

10000

20000

30000

40000

0 20 40 60 80 100 120

Time (ms)

Forc

e (N

)

Plain Seat: Upper Torso - Seat : x force

Foam Cushion: Upper Torso - Seat : xforce

(g)

Figure 3.3 Results of EA Seat with GEBOD dummy subject to vertical drop testing

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3.4 EA seat with HYBRID III dummy subjected to vertical

drop testing

Comparison between EA Plain Seat and Foam Cushion Seat with Hybrid III dummy subject to prescribed deceleration pulse during impact after freefall

-Head (x) Acceleration

-200

20406080

100120140

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

) Plain Seat: Head X Acc

Foam Cushion: Head (x) Acc

period where gravity isused to settle the dummy

(a)

Comparison between EA Plain Seat and Foam Cushion Seat with Hybrid III dummy subject to prescribed deceleration pulse during impact after freefall

-Neck (x) Acceleration

-200

20406080

100120140

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Plain Seat: Neck (x) Acc

Foam Cushion: Neck (x) Acc

period where gravity isused to settle the dummy

(b)

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Comparison between EA Plain Seat and Foam Cushion Seat with Hybrid III dummy subject to prescribed deceleration pulse during impact after freefall

-Neck Moment

-51000

-41000

-31000

-21000

-11000

-1000

9000

0 20 40 60 80 100 120

Time (ms)

Nec

k M

omen

t (N

-mm

)

Plain Seat: Neck Moment

Foam Cushion: Upper NeckMoment

Foam Cushion: Lower NeckMomentperiod where gravity is

used to settle the dummy

(c)

Comparison between EA Plain Seat and Foam Cushion Seat with Hybrid III dummy subject to prescribed deceleration pulse during impact after freefall

-Rigid Seat Acceleration (y) Pulse

-60

-40

-20

0

20

40

60

80

100

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Foam Cushion: Rigid Seat (y) AccInput Deceleration PulsePlain Seat: Rigid Seat (y) Acc

(d)

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56

Comparison between EA Plain Seat and Foam Cushion Seat with Hybrid III dummy subject to prescribed deceleration pulse during impact after freefall

-Lower Torso (y) Acceleration

-20-10

0102030405060708090

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Foam Cushion: Lower Torso (y) AccInput Deceleration PulsePlain Seat: Lower Torso (y) Acc

(e)

Figure 3.4 Results of EA Seat with HYBRID III dummy subject to vertical drop

testing

3.5 EA seat with GEBOD dummy subjected to mine blast

testing

Comparison between EA Airbag Cushion Seat and Foam Cushion Seatwith GEBOD dummy subject to prescribed Mine Blast

-Head Acceleration

-8-4048

12162024

0 20 40 60 80 100 120 140

Time (ms)

Acc

eler

atio

n (G

)

Head (x) Acc - Foam

Head (y) Acc - Foam

Head (x) Acc - Airbag

Head (y) Acc - Airbag

(a)

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Comparison between EA Airbag Cushion Seat and Foam Cushion Seatwith GEBOD dummy subject to prescribed Mine Blast

-Input and Lower Torso Pulses

-50

0

50

100

150

200

0 20 40 60 80 100Time (ms)

Acc

eler

atio

n (G

)

Low er Torso (y) Acc - Foam

Rigid Seat (y) Acc

Input Pulse

Low er Torso (y) Acc - Airbag

(b)

Comparison between EA Airbag Cushion Seat and Foam Cushion Seatw ith GEBOD dummy subject to prescribed Mine Blast

-Input and Middle Torso Pulses

-50

0

50

100

150

200

0 20 40 60 80 100Time (ms)

Acc

eler

atio

n (G

)

Mid Torso (y) Acc - Foam

Rigid Seat (y) Acc

Input Pulse

Mid Torso (y) Acc - Airbag

(c)

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Comparison between EA Airbag Cushion Seat and Foam Cushion Seatwith GEBOD dummy subject to prescribed Mine Blast

-Upper Torso and Seat (x) Force

-20000

2000400060008000

1000012000

0 20 40 60 80 100 120 140

Time (ms)

Forc

e (N

)

Foam Cushion SeatAirbag Cushion Seat

(d)

Comparison between EA Airbag Cushion Seat and Foam Cushion Seatwith GEBOD dummy subject to prescribed Mine Blast

-Lower Torso and Seat (y) Force

-4000-2000

02000400060008000

10000

0 20 40 60 80 100 120 140

Time (ms)

Forc

e (N

)

Foam Cushion Seat

Airbag Cushion Seat

(e)

Figure 3.5 Results of EA Seat with GEBOD dummy subject to mine blast testing

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59

3.6 EA seat with HYBRID III dummy subjected to mine blast

testing

Comparison between EA Plain Seat and Foam Cushion Seatwith Hybrid III dummy subject to prescribed Mine Blast

-Head Acceleration

-20

0

20

40

60

80

100

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

) Plain Seat: Head (x) Acc

Foam Cushion: Head (x) Acc

period where gravity isused to settle the dummy

(a)

Comparison between EA Plain Seat and Foam Cushion Seatwith Hybrid III dummy subject to prescribed Mine Blast

-Input and Lower Torso Pulses

-50

0

50

100

150

200

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

) Plain Seat: Low er Torso (y)AccInput Deceleration Pulse

Foam Cushion: Low er Torso(y) Acc

(b)

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Comparison between EA Plain Seat and Foam Cushion Seatwith Hybrid III dummy subject to prescribed Mine Blast

-Input and Middle Torso Pulses

-50

0

50

100

150

200

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

) Plain Seat: Mid Torso (y) Acc

Input Deceleration Pulse

Foam Cushion: Mid Torso (y)Acc

(c)

Figure 3.6 Results of EA Seat with HYBRID III dummy subject to mine blast testing

3.7 Improved Modeling of the EA seat structure

So far the energy absorbing seat structure used was modeled based on

dimensions from [9]. However, after making a few simple modifications to the

structure, better results were obtained. The run time of the simulation can be

drastically reduced by making all elements excepting the crush tube elements

as rigid, so that they are bypassed during element processing. Then they can

be switched back to deformable to study the bending of the rails and overall

structural deformability and strength. 4-noded shell elements (quad) are

computationally less expensive than 8-noded solid elements (brick) and are the

preferred choice wherever possible. When using shell elements, it is important to

take the thickness of the shell into consideration while modeling the mid-

surface. Figure 3.7 displays an improved modeling of the EA seat structure.

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61

Figure 3.7 Improved modeling of the EA seat structure

3.8 Effect of Aluminum Yield Strength on the Simulations

According to Alexander, the mean axial crushing load of aluminum tubes is

given by

Pav = 6Yt(Dt)1/2 (3.1)

This implies that Pav is directly proportional to the yield strength Y. However this

applies to the static crushing of tubes. In these simulations, there is an 80 G

impulse load applied to the crush tube in a 10-20 ms period. The variation of

Rigid Seat deceleration pulse is around only 1-2 G for yield stresses ranging from

124 MPa to 230 MPa. This clearly demonstrates the dynamic effect of high

impulse axial loading of aluminum tubes, which results in approximately similar

energy absorption and deceleration pulse for the studied range of yield stresses.

The limit of the study was 230 MPa as once the yield stress reaches that of the

steel rail which is 440 MPa, the rail begins to bend excessively before the

crushing of the aluminum tubes. Similarly 124 MPa was chosen as the starting

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62

yield stress as this corresponds to a soft version of Al 3003 grade. As the strain

rate decreases, the difference in response of aluminum of varying yield stresses

becomes more prominent. This means for a 20-30 G impulse load, the

difference in the deceleration pulse will be around 5-10 G.

Effect of Aluminum yield strength on the Rigid SeatDeceleration Pulse

-2

0

2

4

6

8

10

0 0.01 0.02 0.03 0.04 0.05

Time (seconds)

Acc

eler

atio

n (G

)

Al 124 MPaAl 200 MPaAl 230 MPaAl 145 MPa

Figure 3.8 Effect of Aluminum yield strength on the simulations

3.9 Stages of Crushing of the Aluminum Crush Tube

Snapshots of the crushing of the aluminum tube during the simulation are shown

below. It has been reported that based on the strain rate, the onset of crushing

will occur at different locations. For low strain rates (0.01 to 1 s-1), the crushing

usually initiates at the point of impact of the impactor and the crush tube. For

very high strain rates (10 to 40 s-1), the crushing usually initiates at the end of the

tube which is rigidly supported. The presence of imperfections in the tube will

also greatly influence the location of initiation of the crushing and the mode in

which the crushing will occur, i.e. sequential concertina or diamond mode. Shell

elements prove to be much more computationally efficient than solid elements

when modeling the crush tube. However to get a proper shape of the fold

formation, a very fine mesh of the order of 1 mm needs to be used, which is not

feasible. Thus a coarser mesh is used, which will result in a non-axisymmetric

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63

mode of crushing, or a crumpling effect, as seen in Figures 3.9 and 3.10.

However the amount of energy absorbed and the shell response was observed

to be identical to the case when solid elements were used to model the crush

tube. The shape of the crushed tube when using solid elements with the same

material model can be seen in Figure 3.11.

3.9.1 Stages of crushing for the original EA seat model

(a) (b)

(c)

Figure 3.9 a) Plastic buckling first occurs at the bottom bracket b) Onset of

plastic buckling at the top bracket c) Completely crushed aluminum crush tube

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3.9.2 Stages of crushing for the improved EA seat model

(a) (b)

(c)

Figure 3.10 a) Plastic buckling first occurs at the top bracket b) Onset of plastic

buckling at the bottom bracket c) Completely crushed aluminum crush tube

3.9.3 Shape of the Crushed Tube when Modeled with Solid

Elements

Figure 3.11 displays a snapshot of the shape of the crushed tube when

modeled with solid elements. The time step fell below 1.00E-08 leading to

automatic deletion of the solid elements by the material model, to prevent the

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65

simulation from running indefinitely. This is a disadvantage of using

computationally expensive elements and a very fine mesh in order to get the

most accurate representation of the physical phenomenon.

Figure 3.11 Shape of the crushed tube modeled with solid elements

3.10 Final EA Seat Design for use in full scale Vertical Drop

Testing and Mine Blast Testing

Figure 3.12 displays the final model of EA seat structure. The headrest has been

given a contoured shape to better support the head. Closer tolerances have

been used in all dimensions along with a finer mesh for the crush tubes. In

previous models, results from only the head, lumbar and torso regions were

concentrated on. Now the base of the structure has been extended till

underneath the dummy’s feet in order to extract the foot acceleration and

impact force along with the rest of the other simulation data. Finally, all the

important points of impact between the dummy and the vehicle have been

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66

covered and can now be analyzed for occupant survivability. Since the data

that can be extracted from the HYBRID III dummy is more extensive and reliable

than the GEBOD dummy, it is the preferred dummy of choice. A 5th percentile

dummy has been used.

