taming openfoam for ship hydrodynamics applications · • one of the test problems for the 2010...

Taming OpenFOAM for Ship Hydrodynamics Applications

Sung-Eun Kim, Ph. D.

Computational Hydromechanics Division (Code 5700)

Naval Surface Warfare Center Carderock Division

Outline• Background

• Target Applications

• Issues

• Examples– Underwater bodies

– Surface ships

– Propulsors

• Concluding remarks

2

Background

• Complex geometry and complex physics (high Re TBL, vortices, multiphysics)

• Increasing emphasis/pressure on delivering engineering solutions to real-world problems in a timely manner.

• High-fidelity of CFD solutions commensurate with computational cost

• We are using several commercial CFD packages and in-house codes.

• Can an open source CFD software be tamed as a production code for industrial applications?

3

4

Target Applications

• Resistance and propulsion of underwater vehicles and surface ships

• Cavitation on hydrofoils and propulsors• Fluid structure interaction• Maneuvering• Seakeeping

Numerical Issues

• Spatial discretization– Gradients– Interpolation schemes– Advection schemes for interface capturing (volume fraction

transport)• Solution algorithms

– Implicit iterative time-advancement– Non-iterative fractional-step method for high-level simulation of

turbulence (e.g., LES)– Moving body problems - meshing strategy (single-grid, overset

grids, deforming)

n1

Spatial Accuracy on Unstructured Grids

• Drag predictions on an ellipsoidal body using structured and unstructured meshes– Very low profile (form) drag– Hybrid mesh with 500K cells

Evolution of a Leading Commercial CFD Code

CB GradNB Grad NB Grad

+ HORCGrad B + HORC+MUSCL

Heat Transfer in a Duct - Tet Mesh

• Tet vs. Hex

cell-based

node-based

node-based + HORC

Heat Transfer in a Duct - Prism + Tet

cell-based

node-based

node-based + HORC

Physical Modeling Issues

• Turbulence modeling– Wall boundary conditions for turbulent quantities (EVMs and

RSTMs)– Source term linearization– High-order RANS models (EARSM, DRSM)– Dynamic SGS models for LES

• Cavitation modeling– Bubble dynamics modeling – Mass transfer models

No. of Points: 841,438No. of Tets: 699,851 No. of Prisms: 1,380,128

y+ ≅ 1.0

Body 1 Grid Characteristics (Half Body)ONR Body-1 Results

Longitudinal Distribution of Pressure (Cp) and Skin Friction (Cf) CoefficientONR Body-1 Results

Boundary Layer ProfilesONR Body-1 Results

Series 66 – Drift Angle Study (ONR)

The negative experimental drift angles are believed to be less accurate as the strut was mounted on the side and the body was in the wake of the strutOpenFOAM with the SST turbulence model providing more accurate predictions than our traditional unstructured solver (Tenasi) on the same grids

SUBOFF Body• Bare hull and fully appended cases• Computations are underway with various meshing and

turbulence modeling strategies

6M cell Hexpress mesh near-wall resolving mesh (y+ ~ 1)

SUBOFF BodyHexpress Grid - Stern Appendages

SUBOFF Body - RANS Solutions(ReL = 1.2 x 107)

K-ω EARSM

SST k-ω

U contour at x/L =0.978

Measured Axial velocity contours at propeller plane

KVLCC - Double-Body Tanker

KVLCC - Nominal Wake Prediction(Kim, 2001)

Predicted axial velocity contours at the propeller plane

KVLCC2 – Double-Body Tanker Model(Kim et al., 2010, Gothenburg Workshop)

20

Hybrid unstructured mesh SnappyHexMesh

Contour of axial velocity at the propeller plane

Outline• Background

• Target Applications

• Issues

• Examples– Underwater bodies

– Surface ships

– Propulsors

• Concluding remarks

21

Issues with Surface Ships

• Advection scheme for volume fraction is critical for solution accuracy and stability

• A suite of advection schemes (CICSAM, HRIC, MHRIC, interGamma, InterGamma-M) for volume-fraction equation have been implemented and validated.

