fell chapter 1

7/28/2019 Fell Chapter 1

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1 Introduction

1.1 Background

Fluid dynamics is a complex field that has challenged engineers for centuries, many of the

challenges steam from the restrictions of experimental work. However, it is essential for

many engineering applications to understand the complex flows associated with solid bodies

submersed in a fluid. Of particular interest in this study is the design of underwater vehicles

as they generate complex flow structures during manoeuvring operations that generate

hydrodynamics forces and complex wake fields. Knowledge of these flow structures leads to

the optimisation of the design of such vehicles, ensuring the installed power will be adequate

to overcome the hydrodynamic forces. In addition, understanding eddying flow structures

such as horse shoe vortices, tip vortices and cross flow vortices are essential to minimisecavitation and the acoustic signatures generated, while understanding the quality of flow

generated through propeller plane allows for optimisation of the propeller design.

Experimental work with scale models in test basins, wind tunnels, and rotating arm facilities

can be used to determine these critical flow characteristics. Model testing, however, can be

timely and expensive, with challenges to obtain visual representation of the vortices and

streamlines.

CFD is an alternative to model testing, and can help to gain insight into these critical fluid

characteristics of underwater vehicles. CFD uses the fundamental equations of fluid

dynamics (Naiver Stokes Equations) to obtain the hydrodynamic coefficients of the vehicles

and the associated flow characteristics.

Experimental work is associated with a degree of uncertainty due to the limitations of the

user and accuracy of the equipment being used; on the other hand most commercial CFD

codes are based on assumptions used to simplify the equations, and hence are also

associated with a degree of uncertainty. For this reason it is imperative that both methods

are employed to ensure validation between results.

An example of such a program is the Suboff submarine model constructed by the Defence

Advanced Research Projects Agency (DAPRA) in the USA that has been extensively tested

in the David Taylor Research Centre (DTRC) wind tunnel to validate CFD methods and

provide hydrodynamic and flow characteristics of such bodies. This model has since


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undergone further testing in wind tanks and tests basins in a number of other investigations

around the world.

1.2 Definition of the Problem

A joint project between the Australian Maritime College (AMC) and the Defence Science and

Technology Organisation (DSTO) conducted by Ackerman (2008) developed a CFD

simulation that investigated the hydrodynamic characteristics of the Suboff model. This

investigation involved the study of:

mesh generation; simulation set up; and the flow structure at static angles of incidence.

Ackermans study resulted in a Suboff model that generated results with close agreement tostatic experimental results but required further refinement to improve the capture of the flow

structures and the surface coefficients. In 2009, this study was extended, with particular

focus on:

validation of meshing techniques, particularly the appendages; development of a step by step guide to allow the techniques used in this tudy

to be applied to structed meshs developed in the future. simulation set up;

static angle of incidence; steady and unsteady simulations; validation through experimental fluid dynamics (EFD) in the AMC tow tank

using the Horizontal Planar Motion Mechanism (HPMM)

1.3 Research Methodology

This thesis is primarily aimed at validating various meshing techniques used to create the

CFD model.

An identical geometry as in Ackerman (2008) was used to ensure the comparison of results.A base mesh was generated and alternative meshing techniques for the appendages were

developed and trialled. The following information was obtained to compare various meshing

techniques:

gird independence; lift, drag and manoeuvring coefficients; and


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velocity contours.

The various mesh types were generated using ANSY ICEM CFD, and solved using the

ANSY-CFX solver. Experimental work conducted in the AMC tow tank and data from the

DARPA Suboff experiments where used to validate the CFD models.

1.4 Suboff Model

The model constructed by DAPRA consists of an axisymmetric hull, sail, and four stern

appendages (Figure 1-1). Groves et al (1989) gives a detailed description of the model,

which is abbreviated and represented below.

1.4.1 Axisymmetric Hull

The hull is composed of a forebody, parallel middle body and an afterbody giving a length

overall of 4.356 m and a maximum diameter of 0.508 m.