Figure 3.12 Final model of the EA seat structure

3.10.1 Vertical Drop Testing

-40

-20

0

20

40

60

80

100

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Low er Torso

Seat

Structure

Figure 3.13 Deceleration pulses

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-2000

0

2000

4000

6000

8000

10000

12000

14000

16000

0 20 40 60 80 100 120

Time (ms)

Forc

e (N

)

Tube Crushing

Dummy-Seat Contact

Figure 3.14 Dynamic axial crushing force of the tube, and Dummy-seat contact

force

-5000

0

5000

10000

15000

20000

25000

0 20 40 60 80 100 120

Time (ms)

Forc

e (N

)

Foot-Floor Contact

Figure 3.15 Contact force between the foot and floor

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68

3.10.2 Mine Blast Testing

-50

0

50

100

150

200

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Low er Torso

Seat

Structure

Figure 3.16 Acceleration pulses

-2000

0

2000

4000

6000

8000

10000

12000

14000

16000

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Tube Crushing

Dummy-SeatContact

Figure 3.17 Dynamic axial crushing force of the tube, and Dummy-seat contact

force

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69

-2000

0

2000

4000

6000

8000

10000

12000

14000

0 20 40 60 80 100 120

Time (ms)

Acc

eler

atio

n (G

)

Foot-Floor Contact

Figure 3.18 Contact force between the foot and floor

3.11 New EA Mechanism

A conventional energy absorbing axially crushable aluminum tube and steel

rail is used to provide occupant protection against vertical acceleration

pulses. However during a mine blast, there are significant lateral forces and

accelerations as the occupant and vehicle are thrown sideways and

backwards. It is not feasible to design a horizontal steel rail-aluminum crush

tube to protect against this. Further all 360° in the horizontal plane needs to

be protected as depending on the location of the mine blast under the

vehicle, the occupant may be accelerated in any direction. This means that

cylindrical crush tubes will have to be placed in a circular pattern in as many

directions as possible, which is not feasible. Instead, a circular annular disk

having a honeycomb structure can be utilized to protect against sideward

and lateral accelerations. LSDYNA offers a Honeycomb Material Model. A

rigid thin steel cylinder placed in the annulus will move laterally according to

the vehicle’s motion as it is thrown up and sideways in a mine blast. As the

steel cylinder moves laterally, it begins to crush the aluminum honeycomb

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70

which contacts it throughout the circumference. Another rigid steel cylinder

on the outer periphery provides the surface against which the honeycomb is

compressed against. Figure 3.19 displays the new honeycomb EA

mechanism.

Figure 3.19 New honeycomb EA mechanism

By using many layers of this honeycomb structure, a high degree of

acceleration pulse attenuation can be accomplished in the lateral direction,

reducing injury criteria such as HIC, NIC and forces between the torso and

seat. Rigid circular steel covers are placed above and below the

honeycomb structure and thin steel cylinder in order to contain the entire

mechanism and ensure there is only movement in the lateral direction.

Figure 3.20 displays the interior view of the honeycomb EA design.

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Figure 3.20 Interior view of the EA mechanism

3.12 Conclusions

1. The crushing of aluminum tubes has proven to be a very effective energy

absorption technique and can attenuate input deceleration pulses to

survivable levels.

2. The initial static crushing strength of the aluminum material used

influences the peak deceleration pulse felt at the rigid seat and brackets for

low strain rates. However for higher strain rates, the dynamic effect comes

into play and there is little difference in the response of the aluminum crush

tube.

3. The ideal energy absorber for the energy absorbing seat mechanism

would be a very long aluminum crush tube with a low yield stress, however

size constraints are imposed upon the design because of the limited length

available for crushing below the seat pan.

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72

4. A foam cushion modeled with either low density foam or crushable foam

helps in increasing occupant survivability by:

a) Delaying the onset of the applied deceleration pulse to the

occupant

b) Attenuating the peak magnitude of the transmitted deceleration

pulse from the seat

c) Extending the time duration of application of the pulse to the

occupant, thereby spreading the shock over a longer duration

5. The responses of the GEBOD and HYBRID III dummy to the same boundary

and loading conditions is different.

6. The H3OUT database corresponding to the HYBRID III dummy contains

data of the various joint moments and forces, and serves as an essential

source of data for comparison with known injury data references to assess

injury.

7. The GEBOD dummy is mainly used for visualization purposes. Only the

accelerations and contact forces of various dummy segments can be

extracted, thus providing for a very limited source of data for comparison

with known injury data references to assess injury.

8. The design that incorporates the aluminum crush tubes and foam cushion

is a robust, efficient and cost-effective design for an energy absorbing seat

mechanism.

9. The usage of prescribed acceleration pulses to simulate vertical drop tests

and mine blasts is an accurate representation of reality.

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73

10. It is not possible to assess the extent of occupant injury, merely the

probability of occurrence of an injury. Further work is required in the field of

Injury Criteria.

11. By improving the modeling of the seat structure, viz. better tolerances

and longer crush tubes, the energy absorption can be maximized while the

peak deceleration pulse at the rigid seat can be minimized.

12. Current versions of LSTC Hybrid III dummy do not allow for extraction of

lumbar load data and so we have to wait for future versions from LSTC to

obtain such data.

13. The use of the HYBRID III dummy to model a human occupant during

vertical drop testing and mine blast testing has been properly validated.

3.13 Scope for Further Work

Airbags and occupant restraint systems can be included into the design.

More advanced numerical dummies such as the BioRID and Thor-Lx with

better detailed structures can be used in place of the HYBRID III dummy. The

EA seat mechanism can be incorporated into the mesh of the actual

armored vehicle provided it can be made available from the U.S. Army.

LSDYNA supports ALE formulations, and instead of using prescribed structural

acceleration pulses to simulate mine blasts, actual mine explosions can be

simulated using keywords such as *LOAD_BRODE and *LOAD_BLAST which

creates pressure waves around the structure similar to an actual IED blast, by

specifying parameters such as amount of TNT used and distance of

explosive device from the structure. Other EA mechanisms such as the

Honeycomb structure mentioned in preceding sections can be further

explored.

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Chapter 4

Impact of Foot during IED/Mine Blast

4.1 Numerical Setup and Methodology

The experimental set up used in [12] formed the basis for the numerical

simulation and is displayed in Figure 4.1. A rigid seat comprised of thin shell

elements is modeled and rigidly fixed in 3-d space. The occupant is simulated

by a 50th percentile HYBRID III dummy which is internally created by LS-DYNA

[122] during the initialization of the simulation run. The dummy is seated on this

rigid seat.

Figure 4.1 Experimental setup of lower leg impact

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The position and orientation of the arms is not important and is therefore left at

its default values as seen in Figures 4.2 and 4.3, as it plays no role during the

simulation. Similarly an occupant restraint mechanism such as a seatbelt has

not been modeled as there is no significant middle or upper torso movement

during the simulation. The main region of activity lies between the foot and hip

of the dummy.

Figure 4.2 Numerical setup in ‘Sitting Straight’ position

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Figure 4.3 Numerical setup in ‘Driving’ position

A rigid horizontal wall modeled with thin shell elements simulates the impacting

vehicle floor. The motion of the wall is controlled by prescribing its velocity.

Contact is specified between the dummy-seat and dummy-wall interfaces.

Before the wall starts moving upwards and imparts a high acceleration pulse to

the dummy’s foot; gravity is applied to the dummy so that it properly settles into

the seat and the foot properly contacts the wall. While modeling the wall, care is

taken to position the wall as close as possible to the feet, as even the smallest

gap between the wall and feet can significantly alter extracted data such as

femur axial compressive force. Since it is not possible during modeling to ensure

exact contact, gravity is applied which ensures the foot initially settles against

the wall. As the feet are thrown upwards during the application of the input

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prescribed velocity pulse to the wall, data such as foot acceleration, lower leg

acceleration, hip moment, knee moment and femur axial compressive force

are measured. This data is later extracted and filtered using LSPREPOST© and

graphical plots for visualization are created. Filtering of data is done with a low

range Butterworth filter, with a cut-off frequency at 300 Hz. The data is then

compared to reference values to assess injury. A series of six simulations are run

for each case of occupant seated position viz. sitting straight and driving

position. For the driving position, the knee flexion-extension angle is changed

from its default value of 90 degrees to 55 degrees as seen in Figure 4.3. The

peak wall impact speed is increased in a step wise manner as follows: 1 ft/s, 5

ft/s, 10 ft/s, 15 ft/s, 25 ft/s, 35 ft/s. The velocity control curve that prescribes the

wall motion is shown in Figure 4.4 below.

0

2

4

6

8

10

12

0 20 40 60 80

Time (ms)

Wal

l Spe

ed (m

/s)

1 ft/s

5 ft/s

10 ft/s

15 ft/s

25 ft/s

35 ft/s

gravitysettling

Figure 4.4 Prescribed velocity of the wall

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4.2 Numerical Results and Discussion

First the data from the simulations is validated against experimental data from

[12]. It is important to note the scarcity of available data due to limited research

conducted, especially on human cadavers, and the classified nature of such

work. Data such as foot acceleration and femur axial compressive force have

injury criteria [7, 13, 14, 15, 27] associated with them and are therefore used for

validation. However data such as knee, hip and ankle moments do not have

associated injury criteria yet and further research needs to be conducted into

this. This data has still been presented in our study as it is important and can

serve as a reference in the future. As can be seen from Figures 4.5 to 4.8, our

data from numerical simulations is in very good agreement with the

experimental data.

-8000

-7000

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

0 5 10 15 20Time (ms)

Forc

e (N

)

experiment

simulation

Figure 4.5: Validation of femur axial compressive force with test db2a

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-40

-20

0

20

40

60

80

100

120

140

160

0 5 10 15 20 25Time (ms)

Acc

eler

atio

n (G

) experiment

simulation

Figure 4.6: Validation of foot acceleration with test db2a

-12000

-10000

-8000

-6000

-4000

-2000

0

2000

0 5 10 15 20Time (ms)

Forc

e (N

)

experiment

simulation

Figure 4.7: Validation of femur axial compressive force with test db3a

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-100

-50

0

50

100

150

200

250

0 5 10 15 20 25Time (ms)

Acc

eler

atio

n (G

) experiment

simulation

Figure 4.8: Validation of foot acceleration with test db3a

4.2.1 Hybrid III dummy in a sitting straight position

Figures 4.9 to 4.14 display the data extracted from the HYBRID III dummy in the

sitting straight position, subject to foot impact at six varying peak impact

speeds. All data are seen to display a trend that can be accurately interpolated

or extrapolated to predict results, eliminating the need of running further

simulations. There is no noticeable activity at the upper torso and the main

region of interest is between the foot and hip. The ankle moment has not been

extracted as the foot maintains its inclination of 90 degrees with the lower leg

throughout the simulation. The femur axial compressive load exceeds the safety

limit of 10,000 N between the 25 and 35 ft/s peak wall impact speeds. The

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exact critical speed can be easily interpolated and is found to be

approximately 27.5 ft/s for the given nature of prescribed input acceleration

pulse. The hip flexion-extension moments for the cases of 25 ft/s and 35 ft/s wall

impact speeds are displayed separately in Figure 4.11, as their magnitudes are

greater than the hip moments for the cases of 1 ft/s – 15 ft/s by an order of

about 100. Correspondingly, the knee flexion-extension moment values for

these higher range impact speeds, of 25 ft/s and 35 ft/s have been truncated

such that the data lines fit within the limits of the plot. The exact significance of

these high moments at the knee and hip is not fully understood at this time as

there is no associated injury for this data. They have been presented as a future

reference.

