motivating problem

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Jim Uschock Naval Surface Warfare Center Dahlgren Division (540) 653-4463 [email protected] Quantitative Methods in Defense & National Security “Understanding the Implications of Decoupling the Full Fluid Structure Interaction When Modeling Blast Waves Interacting with Structure” May 26, 2010

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Quantitative Methods in Defense & National Security “Understanding the Implications of Decoupling the Full Fluid Structure Interaction When Modeling Blast Waves Interacting with Structure” May 26, 2010. Motivating Problem. Example of a Blast-Structure Calculation using CTH. Time=400 m sec. - PowerPoint PPT Presentation

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Page 1: Motivating Problem

Jim Uschock

Naval Surface Warfare CenterDahlgren Division

(540) [email protected]

Quantitative Methods in Defense & National Security

“Understanding the Implications of Decoupling the Full Fluid Structure

Interaction When Modeling Blast Waves Interacting with Structure”

May 26, 2010

Page 2: Motivating Problem

2

Motivating Problem

Page 3: Motivating Problem

3

Time=0 sec Time=200 sec Time=400 sec

Top

Example of a Blast-Structure Calculation using CTH

• Eulerian code CTH well suited for detonation• Blast-structure interaction for this problem is 3D in its

behavior• Disparate length scales require Adaptive Mesh

Refinement (AMR)– Detonation, mm scale– Air shock, mm scale– Boat, 8 ft wide

• With half plane symmetry ~1000 cpu-hours

Page 4: Motivating Problem

4

Calculating Damage in LS-DYNA with CTH Input

• CTH is an Eulerian code suited for shock physics

• LS-Dyna is a Lagrangian code suited for structural response

• Timescale for the explosive loading is small relative to the timescale for structural response– i.e. The boat hull does not deform during

blast loading

• This allows a combined code approach– CTH + LS-Dyna

• Use boat test data for validation

CTH calculates blast in 3D

Export correct pressure time histories from CTH

LS-Dyna calculates hull deformation

Page 5: Motivating Problem

5

Issues with Approach

• Simulation is split up into 2 separate calculations which are run consecutively– This approach precludes mutual interaction (inaccurate)– This is inefficient from a parallelization standpoint– Requires loading histories on a rigid plate which is an engineering

approximation• What if the geometry was much more complicated?

– Not applicable for events involving long time behavior of structure (seconds)

• E.g. Sympathetic Detonation due to Kinetic Trauma

– Requires stand-alone routines to be written for specific application to allow CTH outputs to be read as LS-DYNA inputs time-consuming

• Simulation couples with commercial FEA solver– Scalability is limited by cost since licenses must be purchased for

each processor– Source code is not available to allow for seamless coupling

independent of specific application

Page 6: Motivating Problem

6

Some Technical Background

Page 7: Motivating Problem

7

The Finite Volume Method

0))(( xt uFu

Page 8: Motivating Problem

8

An Aside: “The Small Cell Problem”

Page 9: Motivating Problem

9

Approach

Page 10: Motivating Problem

10

Our Approach (in the large)

• Couple freely-available, scalable solvers using finite volume for the fluid (gas) and finite element for the solid structure focusing on the ability to handle complex geometry– Write an interface that passes information between the two solvers

as part of a single simulation– Use embedded boundary techniques in conjunction with state-of-the-

art numerical routines capable of dealing with the associated, so-called, “small cell problem”

Page 11: Motivating Problem

11

Approach

• Write 1D code to solve Euler equations with an ideal gas law

• Modify 1D code to allow for small cells (irregular grid) – Implement new theoretical algorithm to deal with

the small cell problem• Verify and validate standard code and newly

enhanced code through suite of linear and nonlinear test problems

• Apply code to fully coupled 1D fluid-structure interaction problem

Page 12: Motivating Problem

12

1D Code for Studying Complex Geometry

– Written in C, ~1000 lines of code– Compatible with CLAWPACK 1D input decks– Allows for variable small-cell capability– Solves 1D inviscid Euler equations:

2

2

2

1

1

0

0

0

up

E

puEuE

puu

u

xt

xt

xt

Page 13: Motivating Problem

13

1D Code for Studying Complex Geometry

• Fully second order accurate (space and time)– MUSCL-Hancock

• Use and in the Riemann solver

– TVD-preserving Runge-Kutta scheme

)(

)(****

*

QtLQQ

QtLQQ nn

)(

2

1 **1 QQQ nn

ini

Ri

ini

Li

iii

uu

uu

uu

2

12

1

)1(2

1)1(

2

12/12/1

)()(2

1

)()(2

1

Ri

Li

Ri

R

i

Ri

Li

Li

L

i

ufufx

tu

ufufx

tu

u

u

uR

i uL

i 1

Page 14: Motivating Problem

14

1D Code for Studying Complex Geometry

• Slope reconstruction routine allows for irregular grids– Follows recent work of Berger– Uses least squares solution

– Van Leer slope limiter is used on primitive variables

iiii uRxxxuxu )()()()( 1

1

ii

iii uu

uuR

iiL uDhh

huD

hh

hD

i

22

2

22

2

ii xxh 1

h

uuuD iii

1

with

Page 15: Motivating Problem

15

1D Code for Studying Complex Geometry

• HLLC Riemann Solver – Work of Toro, Spruce, and Speares– Modifies HLL (Harten, Lax, and Van Leer)

scheme by restoring missing contact and shear waves

– Approximation for the intercell numerical flux is obtained directly in this approach

• Shown to be effective in use with 1D inviscid Euler equations, for example

• Roe Solver

Page 16: Motivating Problem

16

(Post Processing) Cell Merging

• Developed cell merging technique that occurs after the Riemann solve but still is conservative

• Formulated and developed in 1D– Take a normal time step

– After Riemann Solve, merge small cell with a non-ghost neighbor in a volume-weighted way

– Perform irregular grid slope reconstruction on merged cell

– Determine correct state values at centers of small cell and neighbor cell based on the new slope calculated

• Successfully demonstrated when small cells are present

Page 17: Motivating Problem

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Verification of 1D Code

•Constant input stays constant (regular and small cell)

•Linear input stays linear (small cell)

Page 18: Motivating Problem

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Verification of 1D Code

)sin(2 x•Sinusoidal advection preserved (regular and small cell)

1u2p• 200 cells on [-π,π]

• Fixed dt=.0005; tfinal=0.5

Page 19: Motivating Problem

19

Verification of 1D Code

•Fully 2nd order accurate (regular grid)

Page 20: Motivating Problem

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Verification of 1D Code

• Sod shock tube problem verified (regular grid)

– 3000 cells

1;3 rrll pp

Page 21: Motivating Problem

21

Verification (Courant Friedrichs)

oio

oioioro PP

PPPP

6

8

Page 22: Motivating Problem

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Piston Problem

• Simplest fluid-structure interaction problem (1D)• Subramaniam Paper (Intl J Impact Engineering, 2009)

– Blast wave interacting with an elastic structure is analyzed in 1D within ALE framework

– The effect of considering 2-way coupling in FSI is compared to 1-way coupling FSI

– Builds on work of Blom (Comp. Meth. Appl. Mech. Engr., 1998)• Advocates monolithical FSI algorithm

Page 23: Motivating Problem

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Transient Dynamic Analysis of Elastic Structure

APtptfukum sssss 0

22.148m

kgms

3610397.1m

Nks

• Consider a plate 4.5m in length, 2.25m wide, and 2.5cm thick

• Assume fixed edges on the plate and pinned BCs

• Can find equivalent structural mass and stiffness of the fundamental mode of vibration per unit cross sectional area:

• Equation integrated with Newmark-Beta

Page 24: Motivating Problem

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Piston Problem

• Structural displacement predicted by ignoring FSI is larger than the corresponding displacement considering FSI. Pressure history is qualitatively different as well:

Page 25: Motivating Problem

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Example Piston Problem Plots

Pressure (1-way) Pressure (2-way)

Page 26: Motivating Problem

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Conclusions

• Through an entirely different approach, have qualitatively verified the work of Subramaniam, et al., in 1D:– Distinct differences in pressure and displacement

histories when comparing coupled and decoupled approaches

– 1D case clearly demonstrates that the decoupling approach may be ill-advised for this class of problems (thin-walled structures)

Page 27: Motivating Problem

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Questions?