1.4.2 Sail (Fairwater)

The sail (referred to as Fairwater in Groves et al (1989)) has a length overall of 0.368 m and

a height of 0.460 m. Attached to the top of the sail is a cap with a 2:1 elliptical shape.

1.4.3 Stern Appendages

The stern appendages are NACA 0020 sections, with a length span of 0.154 m

.

Figure 1-1 SUBOFF model geometry (DSTO)

Sail

Hull

Stern

Appendages


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Parameter Value

Overall hull length (L oa ) 4.356 m

Maximum hull diameter (D max ) 0.508 m

Sail chord length (c sail ) 0.368 m

Sail span (s sail ) 0.206 m

Stern appendage chord length (c stern )

Stern appendage span (s stern )

0.154 m

0.172m

1.5 Literature Review

The use of underwater vehicles has increased significantly in recent times, with submarinesand unmanned vehicles being used in the naval, commercial, and private realms.

Autonomous Underwater Vehicles (AUV) and Remotely Operated Vehicles (ROV) are

becoming much more accessible to perform work that is impossible for divers to complete.

As the use of underwater vehicles expands, the demand for improved designs of such

vessels is also increasing. Gaining an understanding of the complex flow characteristics

associated with these vessels is crucial for the future developments in this field. CFD is a

method where the hydrodynamic coefficients can be determined to allow for accurate design

of the propulsion and manoeuvring systems of these vessels. In addition CFD can visually

represent the flow structures created by these vehicles allowing for the optimisation of the

propeller design and the minimisation of cavitation, vibration and the acoustic signatures

created by the vessel. However CFD is based on the fundamental equations of motion

where a form of averaging is employed to simplify the equations. This introduces a degree

of error requiring all CFD work to be validated by experimental work. McDonald, (1997)

explains that initially the strengths of both CFD and experimental work are needed to

supplement each other. However, once validated a physics based computational approach

can be used for various flow conditions, geometric configurations, and propulsor devices

outside the regime of available experimental data, with reasonable confidence that it isvalidated to the extent possible.

1.5.1 Experimental Work to date

During the late 1980s there was insufficient experimental data for the flow field over an

appended body, making CFD validation difficult for underwater vehicles, Groves et al (1989).

For this reason a DARPA project was conducted during 1988 and 1989 that developed the

Table 1-1 Suboff model dimensions (Ackerman, 2008)


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Suboff model to obtain data specifically for CFD validation. The experiments were

conducted at DTRC wind tunnel, where the model was supported in the wind tunnel by two

0015 NACA struts, thus minimising the effect on the flow, as illustrated in Figure 1-2.

Despite the measures taken to minimise the adverse effects on the flow there still exists a

degree of uncertainty associated with the experimental work that needs to be accounted for

when validating CFD results. Groves et al found the uncertainty of the velocity profiles was

approximately 2.2% due to the use of Hot-Film Velocity measurements while the uncertainty

associated with the pressure coefficients was 0.015.

Feldman (1987) performed straight line and rotating arm captive model tests at the

DTRC. Straight line tests were performed using a vertical and horizontal Planar Motion

Mechanism (PMM). Feldmans experiments were used to determine the hydrodynamic

coefficients over a submarine model at various angles of attack. Shown in Figure 1-3 is

a schematic of the PMM used by Feldman.

Figure 1-2 Experimental arrangement for Suboff testing at the DTRC (Groves et al)


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Feldman assumes that oscillatory tests are conducted to determine added mass and the

moment of inertia of the model. He presented numerous bias and precision errors both

mechanical and electrical, although he concluded that most of these errors are negligibleafter observations, testing, and analysis. Feldman found that there was numerous bias

and errors associated with the experiments, the most significant errors are as follows:

changes in gauge calibration; fabrication of the appendages and model; incorrect model test conditions, such as; speed, control surface angle and tilt

table angle; nonlinearity in gauge calibration;

irregularities in the rails in the towing basin; and interpretation of the hydrodynamic force and moment data.