Hybrid III - Sitting PositionFoot (z) Acceleration

-500

50100150200250300

0 10 20 30 40 50 60 70

Time (ms)

Foot

Acc

eler

atio

n (G

)

1 ft/s Wall Speed5 ft/s Wall Speed10 ft/s Wall Speed15 ft/s Wall Speed25 ft/s Wall Speed35 ft/s Wall Speed

Figure 4.9 Foot (z) acceleration

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Hip (y) Flexion-Extension MomentHybrid III - Sitting Position

-500000-400000-300000-200000-100000

0100000

0 10 20 30 40 50 60 70

Time (ms)

Hip

Mom

ent N

-mm

1 ft/s Wall Speed5 ft/s Wall Speed10 ft/s Wall Speed15 ft/s Wall Speed

Figure 4.10: Hip flexion-extension moment for wall speeds 1 ft/s - 15 ft/s

Hip (y) Flexion-Extension MomentHybrid III - Sitting Position

-50000000

-40000000

-30000000

-20000000

-10000000

0

10000000

0 10 20 30 40 50 60 70

Time (ms)

Hip

Mom

ent N

-mm

25 ft/s Wall Speed35 ft/s Wall Speed

Figure 4.11: Hip flexion-extension moment for wall speeds 25 ft/s - 35 ft/s

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Hybrid III - Sitting PositionLower Leg (z) Acceleration

-500

50100150200250

0 10 20 30 40 50 60 70

Time (ms)

Low

er L

eg

Acc

eler

atio

n (G

)

1 ft/s Wall Speed5 ft/s Wall Speed10 ft/s Wall Speed15 ft/s Wall Speed25 ft/s Wall Speed35 ft/s Wall Speed

Figure 4.12: Lower leg (z) acceleration

Hybrid III - Sitting PositionFemur Axial Compressive Force

-15000-12000-9000-6000-3000

03000

0 10 20 30 40 50 60 70

Time (ms)

Fem

ur A

xial

C

ompr

essi

ve F

orce

(N)

1ft/s Wall Speed5ft/s Wall Speed10ft/s Wall Speed15ft/s Wall Speed25ft/s Wall Speed35ft/s Wall Speed

Figure 4.13: Femur axial compressive force

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Knee (y) Flexion-Extension MomentHybrid III - Sitting Position

-500-400-300-200-100

0100

0 10 20 30 40 50 60 70

Time (ms)

Knee

Mom

ent N

-mm

(x

1E-

06) 1 ft/s Wall Speed

5 ft/s Wall Speed10 ft/s Wall Speed15 ft/s Wall Speed

Figure 4.14: Knee flexion-extension moment

4.2.2 Hybrid III dummy in a driving position

Figures 4.15 to 4.21 display the data extracted from the HYBRID III dummy in the

driving position, subject to foot impact at six varying peak impact speeds. All

data are seen to display a trend that can be accurately interpolated or

extrapolated to predict results, eliminating the need of running further

simulations. There is no noticeable activity at the upper torso and the main

region of interest is between the foot and hip. Even at a 35 ft/s peak impact wall

speed, the femur axial compressive force stays below the safety limit of 10,000

N, implying no injury to the foot. Since the axis of the femoral bone is inclined to

the direction of motion of the impacting wall, the force transmitted to the lower

leg is limited to the vertical component of the total force. This explains the

significantly lower compressive axial femur force as compared to the sitting

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straight position. The critical impact speed can be easily obtained through

extrapolation. Initially, the heel of the foot is the only contact point between the

dummy and the wall. As the wall moves upwards, the foot rapidly changes its

initial inclination angle of 90 degrees with the lower leg, as the ankle joint

rotates. Significant ankle moments can be observed for the higher wall impact

speeds compare to the negligible values for speeds below 15 ft/s. Thus the

ankle moments for the cases of 15 ft/s – 35 ft/s are displayed separately in

Figure 4.21. The ankle moments for the peak impact speeds of 1 ft/s – 10 ft/s do

not display any trend, however their magnitudes are of the order of 1.00E-11

and can therefore be treated as negligible. It is not known at what peak dorsi-

plantar flexion moment the ankle joint will fail, and whether this failure can be

numerically simulated by the HYBRID III dummy.

Hybrid III - Driving PositionFoot (z) Acceleration

-50

0

50

100

150

200

0 10 20 30 40 50 60 70

Time (ms)

Foot

Acc

eler

atio

n (G

)

Wall Speed 1ft/sWall Speed 5ft/sWal Speed 10ft/sWall Speed 15ft/sWall Speed 25ft/sWall Speed 35ft/s

Figure 4.15 Foot (z) acceleration

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Hybrid III - Driving PositionHip (y) Flexion-Extension Moment

-80000

-60000

-40000

-20000

0

20000

0 10 20 30 40 50 60 70

Time (ms)

Hip

Mom

ent N

-mm

Wall Speed 1ft/sWall Speed 5ft/sWall Speed 10ft/sWall Speed 15ft/s

Figure 4.16: Hip flexion-extension moment

Hybrid III - Driving PositionLower Leg (z) Acceleration

-50

0

50

100

150

200

0 10 20 30 40 50 60 70

Time (ms)

Low

er L

eg

Acce

lera

tion

(G)

Wall Speed 1ft/sWall Speed 5ft/sWall Speed 10ft/sWall Speed 15ft/sWall Speed 25ft/sWall Speed 35ft/s

Figure 4.17: Lower leg (z) acceleration

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Hybrid III - Driving PositionFemur Axial Compressive Force

-10000-8000-6000-4000-2000

02000

0 10 20 30 40 50 60 70

Time (ms)

Fem

ur F

orce

(N)

Wall Speed 1ft/sWall Speed 5ft/sWall Speed 10ft/sWall Speed 15ft/sWall Speed 25ft/sWall Speed 35ft/s

Figure 4.18: Femur axial compressive force

Hybrid III - Driving PositionKnee (y) Flexion-Extension Moment

-505

10152025

0 10 20 30 40 50 60 70

Time (ms)

Knee

Mom

ent N

-mm

(x 1

E-0

6)

Wall Speed 1ft/sWall Speed 5ft/sWall Speed 10ft/sWall Speed 15ft/s

Figure 4.19: Knee flexion-extension moment

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Hybrid III - Driving PositionAnkle (y) Dorsi-Plantar Flexion

-4E-11-2E-11

02E-114E-116E-118E-11

0 10 20 30 40 50 60 70

Time (ms)

Ank

le M

omen

t N-m

m

Wall Speed 1ft/sWall Speed 5ft/sWall Speed 10ft/s

Figure 4.20: Ankle dorsi-plantar flexion moment for wall speeds 1 ft/s - 10 ft/s

Hybrid III - Driving PositionAnkle (y) Dorsi-Plantar Flexion

-10000000

-8000000

-6000000

-4000000

-2000000

0

2000000

0 10 20 30 40 50 60 70

Time (ms)

Ank

le M

omen

t N-m

m

25 ft/s Wall Speed35 ft/s Wall Speed

Figure 4.21 Ankle dorsi-plantar flexion moment for wall speeds 15 ft/s - 35 ft/s

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4.3 Parametric Study

The data analyzed from the simulations showed a trend and therefore a simple

parametric study was undertaken to determine if it is possible to predict the

lower leg and foot response without having to run a numerical simulation or

conduct a destructive test. In a simple case study, there is one independent

variable viz. wall speed (as dictated by the input pulse) and three dependant

variables in the simulations involving dummy foot impact by a rigid moving wall,

as seen in Figure 4.22. They are:

1) Knee angle (θ1)

2) Ankle angle(θ2)

3) Dummy Size (5th, 50th or 95th percentile)

There are other variables which can also be considered such as hip angle,

dummy gender and type, et cetera; however this will lead to a very complex

study, beyond the scope of the current undertaking.

Figure 4.22 Variables used in the parametric study

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The data extracted for assessment of injury comprises:

1) Axial Compressive Femur Force

2) Foot Acceleration

3) Lower Leg Acceleration

By running simulations while systematically varying the dependant variables, it is

possible to parametrically study the effect each variable has on the extracted

data. By using non-linear regression techniques and curve fitting, equations of

best fit can be derived that handle from one to all of the dependant variables

at a time. Further, it is possible to code the entire system of equations into a

software package, such that a user can input the required variables and extract

peak values of injury criteria, after which a comparison can be made to

allowable values to assess injury. This will further reduce the reliance on running

numerous numerical simulations, which can also prove costly. It will also provide

a useful ready reference during the design of occupant survivability

enhancement mechanisms to handle the explosion of AT mines.

Sample plots from the one variable parametric study of the data extracted from

the HYBRID III dummy are presented below. Figure 4.23 displays the variation of

peak foot acceleration with peak wall speed for a 50th percentile HYRBID III

dummy in the driving position. The equation of best fit used in a fifth order

polynomial (seen in the figure in red font) and corresponds to a perfect

coefficient of correlation (R2=1).

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Variation of Foot Acceleration with Wall Speed for HYBRID III in the Driving Position

y = 3E-05x5 - 0.002x4 + 0.0492x3 - 0.445x2 + 5.654x - 0.2515R2 = 1

0

40

80

120

160

0 5 10 15 20 25 30 35 40

Peak Wall Speed (ft/s)

Peak

Foo

t Acc

eler

atio

n (G

)

curve of best fit

Figure 4.23 Variation of peak foot acceleration with peak wall speed for a

dummy in a driving position

Figure 4.24 displays the variation of peak femur force with wall speed for a

50th percentile HYRBID III dummy in the driving position. A fifth order

polynomial was used to curve fit the data. We observe the peak femur axial

compressive force does not exceed the safety limit of 10,000 N at the

maximum peak wall speed of 35 ft/s used in our study. However, we can

extrapolate the data using the best fit curve equation to determine at what

peak wall speed, the peak compressive load will reach 10,000 N. This is an

advantage of the parametric study. Further numerical simulations do not

need to be run to determine the above unknown value.

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Variation of Femur Force with Wall Speed for HYBRID III in the Driving Position

y = -0.0002x5 + 0.015x4 - 0.4452x3 + 6.7427x2 - 307.46x - 13.749R2 = 1

-10000

-8000

-6000

-4000

-2000

0

0 5 10 15 20 25 30 35 40

Peak Wall Speed (ft/s)

Pea

k Fe

mur

Axi

al C

ompr

essi

ve

Forc

e (N

) curve of best fit

Figure 4.24 Variation of peak femur force with peak wall speed for a dummy in

a driving position

Figure 4.25 displays the variation of peak femur force with wall speed and knee

angle for the 50th percentile HYBRID III dummy in various seated positions.

Variation of Peak Femur Force with Wall Speed and Knee Anglefor the HYBRID III

-14000-12000-10000

-8000-6000-4000-2000

0

0 10 20 30 40Peak Wall Speed (ft/s)

Peak

Fem

ur F

orce

(N)

Knee Angle = 0 (Sitting)

Knee Angle = 55 (Driving)

Knee Angle = 27.5 (Extrapolated)

Extrapolated data

Figure 4.25 Variation of peak femur force with wall speed and knee angle for

various dummy positions

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Here, both wall speed and knee angle are varied systematically, and the

resultant effect on the femur force is studied. While 4th and 5th order

polynomials are used to curve fit the Femur Force Vs. Wall Speed data, a

simple average is used to interpolate the effect of varying the Knee Angle

(seated dummy position). Though we did not run further simulations at this point,

by running more simulations with varying knee angles, a better fit parametric

equation for the knee angle can be derived. Similarly, the effect of the Ankle

Angle can also be included in the parametric study (three variable study) to

provide a comprehensive analysis of the data.

4.4 Conclusions

By comparing the dummy data extracted from the simulations with the known

allowable values, injury can be accurately assessed. The femur axial

compressive force is far higher in the case of sitting straight position than the

driving position as the entire compressive load is directly transmitted to the

femoral bone, since the direction of the compressive load coincides with axis of

the femoral bone. The ankle moments are significantly higher for the upper

range of wall impact speeds in the driving position, compare to the sitting

straight position where the complete lower surface of the foot maintains its flat

contact with the wall throughout the simulation leading to negligible ankle

moments. Thus occupant position plays an important role in the magnitude of

loads transmitted and injury severity. The use of the HYBRID III dummy for

occupant simulation during mine blast testing has been satisfactorily validated,

after comparison of foot acceleration and femur axial compressive load, with

experimental data. Further data extracted such as hip, knee and ankle

moments can therefore be used now for accurate injury assessment. It has

been reported in automobile crash testing that the HYBRID III legs are too stiff

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which may lead to an underestimation of injury. The accuracy of results can be

optimized by using more advanced dummies that better model the human

body such as the Thor-Lx and Hybrid Denton leg [12]. However our simulations

have demonstrated the use of the HYBRID III dummy for occupant safety

assessment during a mine blast application with satisfactory results. There is a

scarcity of available data pertaining to lower leg impact during a mine blast

under armored vehicles and extensive research needs to be conducted,

especially testing on human cadavers in order to better understand the injury

assessment and establish a reliable and extensive source of experimental data.

Further, new injury criteria for the foot need to be developed. A simple

parametric study was presented to predict the occupant response during lower

leg impact. The parametric study used curve fitting of numerical data using 4th

and 5th order polynomials. A very good coefficient of correlation was seen,

justifying the use of a parametric approach to study trends in the occupant

response without having to resort to further numerical simulations and destructive

tests.

4.5 Scope for Future Work

More advanced dummies with detailed leg models can be used in place of

the HYBRID III dummy. The lower leg and foot response can be further studied for

different types of input pulses and impact speeds, as well as other occupant

seated positions. More injury criteria can be formulated that utilizes other data

apart from foot accelerations and compressive femur loads. The simple

parametric study presented to predict the occupant’s response to lower leg

impact can be further worked on by increasing the data set used for curve

fitting thereby ensuring better accuracy and more generality. Also, more input

parameters can be included in the regression analysis, such as occupant size,

weight, and gender which vary as per the numerical dummy used, thereby

varying the occupant’s lower leg response to foot impact.

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Chapter 5

Dynamic Axial Crushing of Circular Tubes:

Numerical Formulation

5.1 Need for a Simple Numerical Formulation

Studies of the axial crushing of cylindrical shells involve analytical and numerical

approaches, which are then compared to experimental studies to validate the

proposed approach. Analytical studies are limited in their approach and

sometimes rely on the curve fitting of experimental data in order to obtain

expressions for certain parameters. Further, analytical approaches are usually

able to only predict either approximate or mean values of the parameters

studied, such as mean static and dynamic crushing load, approximate half

wavelength of crushing, and approximate energy absorbed per fold formation.

It is not possible to obtain the time histories of variables during the impact event,

such as instantaneous impactor velocity and deceleration, instantaneous

plastic work of crushing, and instantaneous dynamic crushing load. These

parameters are important in applications involving occupant safety, where they

can be compared with reference values to assess occupant survivability. For

example, the acceleration response of the impactor will yield the acceleration

response of a crew seat in a vertical drop test to simulate aircraft crash-landing.

This can then be compared to the peak acceleration that can be sustained by

a human to assess survivability. Table 5.1 displays the human tolerance limits for

typical crash pulses along three mutually orthogonal axes, for a well restrained

young male. These values provide a general outline of the safe acceleration

limit for a human during a typical crash. Higher acceleration pulses can be

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96

sustained for shorter durations compare to lower acceleration pulses for longer

durations [14].

Direction of Accelerative

Force

Occupant’s Inertial Response Tolerance Level

Headward (+Gz) Eyeballs Down 25 G

Tailward (-Gz) Eyeballs Up 15 G

Lateral Right (+Gy) Eyeballs Left 20 G

Lateral Left (-Gy) Eyeballs Right 20 G

Back to Chest (+Gx) Eyeballs-in 45 G

Chest to Back (-Gx) Eyeballs-out 45 G

Table 5.1 Human tolerance limits to acceleration [14]

Numerical studies involve the use of commercial finite element packages, such

as the dynamic analysis finite element code ABAQUS© in [33, 37, 38], and

RADIOSS© in [35]. These analyses sometimes contain inaccuracies due to the

high mesh-sensitivity of the impact simulation. There is a difference in shell

response when simulating impact as a moving mass striking the stationery shell

as commonly observed in laboratory conditions, and as a the moving shell

striking a stationery rigid wall. Also, inappropriately filtering the data can lead to

significant under estimation of results such as crushing load [38]. However, the

results from numerical studies are still reliable and can be used to accurately

study the crushing of tubes. As the mesh density increases, so does the

computational intensity, and subsequently running numerous simulations to

study the response of different combinations of mesh densities, impactor

parameters, tube material and geometrical properties becomes very expensive

computationally, and time consuming.

Therefore, a simple numerical formulation was developed that extended on

analytical approaches and was able to accurately predict the instantaneous

response of the cylindrical shell under dynamic axial impact, but at a fraction of

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the computational expense. The primary purpose of the numerical formulation

remained the response prediction for any combination of input parameters

such as impactor mass and velocity, and tube geometric and material

properties. The formulation is based on an energy balance approach that

primarily utilizes analytical work of [28, 29, 31], to predict the response history

such as the impactor velocity and deceleration, plastic work and kinetic energy

dissipated, and the dynamic crushing load. The formulation is implemented in

the high-level language MATLAB© and is run on a Pentium 1.3 GHz personal

computer. Run times average around 40 seconds for a tube approximately 228

mm in length impacted at 8 m/s by a 78 kg mass.

5.2 Theory and Formulation

Terminology:

h thickness of shell element / cylinder wall

2H initial distance between hinges on top and bottom of a basic

folding

element

α folding angle

v velocity of impacting mass

R mean radius of cylinder

D mean diameter of cylinder

l folding length

L length of cylindrical tube

ε circumferential strain

σo yield stress

NRB refers to a nodal rigid body that may either represent an impactor

or

a combination of a seat and a human occupant

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m mass of NRB or impactor

Δt time step

M full plastic moment of the tube wall per unit length

The formulation can be used in two configurations, each of which will require

slight modifications be made to the program code. The first configuration

involves an impactor striking a stationery aluminum crush tube, whose farthest

end is supported by a stationery rigid wall. The second configuration involves the

application of the formulation in crashworthiness applications. Here, both the

aluminum tube and the impactor initially move with the same velocity. A large

deceleration pulse is applied to the supporting structure to simulate the impact

event, say impact after freefall as displayed in Figure 5.1.

-20

0

20

40

60

80

100

0 20 40 60 80

Time (ms)

Acc

eler

atio

n (G

)

Vertical Drop TestPulse

Figure 5.1 Applied deceleration pulse simulating impact after freefall

This deceleration pulse is transmitted from the support structure to the impactor

which begins to crush the tube. The final response of the impactor will indicate

the crushing response of the aluminum tube. Usually, the crew seat of an aircraft

represents the impactor, and thus its acceleration response will indicate the

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deceleration pulse that will be transmitted directly to the human occupant, and

this forms the basis of the survivability study.

This formulation uses a simple energy balance equation in order to predict the

response history of the energy absorbing seat or EA seat, as the aluminum tubes

get axially crushed during impact. The initial kinetic energy of the NRB (here, EA

seat) is absorbed by various sources during the impact test and is given by

Equation 5.1

_ _ _. . .......init finalNRB NRB crushing friction rail bending seat frame defK E K E E E E E E= + + + + +

(5.1)

For the sake of simplicity, we only consider energy dissipated by the dynamic

axial crushing of the aluminum tubes, as this is the predominant source of

energy dissipation. If the NRB were only to represent an impactor, then the other

sources such as seat frame deformation and seat cloth tearing would

automatically be excluded as they would be non-applicable to the study.

Rewriting Equation 5.1 in iterative form, we get

( ) ( 1) ( ). .n n nNRB NRB crushingK E K E E−= −Δ

(5.2)

For the first step of the iteration, the crushing energy is zero and therefore the

kinetic energy of the NRB is given by

(1) 21.2NRB initK E mv=

(5.3)

Equation 5.4 to Equation 5.17 discusses the approach used to compute the

energy absorbed during the dynamic axial crushing of the tubes. Figure 5.2

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depicts the formation of a basic folding element, which occurs progressively

until the entire tube has been crushed or the impactor has been brought to rest.

Figure 5.2 Formation of a basic folding element [29]

Johnson [157] computes the energy absorbed due to circumferential forces as

10

2H

oE h dAσ ε= ∫ (5.4)

with

[ ]{2 ( sin ) 2 } 2d R s R Rdtα

εΠ + − Π Π

= (5.5)

and

2 ( sin )dA R s dsα= Π + (5.6)

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Alexander [31] however does not consider the variation of ‘s’ in the computation

of mean circumferential strain. It is also worthwhile to note that the simple

approaches adopted by Alexander [31], Abramowicz and Jones [29] do not

account for strain hardening of the material during the formation of lobes.

Substituting Equations 5.5 and 5.6 in Equation 5.4, we get, as per [29]

2 31

1sin4 cos

2 3odE H HE hdt R

ασ αα⎛ ⎞

= = Π +⎜ ⎟⎝ ⎠ (5.7)

The aim is to obtain the energy dissipated by the formation of a lobe at each

time increment, so that the dynamic response can be studied and time histories

of plastic work and NRB velocity can be extracted.

Writing Equation 5.7 in iterative form

2 3 ( )( ) ( ) ( ) ( )1

sin4 cos2 3

nn n n n

oH HE h t

Rασ α α

⎛ ⎞Δ = Π + Δ⎜ ⎟

⎝ ⎠ (5.8)

Disregarding the variation of mean circumferential strain with ‘s’, Equation 5.5

becomes

cosHRααε =

(5.9)

Equation 5.9 is solved using the non-linear Levenberg-Marquardt formulation, to

obtain the fold angle at each increment, since the strain rate at each time step

is known. Substituting rate of change of fold angle from Equation 5.9 into

Equation 5.8, we obtain

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2 3 ( ) ( )( ) ( ) ( )1 ( )

sin4 cos2 3 cos

n nn n n

o n

H H RE h tR Hα εσ α

α⎛ ⎞

Δ = Π + Δ⎜ ⎟⎝ ⎠ (5.10)

The increment in time or time step is usually kept constant throughout the

analysis. The choice of time step is very important, as if the time step is too

large; it does not capture the folding process properly and can lead to drastic

underestimation of energy dissipated. Within the formation of each lobe, since

0°< α <90°, the sub-iterative process is stopped when the fold angle exceeds

90°. The next main iteration is started, for the formation of the subsequent fold.

Abramowicz and Jones [29] suggested an equation for the strain rate during the

axisymmetric or concertina mode of crushing. The velocity of the NRB and

consequently the strain rate of the aluminum tubes change (decrease) with

each time increment. Thus we need to apply an iterative method to their

equation to update the strain rate at each instant.

( 1)( ) 0.25

0.86 0.618 2

nn v

hR R

ε−

=⎡ ⎤−⎢ ⎥⎣ ⎦ (5.11)

In their derivation of Equation 5.11, Abramowicz and Jones assumed the mean

velocity of the striking mass as half of the initial striking velocity, based on an

approximation of observed experimental results. However, for this application,

based on experimental observations of [9] and simulations run using the explicit

dynamic analysis finite element software LSDYNA© by Nilakantan [50], the mean

velocity is approximately 0.70 - 0.85 times the initial impact velocity. Thus the

factor of 0.25 in Equation 5.11 needs to be suitably calibrated to yield the best

approximation. Values ranging between 0.35 and 0.48 were found to yield the

best application-specific fit. Substituting Equation 5.11 into Equation 5.10, we

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obtain a final equation for the computation of increment in energy dissipated

by circumferential forces at each time step.

( )2 ( )

( ) ( 1) ( )1

sin 12 3 0.86 0.618 2

nn n n

oH HE hv t

R hR

ασ − ⎛ ⎞Δ = Π + Δ⎜ ⎟

⎝ ⎠ − (5.12)

Alexander [31] calculated the energy dissipated in three stationery

circumferential plastic hinges during the crushing of one lobe

2 4 ( sin )dE Md D hα α= Π + (5.13)

where

2

0243HM σ

= (5.14)

Differentiating Equation 5.13 with respect to time and writing it in iterative form,

as before,

( ) ( ) ( ) ( ) ( )2 4 ( sin )n n n n nE M D h tα α α⎡ ⎤Δ = Π + Δ⎣ ⎦ (5.15)

Thus, the total incremental energy absorbed due to axial crushing, at each time

increment is

( ) ( ) ( )

1 2n n nE E EΔ = Δ + Δ (5.16)

Equation 5.16 is used to update the total crushing energy as

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( ) ( 1) ( )n n ncrushing crushing crushingE E E−= + Δ (5.17)

We can now compute the net instantaneous kinetic energy of the NRB as

( ) ( 1) ( ). .n n nNRB NRB crushingK E K E E−= −Δ

(5.18)

or

( ) ( ) ( ). .n initial nNRB NRB crushingK E K E E= −

(5.19)

From this, the velocity response of the NRB is computed as

( )( ) 2 . nn NRBK Ev

m=

(5.20)

The above sub-iterative procedure represented by Equation 5.2 to Equation

5.20 is repeated until the fold angle reaches 90°. Then, the entire procedure is

repeated ‘N’ times or until the net kinetic energy of the NRB falls below zero,

whichever occurs first. The former case indicates that the maximum number of

folds has been formed and the tube is fully crushed, while the latter case

indicates that the velocity of the NRB seat has been brought to zero before the

tube has been fully crushed. Here ‘N’ stands for the number of folds that can be

formed in a tube of length ‘L’ and is given as

/ 2N L l= (5.21)

where

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‘l’ is the half fold length presented by Alexander [31] as

( )1 2/ 3l Rtπ=

(5.22)

which is based on the static yield stress of the material, and needs to be

corrected by a factor given by [32]

* 0.86 0.568 tl D= − (5.23)

The choice of the fold length is very important as it determines the simulation

run-time as well as the total energy dissipated (number of folds x energy

absorbed per fold) which controls the final velocity. Various authors have

presented different formulae to calculate the fold length, each considering

certain factors. These include Abramowicz and Jones [30]

( )1 21.76 / 2l Rt= (5.24)

which is based on the static yield stress, and Wierzbicki et al. [41]

( )1 22.62 / 2l Rt= (5.25)

which uses a flow stress equal to 92% of the ultimate tensile stress of the material

[38]. The formula of Wierzbicki et al. in Equation 5.25 provided the most

accurate results and was therefore chosen for our formulation. Galib and Limam

[35] have provided a brief tabular description of various analytical models.