Several of these errors were found when performing HPMM investigations on the DSTO

AUV Mullaya for this study, including and most importantly, the irregularities in the rails.

Figure 1-3 Schematic arrangement of DTMB PMM. Source: (Gertler, 1963)


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1.5.2 Mesh Generation

When performing CFD simulations, a mesh is generated that is associated to represent the

geometry of the simulation. It is at each node of this so called mesh that the fundamental

equations of fluid mechanics are calculated thus, it is essential to create a mesh that

accurately represents the intended geometry. There are multiple types of meshes that can

be created, most commonly used are hexahedron shaped elements and tetrahedron

elements, with both having advantages and disadvantages. Ackerman (2008) used entirely

hexahedron elements to generate a mesh to simulate the Suboff geometry, while Widjaja et

al (2007) used a hybrid mesh. The hybrid mesh utilises the accuracy and robustness of the

hexahedron shaped elements around the Suboff, while the tetrahedron shaped elements in

the farfield reduce the number elements used when compared to a completely structured

(hexahedron) mesh, which can suffer from poor aspect ratios in the farfield and wake

regions.

An initial understanding of the anticipated flow characteristics associated with the flow isessential. In regions of anticipated complex flow, the mesh density needs to be refined to

allow the simulation to entirely resolve the complex flows. Phillips et al (2007) found that the

predicted drag reduces with increasing mesh density. This is indicative of there being too

few elements in the stagnation region at the bow of the vessel and in the wake region aft of

the vehicle to accurately capture the pressure difference between the bow and stern of the

vessel.

Figure 1-4 Structured mesh in the near field and unstructured mesh in the far field

(Widjaja et al 2007)


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1.5.3 Grid Independence

Once a base mesh is developed, it is crucial to optimise the mesh to ensure accuracy whilst

minimising computational time. This can be done by systematically varying mesh density

and comparing to experimental data to determine the optimum mesh size. However when

altering the mesh size, the y+ value (see Section 2.4 Near wall modelling), must be kept

constant to ensure applicability of turbulence models (Bull, 1996). Sung (1996) explains that

grid independence is achieved when the flow variables change by 1% with a 50% increase

in mesh density.

1.5.4 Turbulence Models

Most commercial CFD code use RANS equations to calculate a solution (see Section 2.2

Flow types). Phillips et al ( 2007) explains that the RANS equations use additional terms

(Reynolds stresses) to approximate the velocity fluctuations in turbulent regions. However

when the flow transitions from turbulent to laminar flow, these additional terms create a

closure problem for the RANS equations thus making them unsolvable. Turbulence models

are used to relate the Reynolds stresses to overcome this closure problem. There are many

turbulence models used in commercial CFD packages, in this study only three models are

investigated, i.e.

1. k- ;

2. k- ; and

3. Shear Stress Transport (SST).

Each model is suited for various applications. Phillips et al ( 2007) explains that the k-

model is a commonly used turbulence model for engineering simulations due to its

robustness and application to a wide range of flows. However it is known to be poor at

locating the onset and extent of separation. An alternative approach, the Shear Stress

Transport (SST) model has been found to be better at predicting the separation likely to be

found at the aft end of underwater vehicles. Additionally Widjaja et al (2007) observed that

the k- SST model satisfactorily predicted the axial force coefficient, but performed poorly in

predicting the side forces, yaw and moment centre. The exact opposite behaviour was

observed in the standard k- model, where the error in axial flow was above 12% but theside force, yaw moment and yaw centre was superior to that of the k- SST model. Phillips

also observed that the SST model stabilizes faster and produces a smoother data set than

the k- model, as shown by the random oscillations of the k- data over the initial time steps

in Figure 1-5.