Karagiozova et al. [37] have reported that for high energy impact and strain rate

sensitive shells, there is a significant axial crushing of the shell, represented by Δ,

which leads to a shortening of the shell. Thus, if ‘L’ is the initial length of the shell,

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only ‘L- Δ’ will be available for the formation of folds. This may lead to an

overestimation of the number of folds, if the axial shortening of the shell is not

considered. In such a situation, the energy dissipated during the axial crushing

also needs to be considered into the energy balance, if its magnitude is

significant.

The following portion describes the changes that need to be made when using

the formulation in the second configuration. In the experimental vertical drop

tests outlined in [9], the support structure and platform are not instantaneously

brought to rest, rather, a deceleration pulse is applied as described in Figure

5.1, resulting in a rapid initial decrease in the initial velocity and then the

structure is gradually brought to rest. To account for this deceleration pulse into

the formulation, we need to use the relative velocity between the EA seat and

support structure instead of the instantaneous EA seat velocity, in all equations

where it is used and at each time step, given as

( ) ( ) ( )n n nrel inst strucv v v= −

(5.26)

The input deceleration pulse, similar to the one displayed in Figure 5.1, is time

integrated to obtain the instantaneous structure velocity. This is fed into the

formulation to determine the relative EA seat velocity at each time increment.

Finally, we obtain the entire relative velocity history of the EA seat. A Fast Fourier

Transform (FFT) is performed on the velocity history data to establish the cut-off

frequency that will be used for filtering the data. Then, a low pass Butterworth

filter is applied to the velocity data and it is differentiated with respect to time to

finally obtain the acceleration response of the EA seat. From this, the magnitude

of the maximum acceleration is obtained, which is used for injury assessment

and survivability studies by comparing it to allowable values. The choice of

filtering can have an adverse effect on the interpretation of some

crashworthiness parameters, such as the underestimation of energy dissipation

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when integrating force-displacement history that has been filtered with low

frequency filters [38]. Similarly, the choice of filter can affect the acceleration

response of the EA seat and therefore care must be taken in choosing the right

filter and filtering frequency.

5.3 Results and Discussion

To validate the formulation, results have been compared with numerical results

from axial impact tests of cylindrical shells by Karagiozova et al. [37], using the

FE code Abaqus/Standard©. This corresponds to the use of the formulation in

the first configuration. Table 5.2 lists the parameters used in the numerical

simulation of [37].

Shell Radius (mm) 11.875

Shell Thickness (mm) 1.65

Shell Length (mm) 106.68

Young’s Modulus (GPa) 72.4

Yield Stress (MPa) 295

Impact Speed (m/s) 4

Impactor Mass (kg) 262.5

Table 5.2 Characteristics of the shell and impactor [37]

Figure 5.3 compares the instantaneous velocity of the impactor from the

numerical simulation and the formulation. The total simulation time, which is

either the time taken to completely crush the tube or bring the impactor to rest,

is accurately predicted by the formulation. The formulation accurately predicts

the instantaneous impactor velocity in the initial period of the simulation.

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-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04Time (s)

Velo

city

(m/s

)

Karagiozova et al.(Numerical)

Formulation

Figure 5.3 Comparison of impactor velocity time history

A slight deviation is observed towards the end of the simulation. This can be

attributed to the strain hardening effect of the material which is captured in the

simulation by using an appropriate material model. However strain hardening is

not accounted for in the formulation, as it is based on the simple uniaxial yield

stress of the aluminum. Since the velocity is calculated from the residual kinetic

energy of the NRB, any deviation in the computed energy will reflect in the

computed velocity.

Figure 5.4 compares the kinetic energy of the impactor (Tk) and the energy

dissipated in plastic deformations (Tp) from the numerical simulation and

formulation. The results from the formulation are in very good agreement with

the numerical simulation.

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0

0.5

1

1.5

2

2.5

0 0.01 0.02 0.03 0.04Time (s)

Ener

gy/W

ork

(KJ)

Tk - Numerical

Tw - Numerical

Tk - Formulation

Tw - Formulation

Figure 5.4 Comparison of energy transformation during the impact event

Figure 5.5 compares the dynamic crushing load obtained from the numerical

simulation and the formulation. It is not possible to get an exact match in the

shapes of both plots, which was also experienced in [35]; during a comparison

of dynamic crushing load from numerical simulation and from experiments.

However we can observe that the peaks in both cases are in reasonable

agreement in terms of the occurrence and magnitudes. Moreover, the mean

dynamic crushing load as computed from the formulation agrees well with the

numerical simulation.

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0

10

20

30

40

50

60

0 0.01 0.02 0.03 0.04Time (s)

Cru

shin

g Fo

rce

(KN

)

Numerical

Formulation

Figure 5.5 Comparison of dynamic crushing load

The formulation is now used in the second conFigureuration, to compare results

with experimental data from [9]. To model the system, the EA seat and crush

tube are initially moving with the same velocity. The deceleration pulse is then

applied to one end of the crush tube, and the response of the impactor, in this

case an EA seat, at the other end is observed. The formulation tracks all the

instantaneous velocities. Figure 5.6 displays the velocities of the structure, and

instantaneous and relative EA seat velocity.

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-10000

100020003000

40005000600070008000

900010000

0 0.02 0.04 0.06 0.08TIme (s)

Velo

city

(mm

/s) Instantaneous EA

Seat Velocity

Structure Velocity

Relative EA SeatVelocity

Figure 5.6 Velocities from the numerical formulation

The relative EA seat velocity is integrated with respect to time to obtain the

acceleration data in its raw or unfiltered form, as displayed in Figure 5.7.

-2.00E+06-1.00E+060.00E+001.00E+062.00E+063.00E+064.00E+065.00E+066.00E+067.00E+068.00E+06

0 0.02 0.04 0.06 0.08

Time (s)

Acc

eler

atio

n (m

m/s

2)

Unfiltered data

Figure 5.7 Unfiltered EA seat acceleration data

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On performing an FFT of the relative velocity data, the cut-off frequency was

chosen as 20 Hz, as illustrated in Figure 5.8.

0

2000

4000

6000

8000

10000

12000

0 50 100 150 200 250 300 350

Frequency (Hz)

FFT

(rel

ativ

e ve

loci

ty) FFT

Figure 5.8 FFT of the relative velocity of the EA seat

The unfiltered acceleration data is then filtered using a Butterworth filter with a

cut-off frequency of 20 Hz. The maximum magnitude is determined to be

approximately 30.5 G. Figure 5.9 compares the EA seat acceleration response

from experiment and numerical formulation.

-20

-10

0

10

20

30

40

0 10 20 30 40 50 60 70 80 90

Time (ms)

Acc

eler

atio

n (G

)

ExperimentFormulation

Figure 5.9 Comparison of acceleration response

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Figure 5.10 compares the peak acceleration magnitudes of EA seat from

experiment, simulation and formulation. All factors involved in the actual

experiment could obviously not be replicated in this simple formulation, and

thus there is a small difference in the peak accelerations.

Experimental Simulation Formulation0

5

10

15

20

25

30

35

Acc

eler

atio

n (G

)

Figure 5.10 Comparison of peak acceleration magnitude

The simple formulation presented herein utilizes uniaxial yield stress and therefore

does not include the plastic strain and strain hardening effect of a material. In

order to do so, the tangent modulus needs to be introduced into the

calculation of increment stress from increment strain at each step, and this must

be used to update the strain energy. This is automatically taken care of by

Material Model 24 in LSDYNA which allows the user to input an arbitrary stress

versus strain curve, as well as for an arbitrary strain rate dependency to be

defined. The energy dissipation due to bending and cracking of the seat

structure and rail, tearing of the seat cloth, and friction during sliding of the seat

brackets against the rail, has not been considered in the energy balance

formulation. The above contributions do not drastically later the energy balance,

but should be considered for accurate comparison between experiments and

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the formulation. The support structure velocity was loaded from a data file

obtained through experiments. Since the time step used in the formulation is

1.00E-05 seconds, the same frequency must be used during the collection of

experimental/simulation data, since this data is used in the calculation of the EA

seat relative velocity. However the frequency of experimental and simulation

data was only 10,000 cycles/sec, and that obtained from the data file was

about 1000 data points for each second, leading to a slight step formation

which can be observed in the plot of relative EA seat velocity. This problem

however was slightly offset during the filtering of the data. Taking into account

the points mentioned above, the results of the simple numerical formulation

were in reasonable agreement with the results from experiments when used in

the second configuration, as can be seen from Figure 5.11. With appropriate

modifications, the formulation proves to be a reliable, low-cost method to

ultimately predicting crew response caused by acceleration from crash.

5.4 Conclusions

The simple numerical formulation presented herein can accurately predict

results when used in the first configuration. When used in the second

configuration, there is a slight overestimation of the predicted peak

acceleration response, due to the current non-reproducibility of all experimental

conditions into the formulation. However, the more the number of terms

considered in the energy balance equation represented by Equation 5.1, the

more will be the accuracy of the formulation. In summary, the formulation is

accurately able to predict key impact event variables that are essential in the

study of injury assessment in crashworthiness applications, and design of energy

absorbing devices.

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5.5 Scope for Further Work

The simple numerical formulation presented herein utilizes the simple uniaxial

yield stress in the energy computations. However, the aluminum crush tube

displays a strain hardening effect, and this needs to be included into the

calculations, by also incorporating the tangent modulus of the material. The

formulation can also be extended from 1-d to multi-dimensions as well as cases

where the impacting mass is offset from the axis of the circular tubes. The

calculation of the dynamic crushing force using the impulse-momentum

equation needs to be refined for improved accuracy.

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Chapter 6

Ballistic Impact of Woven Fabrics

6.1 Description of the Material Model

A computational micro-mechanical material model of loosely woven fabric for

non-linear finite element impact simulations is presented in this chapter. The

model is a mechanism incorporating the crimping of the fibers as well as the

trellising. The equilibrium of the mechanism allows the straightening of the fibers

depending on the fiber tension. The contact force at the fiber crossover points

determines the rotational friction which dissipates a part of the impact energy.

The stress-strain relationship is elastic based on a one-element spring model. The

failure of the fibers is strain rate independent. The model is implemented as user

defined subroutine in the transient finite element code LS-DYNA. The reader is

encouraged to refer [144] for the basic terminology and formulation of the

material model, since most parts remain similar to the work presented here.

6.2 The Representative Volume Cell of the Model [144]

The representative volume technique, vastly used in the micro-mechanical

models, is utilized hereafter. A current deformed state of the fabric is

considered. The Representative Volume Cell (RVC) of the loosely woven fabric

material model is extracted from the deformed pattern of the material, as seen

in Figure 6.1. The RVC consists of an undulated fill yarn crossed over an

undulated warp yarn as seen in Figure 6.1. The parameters of the RVC are: the

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yarn span, s, the fabric thickness, t, the yarn width, w, and the yarn cross-

sectional area, S.

warp yarn

fill yarn

t

s

w

S

Figure 6.1 Representative Volume Cell (RVC) of the model

The complex geometry of the yarns is simplified and they are represented as a

pin-joint mechanism of straight elastic bars connected at the middle crossover

point by a rigid link as seen in Figure 6.2. The end nodes of the yarns are always

in the plane of the shell element xy. The distance between the central nodes of

the yarns in z-direction is provided by the rigid link of length t/2, which is always

normal to the xy-plane, and their z-coordinates depend on the equilibrium of

the stretching forces in the yarns. The pin-joints have axes always parallel to the

xy-plane and perpendicular to the bars. The mechanism allows the in-plane

rotation of the yarns about the rigid link as a trellis mechanism and the

straightening of the zig-zag undulated yarns depending on their tension. The

deformation of the yarns as a result of the contact between the yarns is

neglected. The in-plane orientation of the yarns is determined by the unit

vectors, q’s, or the braid angles, θ’s, measured with respect to the axis x of the

RVC coordinate system. The subscript f denotes the fill yarn and the subscript w

denotes the warp yarn.

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In explicit finite element codes as LS-DYNA, the material model has to determine

the stress response of the material to the strain increment obtained at each

time step of the explicit time integration. Assuming that the RVC coordinate

system is the shell element local coordinate system, the stress response of the

woven fabric RVC to the strain increment passed to the model in the RVC

coordinate system has to be developed by the micro-mechanical approach.

fill yarn

warp yarn

θfqf

θwqw

x

y

z

t/2

rigid link

Figure 6.2 Pin-joint bar mechanism

6.3 Elastic Model

Figure 6.3 One Element Elasticity Model

σ, ε σ, ε

Ka

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The governing equation of elasticity for the one element elastic model can be

derived from equilibrium as

aKσ ε= (6.1)

Then Equation 6.1 can be written in incremental form for the time step n+1 as

follows:

( ) ( ) ( ) ( )( )n n n n

aKσ σ ε ε+ Δ = + Δ (6.2)

We can determine the stress increment from the last equation

( ) ( ) ( ) ( )n n n na aK Kσ ε ε σΔ = + Δ − (6.3)

Where Ka is the spring stiffness and is equal to E1, the static Young’s modulus of

elasticity. The only failure mode available is when the fiber strain reaches the

failure strain or

maxaK

σε ε= > (6.4)

The input parameters for the Elasticity model are Hookean spring coefficient Ka

and static ultimate strain εmax. We now consider the equilibrium position of the

central nodes as seen in Figure 6.4..

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Figure 6.4 Equilibrium position of the central nodes

We consider the equilibrium of the central nodes (the crossover point) of the

yarns at time step n+1 because the incremental elasticity equations of the

yarns are written for this instant. Again we assume that this state is linear

interpolation of the states at time step n and time step n+1. The equilibrium

state is given in Figure 6.4 for the fill yarn (upper scheme) and for the warp yarn

(lower scheme). The span between the yarns and the length of the bars can be

calculated for each time step of interest as follows:

ssss nw

nw

nf

nf

)1()1()1()1( , ++++ Λ=Λ= (6.5)

( ) ( )2)()(2)1(

)1(2)()(

2)1()1(

2,

2nn

w

nwn

wnn

f

nfn

f hs

Lhs

L δδ −+⎟⎟⎠

⎞⎜⎜⎝

⎛=++

⎟⎟⎟

⎜⎜⎜

⎛=

++

++ (6.6)

The vertical components of the yarn forces can be determined as follows:

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121

( )( ) ( ) ( ) ( )

( ) ( )( 1) ( 1)

n n n nf f n n

f f f fn nf f

h hF N S

L Lδ δ

σ σ+ +

+ += = + Δ (6.7)

( )( ) ( ) ( ) ( )

( ) ( )( 1) ( 1)

n n n nn nw w

w w w wn nw w

h hF N SL L

δ δ σ σ+ +

− −= = + Δ (6.8)

where S is the cross-sectional area of the yarns. The equilibrium of the

mechanism is reached when

wf FF 22 = (6.9)

Developing Equation (24) by plugging in Equations (14) and (16) we get:

( )

( ) ( )( ) ( ) ( )

1 2n n

f n n na f a f fn

f

hK K S

Lε ε σ

+

+ ∂⎡ ⎤+ Δ −⎣ ⎦

= ( )

( ) ( )( ) ( ) ( )

1 2n n

n n nwa w a w wn

w

h K K SL

ε ε σ+

+ ∂ ⎡ ⎤+ Δ −⎣ ⎦ (6.10)

The strain increments of the yarns are determined by the expressions:

( ) ( )1( )

n nf fn

f

L LL

ε+ −

Δ = and ( ) ( )1

( )n n

n w ww

L LL

ε+ −

Δ = (6.11)

Where L is the initial length of the bars calculated by the formula:

2 2

2 4s tL ⎛ ⎞ ⎛ ⎞= +⎜ ⎟ ⎜ ⎟

⎝ ⎠ ⎝ ⎠ (6.12)

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Substituting yarn strain increments of Equation 6.11 in Equation 6.10 and

plugging Equations 6.6 in, we can get the final equation after some small

simplifications:

( )( )

( )21

2( ) ( ) ( ) ( )

2

nn n n nw

f wsh h

+⎛ ⎞+ ∂ + −∂⎜ ⎟⎜ ⎟

⎝ ⎠ x

( )

( ) ( )21

2( ) ( ) ( ) ( )22

nf nn n n na

a f f f f

sKK h LL

ε σ+⎡ ⎤⎛ ⎞⎛ ⎞⎢ ⎥⎜ ⎟− + + + ∂ −⎜ ⎟⎢ ⎥⎜ ⎟⎜ ⎟⎜ ⎟⎝ ⎠⎢ ⎥⎝ ⎠⎣ ⎦

+ ( )( )

( )21

2( ) ( ) ( ) ( )

2

nfn n n n

w f

sh h

+⎛ ⎞∂ − + + ∂⎜ ⎟

⎜ ⎟⎝ ⎠

x

( )

( ) ( )21

2( ) ( ) ( ) ( )22

nnn n n na w

a w w w wK sK h LL

ε σ+⎡ ⎤⎛ ⎞⎛ ⎞⎢ ⎥⎜ ⎟− + + −∂ −⎜ ⎟⎜ ⎟⎢ ⎥⎜ ⎟⎜ ⎟⎝ ⎠⎢ ⎥⎝ ⎠⎣ ⎦

= 0

(6.13)

Equation (6.13) can be solved numerically for ( )n∂ by means of Newton-

Raphson method. The vertical position change of the central nodes is

constrained in order to avoid the snap-through behavior of the mechanism, ( )4 4nt tδ− ≤ ≤ . In this way, the buckling of the yarns in compression is

represented by the structural buckling of the membrane shell element model.

The vertical positions of the central nodes, initially set to 4/)0()0( thh wf == , are

finally updated:

( 1) ( ) ( )n n nf fh h+ = + ∂ , ( 1) ( ) ( )n n n

w wh h+ = + ∂ (6.14)

From here on, the calculation of strain and corresponding stress response

follows the formulation from [144] and is therefore not presented.

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Because the behavior of the yarn has been represented by a one-element

linear spring system, there is no strain rate or viscoelastic effect present. This

implies that regardless of the strain rate in the fabric material during loading or

deformation, the stress-strain response will remain the same. However in reality,

all high strength and high modulus fabrics exhibit varying degrees of

viscoelasticity. But representing a yarn as a simple elastic member greatly

simplifies the formulation as well makes the numerical model less

computationally expensive with good accuracy. Moreover, it acts as a simple

platform on which various modifications and additions can be made to the

model such as adding yarn pullout effect, remote yarn failure, and other

complex phenomena, after which the yarn behavior can then be easily

switched back to being viscoelastic. Figure 6.5 displays the yarn stress-strain

curves for varying strain rates during the axial testing of a fabric strip that used

the viscoelastic model from [144]. It is evident that the stress-strain response

varies as the strain rate varies. In addition, a transition strain rate can be

observed at 100 s-1, where the mode of failure changes from primary yarn

failure to secondary yarn failure. The curves exhibit non-linearity because of the

viscoelastic nature of the yarn. Figure 6.6 displays the stress-strain response of a

yarn for the same fabric strip test using the elastic model. Perfect linearity is

observed in the plot as a one-element linear spring has been used. No matter

what the strain rate is, the response remains the same. Moreover, this elastic

model has only one mode of yarn failure, unlike the two-mode yarn failure

observed in the viscoelastic model.

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124

Figure 6.5 Yarn stress-strain response of viscoelastic model

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125

Figure 6.6 Yarn stress-strain response of elastic model

6.4 Numerical Results – Fabric Strip Testing

To test the elastic material model, axial and bias tensile tests are conducted on

a Kevlar© strip measuring 203.2 mm x 50.4 mm. Axial tests refer to the case

when the strip is pulled along the direction of the primary yarn. Bias tests refer to

the case when the strip is pulled along a 45 degree angle to the primary yarn.

The numerical setup is displayed in Figure 6.7. The strip is modeled using shell

elements which utilize the elastic material model. During the running of the

simulation, LSDYNA makes external calls to the user defined material model and

passes the strain increments to the model, which then returns the stress

increments to the main program. The set of nodes along the width of one end

of the strip are constrained completely. A displacement control is prescribed for

the corresponding set of nodes on the other end of the strip.

Figure 6.7 Numerical setup of fabric axial strip test

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126

Because fabrics have very low out of plane stiffness, using extremely small

values of shear moduli can cause numerical instabilities and are therefore

scaled higher in the material model. This does not later the behavior of the

fabrics in any way. Table 6.1 lists the material properties of the Kevlar© fabric

strip used. Axial and bias tests are run using strain rates ranging from 1 s-1 to 300

s-1. The numerical results are then compared to data from the axial strip tests

using the viscoelastic model outlined in [144]. Element stresses and strains,

fabric deformation shape and stress contours are observed. Figure 6.8 displays

the Von-Mises stress distribution for a Kevlar© strip test with a prescribed strain

rate of 30 s-1.

Figure 6.8 Von-Mises stress distribution for strip with 30 s-1 strain rate

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127

Longitudinal Young’s modulus 25 GPa Locking angle 10 deg

Transverse Young’s modulus 1.5 GPa Initial braid angle 45 deg

Shear modulus (G12) 1 GPa Coefficient of friction (μ) 1.7

Shear modulus (G23) 1 GPa Bulk modulus (K) 500 GPa

Shear modulus (G) 300 GPa Primary spring stiffness (Ka) 50 MPa

Yarn failure strain (εfail) 0.30 Yarn width (w) 0.32750 mm

Fabric real thickness 0.23 mm Yarn cross sectional area (S) 4.63E-02 mm2

Fabric effective thickness 0.125 mm Yarn span (s) 0.74710 mm

Table 6.1 Material and geometric properties of the Kevlar© fabric strip

6.4.1 Elastic model fabric strip test

Figure 6.9 displays the stress-strain curves for an element at the middle of the

strip during the axial tests. For very low strain rates ranging from 0.01 s-1 to 1 s-1,

an initial almost flat portion is seen in the plot, as the element stresses are very

low and take time to start building up. The stress wave propagates extremely

slowly through the fabric strip from the end being pulled to the constrained end.

There is very little geometric non-linearity for such low strain rates and as a

consequence, in accordance with the material model which uses one spring

element to represent the yarn behavior, the stress-strain curve is linear. As the

strain rate increases, there is increased geometric non-linearity in the strip due to

excessive deformation of the fabric and the stress-strain curve assumes a

curved shape. Such non-linearity is common in problems where the direction of

forces change as the structure shape deforms, such as pressure on the inner

surface of an elastic hemispherical membrane. When the failure strain is

reached for a particular element, or it warps beyond the maximum shell

warpage angle, it is deleted from the mesh.

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128

-500

0

500

1000

1500

2000

2500

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Strain

Stre

ss (M

Pa)

Elastic-Axial-1

Elastic-Axial-30

Elastic-Axial-100

Elastic-Axial-300

Figure 6.9 Axial strip tests of Elastic model

Figure 6.10 displays the stress-strain curves for an element at the middle of the

strip during the bias tests. Because the fabric is being pulled in the bias

direction, the yarns first realign along the bias direction until the locking angle is

reached and then start getting stretched. This is similar to a trellis mechanism

and is referred to as a scissoring effect. Once the fabric locking angle as

specified in the material model is reached, element stresses start building up.