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1.5.5 Convergences

CFD solutions are solved iteratively, thus it is essential to ensure that the flow variables

converge to within a specified range. Sung (1996) explains that most CFD problems are

considered converged when the drop in magnitude of the root-mean-square of the

residuals is less than 1x10 -4. However, achieving convergence for flows with high Reynolds

number such as those used in the DARPA Suboff experiments can be difficult. The

Reynolds number of these flows are extremely large and the viscous regions resolve to y+

values of near one, this places sever demands on the numerical solution scheme in terms of

stability and accuracy (McDonald 1997), thus convergence may be defined at much larger

residual values. Widjaja et al (2007) found this occurred when conducting simulations for

14x10 6 Reynolds number simulations on the non appended Suboff model. Shown in Figure

1-6 is the continuity residual which does not get below 1x10 3. Additionally Widjaja et al

confirm that at high Reynolds numbers the simulation becomes unstable, as shown in Figure1-7, the hydrodynamic forces fluctuate throughout the solution.

Figure 1-5 Stabilisation of SST turbulence model (A. Phillips, 2007)


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1.5.6 Validation

Bull (1996) states that both experiments and CFD computations have degrees of

uncertainty, this gives rise to the need for validation of both the measurements and the

computations for such flows, in order to quantify the uncertainty levels. Validation must bedone by a variety of methods to ensure all hydrodynamic data and flow structures are

accurately represented. Bull (1996) recommends the following experimental data and

contours are used for validation:

non dimensional coefficients of drag, pressure and skin friction; boundary layer profiles of the axial velocity;

Figure 1-6 Convergence of continuity RMS residual does not get below 10 - ,

(Widjaja et al (2007))

Figure 1-7 Convergence history of hydrodynamic force and momentum

coefficients, Widjaja (et al)


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turbulent kinetic energy and; wake harmonics as shown in Figure 1-8

Of all the hydrodynamic coefficients required for validation, the coefficient of drag is most

stable, while the coefficient of friction is least stable. Thus, validation should begin with C d

and progress to C f as refinement of the simulation progresses.

1.6 Thesis summary

The findings in this study are briefly outlined in this section. They include: the fundamental

theory used in CFD code, mesh generation techniques, simulation conditions and an

explanation of the results. The experimental work performed is outlined and evaluated, and

conclusions are drawn with recommendations for future work made.

1.6.1 Chapter 2 - Fluid Modelling

An explanation of the theory used in this study, namely the derivations of the continuity andmomentum equations, and how these are used to develop Eulers, and Naiver-Stokes

equations (momentum). Laminar and turbulent flows are defined including a description of

the associated turbulent flow structures. Application of the Naiver Stokes equations to CFD

is then shown by the use of Reynolds stresses, turbulence models and near wall modelling.

Figure 1-8 Taylor wake contours of measured data (Bull, 1996)


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1.6.2 Chapter 3 - Topology and mesh generation

The advantages of a structured mesh compared to an unstructured mesh are briefly

explained. Various topology types are explained, culminating in a user guide to generate the

final topology developed in the study using ANSYS-ICEM CFD.

1.6.3 Chapter 4 - Boundary and solver conditionsThis chapter details the simulations conducted using ANSYS-CFX. The boundary and

solver conditions for initial, angles of attack, and unsteady simulations are explained.

1.6.4 Chapter 5 Results

Results for grid independence, the effects of y+ and turbulence model are explained. Final

result for various angles of attack and unsteady simulations are also discussed.

1.6.5 Chpater 6 - Experimental Work

Experimental work was based on the DSTO AUV Mullaya with an aim to validate the CFD

data of the Mullaya , an AUV model of similar hydrodynamic characteristics to the Suboff .

The meshing strategies of the Mullaya are identical to those used for the Suboff model, thus

lends itself to the validation of similar models of geometrical vehicles. Experimental work of

the fully appended Suboff model is scheduled for early 2010. Details of the aims,

procedures, and results are shown.

1.6.6 Chapter 7 - Conclusions and recommendations

Optimum meshing strategies are identified, the issues associated with the boundary and

solver conditions are summarised. Future modifications to the meshing structures and

experimental work are presented.

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