The locking angle used in these tests was 10 degrees and this roughly

corresponds to a strain of 0.145 in the global reference coordinate system.

Remember, this frame of reference is different from both the RVE coordinate

system and the yarn axes, and thus while a strain in the fabric seems to exist

even with zero stress up to a value of 0.145 in the global system, the yarn strain

is actually zero.

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129

-500

0

500

1000

1500

2000

2500

0 0.1 0.2 0.3 0.4

Strain

Stre

ss (M

Pa)

Elastic-Bias-1

Elastic-Bias-30

Elastic-Bias-100

Elastic-Bias-300

Figure 6.10 Bias strip tests of Elastic model

6.4.2 Viscoelastic model fabric strip test

Figures 6.11 and 6.12 display the stress-strain curves for an element at the

middle of the strip during the axial and bias tests respectively, using the

viscoelastic model. Both strain rate sensitivity and non-linearity can be observed

in the plots. For the bias tests, there is yarn realignment until the locking angle is

reached after which the yarns start getting stressed.

-500

0

500

1000

1500

2000

2500

3000

3500

0 0.1 0.2 0.3 0.4 0.5

Strain

Stre

ss (M

Pa)

Viscoelastic-Axial-1Viscoelastic-Axial-30Viscoelastic-Axial-100Viscoelastic-Axial-300

Figure 6.11 Axial strip tests of Viscoelastic model

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130

-500

0

500

1000

1500

2000

2500

3000

3500

0 0.1 0.2 0.3 0.4 0.5

Strain

Stre

ss (M

Pa)

Viscoelastic-Bias-1Viscoelastic-Bias-30

Viscoelastic-Bias-100Viscoelastic-Bias-300

Figure 6.12 Bias strip tests of Viscoelastic model

6.4.3 Comparison between Elastic and Viscoelastic model results

Figure 6.13 and 6.14 compare the results from the two models. A very good

correlation can be seen between the results of the elastic and viscoelastic

model for the tensile fabric strip tests at varying strain rates. The viscoelastic

model is seen to fail at a higher strain than the elastic model, since the

viscoelastic model has a two mode yarn failure, which occurs at different strain

rates. This good correlation enforces the fact that sometimes simplistic models

can prove to be as reliable as complex models that try to represent all fabric

phenomena to the highest degree possible. The advantage of simple models

lay in their reduced computational requirements.

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131

-50

0

50

100

150

200

250

300

350

400

0 0.05 0.1 0.15 0.2 0.25

Strain

Stre

ss (M

Pa)

Elastic-Bias-1Viscoelastic-Bias-1

-500

0

500

1000

1500

2000

2500

0 0.1 0.2 0.3 0.4

Strain

Stre

ss (M

Pa)

Elastic-Bias-30

Viscoelastic-Bias-30

(a) (b)

-500

0

500

1000

1500

2000

2500

3000

0 0.1 0.2 0.3 0.4

Strain

Stre

ss (M

Pa)

Elastic-Bias-100

Viscoelastic-Bias-100

-500

0

500

1000

1500

2000

2500

3000

3500

0 0.1 0.2 0.3 0.4 0.5

Strain

Stre

ss (M

Pa)

Elastic-Bias-300

Viscoelastic-Bias-300

(c) (d)

Figure 6.13 Comparison of bias tests of elastic and viscoelastic models at

different strain rates a) 1s-1 b) 30-1 c) 100-1 d) 300-1

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132

-200

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Strain

Stre

ss (M

Pa)

Elastic-Axial-1Viscoelastic-Axial-1

-500

0

500

1000

1500

2000

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Strain

Stre

ss (M

Pa)

Elastic-Axial-30Viscoelastic-Axial-30

(a) (b)

0

500

1000

1500

2000

2500

3000

0 0.1 0.2 0.3 0.4

Strain

Stre

ss (M

Pa)

Elastic-Axial-100Viscoelastic-Axial-100

0

500

1000

1500

2000

2500

3000

3500

0 0.1 0.2 0.3 0.4 0.5

Strain

Stre

ss (M

Pa)

Elastic-Axial-300Viscoelastic-Axial-300

(c) (d)

Figure 6.14 Comparison of axial tests of elastic and viscoelastic models at

different strain rates a) 1s-1 b) 30-1 c) 100-1 d) 300-1

6.5 Conclusions

The elastic model is able to capture phenomena such as fabric reorientation,

fabric locking, and rotational frictional effects. A simple failure mode has been

used for the yarns. The results compare very well to the viscoelastic model. Non-

linearity is observed in the Elastic model in spite of using a linear spring to model

the yarn behavior. There is no strain rate sensitivity associated with the yarn

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133

behavior. However, the fabric response shows slight strain rate sensitivity

because of the inherent complex architecture of the fabric and inter-yarn

interactions. The model is very computationally inexpensive while still

maintaining reasonable accuracy. Further testing of the elastic model is

required in the form of transverse impact tests and draping tests before full

validity can be claimed.

6.7 Scope for further work

The phenomena of yarn pullout and remote yarn failure can be included in the

model, as well as the energy dissipated by inter-yarn friction during pullout. A

constant cross section of the yarn has been assumed and therefore the

transverse compression of the yarns has not been accounted for. This can be

overcome by including the compression of the yarns into the equilibrium of the

central nodes of the RVE. Further testing of the Elastic model is required and has

been outlined in the preceding section. A more comprehensive strain based

failure can be incorporated instead of a simple two mode failure. Dynamic

mechanical properties of the fabrics can be fed into the formulation using data

tables, rather than using static properties, as it is well established that the

mechanical properties of the yarns is highly strain rate dependent.

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Appendix I

Source code for the numerical formulation of dynamic

axial crushing of circular tubes

Configuration I

%********************************************************************** % Analysis of Dynamic Axial Crushing of Thin Cylindrical Tubes (and) % Energy Balance formulation to predict EA Seat response % % Author(s): Dr. Ala Tabiei and Gaurav Nilakantan % Date: March, 2006 (Final version) % email: [email protected] / [email protected] % % Notice: The authors assume no responsibility for the veracity, % validity, accuracy or applicability of the formulations or results % obtained herein. % Suggestions and comments are welcome. % % Copyright (C) 2006 % by Tabiei, Nilakantan % All rights reserved % %********************************************************************** % % List of variables: % sigmay - uniaxial yield stress % r - mean radius of the cylindrical tube % d - mean diameter of the cylindrical tube % h - wall thickness of the cylindrical tube % L - axial length of the cylindrical tube % v - final velocity of structure at the time of impact % vinst - instantaneous velocity of EA seat % vrel - relative velocity of EA seat % m - total mass of EA seat and occupant % Mo - full plastic moment of the tube wall per unit % length % H - initial half distance between the plastic hinges % at the top and bottom of a basic folding element % xm - intermediate folding variable % delta - effective crushing distance % l - folding length % n - number of folds that can be formed in distance L % a - angle of fold % da - increment in fold angle % E - total plastic energy absorbed by the tube % dE - increment in E % E1 - energy dissipated due to circumferential forces% % dE1 - increment in E1

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% E2 - energy dissipated during crushing of three % stationery % circumferential plastic hinges % dE2 - increment is E2 % KEi - initial kinetic energy % KEnet - net kinetic energy % Ps - mean static crushing load % Pd - mean dynamic crushing load % i - counter variable % j - counter variable % t - time % dt - increment in time % epsilon_dot - strain rate % alpha_dot - rate of change of fold angle %********************************************************************** % System of consistent units (N,mm,ton,s,degree) %********************************************************************** clear clc %*************************** % User defined data %*************************** %sigmay=input('Enter the uniaxial yield stress of the material (MPa): %'); %r=input('Enter the mean radius of the cylindrical tube (mm): '); %h=input('Enter the thickness of the cylindrical tube (mm): '); %v=input('Enter the final velocity of the structure before impact %(mm/s): '); %m=input('Enter the total mass of the EA Seat and Occupant (ton): '); %L=input('Enter the length of the cylindrical tube (mm): '); %dt=input('Enter the time step for the problem (s): '); global xo global epsilon_dot global r global dt global H %********************************************************************** % Pre defined data - Based on Karagiozova Pg 1095 "Inertia Effects...." %********************************************************************** sigmay=295.000; r=11.875; h=1.65; v=4000.0; m=0.2625; L=106.68; dt=0.00001; %********************************************************************** d=r*2; Mo=(2/sqrt(3))*(sigmay*h^2)/4; xm=0.28*H/2; delta=2*H*(0.86-0.543*sqrt(h/d)); %******************************************************************* % Based on Wierzbicki % Comment: Number of folds greatly effects total run time. The % formulae of Wierzbicki are chosen as it yields the longest % fold length and thus yields the least number of folds l=2.62*sqrt(r*h/2);

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H=1.853*r*sqrt(h/r); %******************************************************************* n=L/(2*l) % Kinetic Energy is in Joules KEi=(0.5*m*(v^2))/1000; %********************************************************************** % From Abramowicz and Jones, as referenced in D. Al Galib et al. Ps=Mo*(25.230*(sqrt(d/h))+15.09); %********************************************************************** vinst=v; vinstarray(1,1)=v; E1=0; E2=0; KEnet=KEi; KE(1,1)=KEi; counter=2; time(floor(n),1)=zeros; cntr(floor(n),1)=zeros; energy_per_fold(floor(n),1)=zeros; totaltime(1,1)=0; totaltime(2,1)=dt; force(1,1)=0; Earray(1,1)=0; % failure flag is activated when net K.E falls below zero failflag=0; for i=1:1:floor(n) a=0; alphainst(1,i)=0; while(a<(pi/2) && KEnet>0) %************************************************************* % Calculation of strain rate from Abramowicz and Jones epsilon_dot=0.5*vinst/r/(0.86-0.618*sqrt(h/d)); xo=alphainst(counter-1,i); % Call function to solve for instantaneous fold angle options=optimset('NonlEqnAlgorithm','lm'); alpha=fsolve(@myfun,0,options); alphainst(counter,i)=alpha; a=alphainst(counter,i); % Computation of fold energies dE1=(4*Mo*pi*(a-xo)*(d+h*sin(a)))/1000; dE2=(4*pi*sigmay*h*(H/2+H^2*sin(a)/(3*r))*epsilon_dot*r*dt)... /1000; E1=E1+dE1; E2=E2+dE2; E=E1+E2; Earray(counter,1)=E; dE=dE1+dE2; energy_per_fold(i,1)=energy_per_fold(i,1)+dE; KEnet=KEnet-dE; if(KEnet<0) failflag=1; end vinst=sqrt(2*KEnet*1000/m); vinstarray(counter,1)=vinst; KE(counter,1)=KEi-E; % Impulse-momentum equation force(counter,1)=m*(vinstarray(counter-1,1)-vinst)/dt;

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time(i,1)=time(i,1)+dt; cntr(i,1)=cntr(i,1)+1; totaltime(counter,1)=totaltime(counter-1,1)+dt; counter=counter+1; if(failflag==1) break end end if(failflag==1) break end end xaxis=[0:dt:(counter-2)*dt]'; %********************************************************************** % Plot of Instantaneous Velocity Vs Time %********************************************************************** subplot(2,2,1); plot(xaxis,vinstarray) title('Instantaneous Velocity Vs Time') %********************************************************************** % Plot of Energy Vs Time %********************************************************************** subplot(2,2,2); plot(xaxis,KE,xaxis,Earray) legend('K.E.','Plastic Work') title('Transformation of Energy w.r.t Time') %********************************************************************** % Plot of Crushing Force Vs Time %********************************************************************** subplot(2,2,3); xaxis2=[0:dt:(counter-2)*dt]'; plot(xaxis2,force) title('Crushing Force w.r.t Time') %**********************************************************************

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Configuration II

%********************************************************************** % Analysis of Dynamic Axial Crushing of Thin Cylindrical Tubes (and) % Energy Balance formulation to predict EA Seat response % % Author(s): Dr. Ala Tabiei and Gaurav Nilakantan % Date: March, 2006 (Final version) % email: [email protected] / [email protected] % % Notice: The authors assume no responsibility for the veracity, % validity, accuracy or applicability of the formulations or results % obtained herein. % Suggestions and comments are welcome. % % Copyright (C) 2006 % by Tabiei, Nilakantan % All rights reserved % %********************************************************************** % % List of variables: % sigmay - uniaxial yield stress % r - mean radius of the cylindrical tube % d - mean diameter of the cylindrical tube % h - wall thickness of the cylindrical tube % L - axial length of the cylindrical tube % v - final velocity of structure at the time of impact % vinst - instantaneous velocity of EA seat % vrel - relative velocity of EA seat % m - total mass of EA seat and occupant % Mo - full plastic moment of the tube wall per unit % length % H - initial half distance between the plastic hinges % at the top and bottom of a basic folding element % xm - intermediate folding variable % delta - effective crushing distance % l - folding length % n - number of folds that can be formed in distance L % a - angle of fold % da - increment in fold angle % E - total plastic energy absorbed by the tube % dE - increment in E % E1 - energy dissipated due to circumferential forces% % dE1 - increment in E1 % E2 - energy dissipated during crushing of three % stationery % circumferential plastic hinges % dE2 - increment is E2 % KEi - initial kinetic energy % KEnet - net kinetic energy % Ps - mean static crushing load % Pd - mean dynamic crushing load % i - counter variable

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% j - counter variable % t - time % dt - increment in time % epsilon_dot - strain rate % alpha_dot - rate of change of fold angle %********************************************************************** % System of consistent units (N,mm,ton,s,degree) %********************************************************************** clear clc %********************************************************************** % User defined data % If needed, remove the comments symbol to allow the user to enter % their own data %********************************************************************** %sigmay=input('Enter the uniaxial yield stress of the material (MPa): %'); %r=input('Enter the mean radius of the cylindrical tube (mm): '); %h=input('Enter the thickness of the cylindrical tube (mm): '); %v=input('Enter the final velocity of the structure before impact %(mm/s): '); %m=input('Enter the total mass of the EA Seat and Occupant (ton): '); %L=input('Enter the length of the cylindrical tube (mm): '); %dt=input('Enter the time step for the problem (s): '); %******************************** % Declaration of global variables %******************************** global xo global epsilon_dot global r global dt global H %************************** % Pre defined data %************************** sigmay=145.000; r=13.667; h=0.890; v=8919.0; m=0.07214; L=228.6; dt=0.00005; %************************** d=r*2; Mo=(2/sqrt(3))*(sigmay*h^2)/4; xm=0.28*H/2; delta=2*H*(0.86-0.543*sqrt(h/d)); %******************************************************************* % Based on Wierzbicki l=2.62*sqrt(r*h/2); H=1.853*r*sqrt(h/r); %******************************************************************* n=L/(2*l); %********************************** % NOTE: Kinetic Energy is in Joules %********************************** KEi=(0.5*m*(v^2))/1000;

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%********************************************************************** % From Abramowicz and Jones, as referenced in D. Al Galib et al. Ps=Mo*(25.230*(sqrt(d/h))+15.09); %********************************************************************** vinst=v; E1=0; E2=0; KEnet=KEi; KE(1,1)=KEi; counter=2; time(floor(n),1)=zeros; cntr(floor(n),1)=zeros; vinstarray(1,1)=vinst; %*********************************************************** % Load file containing velocity profile of support structure %*********************************************************** load strucbot.dat vrel=v-strucbot(1,1); totaltime(1,1)=0; totaltime(2,1)=dt; energy_per_fold(floor(n),1)=zeros; Earray(1,1)=0; % failure flag is activated when net K.E falls below zero failflag=0; for i=1:1:floor(n) a=0; alphainst(1,i)=0; while(a<(pi/2) && KEnet>0) % Calculation of strain rate epsilon_dot=0.5*vrel/r/(0.86-0.618*sqrt(h/d)); xo=alphainst(counter-1,i); % Call function to solve for instantaneous fold angle options=optimset('NonlEqnAlgorithm','lm'); alpha=fsolve(@myfun,0,options); alphainst(counter,i)=alpha; a=alphainst(counter,i); % Computation of fold energies dE1=(4*Mo*pi*(a-xo)*(d+h*sin(a)))/1000; dE2=(4*pi*sigmay*h*(H/2+H^2*sin(a)/(3*r))*epsilon_dot*r*dt)... /1000; E1=E1+dE1; E2=E2+dE2; E=E1+E2; dE=dE1+dE2; KEnet=KEnet-dE; if(KEnet<0) break end % Calculation of instantaneous EA seat velocity vinst=sqrt(2*KEnet*1000/m); % Locate the instantaneous support structure velocity for location=1:1:80 if ((totaltime(counter,1)*1000)>strucbot(location,1) || ... (totaltime(counter,1)*1000)==strucbot(location,1))&&... ((totaltime(counter,1)*1000)<strucbot(location+1,1) ||...

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(totaltime(counter,1)*1000)==strucbot(location+1,1)) vstruc=strucbot(location,2); vstrucarray(counter,1)=vstruc; break end end if(KEnet<0) failflag=1; end vrel=vinst-vstruc; vinstarray(counter,1)=vinst; vrelarray(counter,1)=vrel; KE(counter,1)=KEi-E; velocity(counter,1)=vrel; Earray(counter,1)=E; energy_per_fold(i,1)=energy_per_fold(i,1)+dE; counter=counter+1; time(i,1)=time(i,1)+dt; cntr(i,1)=cntr(i,1)+1; totaltime(counter,1)=totaltime(counter-1,1)+dt; if(failflag==1) break end end if(failflag==1) break end end %********************************************************************** % Plot of Relative Velocity Vs Time %********************************************************************** subplot(2,2,1); xaxis=[0:dt:(counter-2)*dt]'; plot(xaxis,velocity) xlabel('Time (s)') ylabel('Relative Velocity (mm/s)') title('Relative Velocity Vs Time') %********************************************************************** % Plot of Instantaneous Velocity Vs Time %********************************************************************** subplot(2,2,2); plot(xaxis,vinstarray) xlabel('Time (s)') ylabel('Instantaneous Velocity (mm/s)') title('Instantaneous Velocity Vs Time') %********************************************************************** % Plot of Kinetic Energy Vs Time %********************************************************************** subplot(2,2,3); plot(xaxis,KE) xlabel('Time (s)') ylabel('Kinetic Energy (J)') title('Kinetic Energy Vs. Time') %********************************************************************** % Plot of Plastic Work Vs Time %**********************************************************************

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subplot(2,2,4); plot(xaxis, Earray) xlabel('Time (s)') ylabel('Plastic Work (J)') title('Plastic Work Vs. Time') %**********************************************************************

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Function ‘myfun’ used in Configuration I and II

%********************************************************************** % Analysis of Dynamic Axial Crushing of Thin Cylindrical Tubes (and) % Energy Balance formulation to predict EA Seat response % % Author(s): Dr. Ala Tabiei and Gaurav Nilakantan % Date: March, 2006 (Final version) % email: [email protected] / [email protected] % % Notice: The authors assume no responsibility for the veracity, % validity, accuracy or applicability of the formulations or results % obtained herein. % Suggestions and comments are welcome. % % Copyright (C) 2006 % by Tabiei, Nilakantan % All rights reserved % %********************************************************************** function F=myfun(alpha) global xo global epsilon_dot global r global dt global H F=(alpha-xo)*cos(alpha)-(epsilon_dot*r*dt/H); end

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Contents of the ‘strucbot’ data file

0.000000000 8918.999023 0.999868847 8918.999023 1.999737695 8918.999023 2.999963937 8918.999023 3.999832552 8918.999023 4.999701399 8918.999023 5.999927875 8918.999023 6.999796722 8918.999023 7.999665104 8918.999023 8.999891579 8918.999023 9.999760427 8918.999023 10.9999869 8903.797852 11.99985575 8909.385742 12.9997246 8911.800781 13.99995107 8912.78125 14.99981992 8913.760742 15.99968784 8914.741211 16.99991524 8915.720703 17.99978316 8916.701172 18.99965294 8917.680664 19.99987848 8917.517578 20.99974826 8911.72168 21.9999738 8894.895508 22.99983986 8865.357422 23.9997115 8788.709961 24.999924 8650.976563 25.99980123 8456.224609 26.99979954 8130.765625 27.99988911 7654.873535 28.99986878 7093.491211 29.99978885 6399.95166 30.99999577 5641.805664 31.99985623 4954.264648 32.99997374 4430.261719 33.99997577 4053.821533 34.99996662 3777.724365 35.99990532 3489.584473 36.99990735 3158.296387 37.99990937 2764.373291 38.99997473 2302.322266 39.99994323 1877.890137 40.999908 1509.176025 41.99997336 1270.943848 42.99993068 1161.104248 43.99995133 1135.381592 44.99999061 1126.782959 45.99997401 1047.84314 46.99999094 903.3579102 47.99992219 753.4771118 48.99991304 621.5859985 49.99994114 556.0709839 50.99992454 576.8318481 51.99996755 650.6864624 52.99992487 771.6782837

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53.99993807 881.1166382 54.99996245 925.1243897 55.99997565 942.7033691 56.9999665 883.3707886 57.999935 820.6410523 58.99997428 790.6043091 59.99993533 796.6851807 60.99992245 849.2549439 61.99995056 934.7791138 62.99994886 1016.16272 63.99992108 1045.249146 64.99996781 1035.973145 65.99995494 1018.441101 66.99997187 991.5888062 67.99998879 964.7364502 68.99996102 954.8067017 69.9999854 963.5032959 70.99998742 984.4906006 71.99994475 1018.152466 72.99996913 1048.165405 73.9999935 1062.786255 74.99996573 1059.519531 75.99996775 1040.250244 76.99998468 1014.58783 77.99999416 987.2261963 78.99996638 978.5117188 79.99999076 977.9264526 80.99997789 998.3884888 81.99997991 1016.932434 82.99996704 1033.3125 83.99996907 1036.335205 84.99999344 1036.62085 85.99995822 1031.807617 86.9999826 1023.998779 87.99996227 1016.104065 88.9999941 1010.756287 89.99998868 1018.790222 90.00004828 0.000

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Appendix II

Source code for the incremental constitutive equation

used in the Elastic material model to derive the stress-

strain relationship

%********************************************************************** % Program to calculate Stress-Strain in a Loose Woven Fabric with % linearly elastic crimped fibers using a 1-element Spring Model. % Micro Mechanical approach has been utilized. % % Author(s): Dr. Ala Tabiei and Gaurav Nilakantan % Date: February, 2005 (Final version) % email: [email protected] / [email protected] % % Notice: The authors assume no responsibility for the veracity, % validity, accuracy or applicability of the formulations or results % obtained herein. % Suggestions and comments are welcome. % % Copyright (C) 2005 % by Tabiei, Nilakantan % All rights reserved % %********************************************************************** clear all %Defining Strain Increment Step Size de=0.000005; %Defining Parameters of the 1-element Spring Model %K1 - Stiffness of Spring 1 that rep a combination of Primary- %Secondary Bond Strength %E1max - Static Ultimate Strain for Spring 1 K1=input('Enter the Spring Stiffness : '); E1max=input('Enter the Static Ultimate Strain of the Spring : '); %Initialize Stress and Strain at t=0 s=0; e=0; ds=0; %Failure Mode: 0-Safe; 1-Fail Fail=0; i=1; while Fail==0 ds=(K1*e)+(K1*de)-(s); s=s+ds;

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e=e+de; if (e>E1max) Fail=1; end stress(i)=s; strain(i)=e; i=i+1; end %Plotting Results plot(strain,stress); grid; xlabel('Strain'); ylabel('Stress, MPa'); title('Stress-Strain curves for Linearly Elastic fibers at ANY Strain rate');

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