• Large time-step size for steady or quasi-steady applications

21-Jun-1122

Zalesak’s Rotating Disk

1

0.5

0

Contours of volume fraction after one revolution

Coarse mesh: 400 x 400

21-Jun-1123

DTMB 5415

• One of the test problems for the 2010 Gothenburg CFD Workshop on Ship Hydrodynamics (Kim et al, 2010)

• ReL = 1.2 x 107, Fr = 0.28• Computations done for fixed and free sinkage and trim • Two-phase RANS computations on systematically refined hexahedral

grids using combinations of – Advection schemes– Turbulence models

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DTMB 5415 – Fixed Sinkage and TrimMesh Dependency

y/L=0.082

Y=0.172

x/LPP

z/L PP

-0.25 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2-0.01

-0.005

0

0.005

0.01 meas.13 Million6 Million3 Million

x/LPP

z/L PP

-0.25 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2-0.01

-0.005

0

0.005

0.01 meas.13 Million6 Million3 Million

DTMB 5415 – Fixed Sinkage and Trim (UCR1)Impacts of Turbulence Models

y/L=0.082

Y=0.172

x/LPP

z/L PP

-0.25 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2-0.01

-0.005

0

0.005

0.01meas.SSTRKEHRW

x/LPP

z/L PP

-0.25 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2-0.01

-0.005

0

0.005

0.01meas.SSTRKEHRW

x/LPP

z/L PP

-0.25 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2-0.01

-0.005

0

0.005

0.01

EFD (Longo et al. 2007)6million-cell-SST-HRIC6million-cell-SST-MHRIC

x/L = 0.082

x/LPP

z/L PP

-0.25 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2-0.01

-0.005

0

0.005

0.01

EFD (Longo et al. 2007)6million-cell-SST-HRIC6million-cell-SST-MHRIC

x/L = 0.172

DTMB 5415 – Impacts of Convection Scheme

Parallel Scalability – DTMB 5415

28

Processors

Spee

d-U

p

64 128 192 256 320 384 448 512

64

128

192

256

320

384

448

512

IdealNavyFOAM

NavyFOAM Computational PerformanceParallel Scalability on Harold at ARLUsing Pure MPI for 13 Million Cells

SGI Altix ICE 820010,752 cores @2.8 GHz Intel Nehalem(8 CPUs on a node)32 TB Memory4X DDR Infiniband

All the results shown were run fully-dense;namely, one prcocess per CPU(e.g., 8 processes on a node)

DTMB 5415

Axial velocity contour at x/L = 0.935

Outline• Background

• Target Applications

• Issues

• Examples– Underwater bodies

– Surface ships

– Propulsors

• Concluding remarks

30

Continuum Approach• Locally homogeneous mixture

formulation (Kim and Brewton, 2008; Kim, 2009)– Phase compositions are represented

by volume-fraction.– Incompressible gas (vapor) & liquid

phases– Implicit time-advancement scheme– Pressure-based projection method

• Mass transfer models– Merkle– Kunz– Schnerr & Sauer

• Validations – Modified NACA-66 foil– Clark-Y hydrofoil– Unsteady sheet/cloud cavity on a

NACA-0015 hydrofoil– Propeller (P4381, P4383, P4990)– Waterjets (AxWJ1, AxWJ2)

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Effects of Cavitation Number(α = 8°, σ = 1.0)

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α = 8°, σ = 1.0 LES result on a 3.3M cell meshSchnerr and Sauer’s mass transfer model

NACA-0015 HydrofoilLift and Drag

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σ(Cavitation number)

CL CD0.5 1.0 1.5 2.0 2.50.0

0.2

0.4

0.6

0.8

1.0

0.00

0.05

0.10

0.15

CD(exp.)CL(exp.)RANS - CDRANS - CLDES - CDDES - CLLES - CDLES - CL

σ/2αfc

/U

1.0 2.0 3.0 4.0 5.0 6.0 7.00.0

0.2

0.4

0.6

0.8

1.0

1.2Measured (Obernach)Measured (SAFL - 7 ppm)Measured (SAFL - 13 ppm)Predicted (DES)Predicted (LES)

Mean lift & drag coefficients Shedding frequency

P4381- Thrust Breakdown at J = 0.889

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Thrust, ΚΤ Torque, ΚQ

σ= 0.6 σ= 1.0 σ= 1.5

ONR AxWJ-2 Thrust Breakdown

Unsteady RANS ComputationN = 2000 RPM, Q* = 0.76, σ = 0.362

movie from 36 in tunnel

ONR AxWJ-2 Cavitation

36

Computation, σ = 0.362

ONR AxWJ-2 Thrust Breakdown Prediction

Predicted using Wilcox’ k-w model on a 2.2M cell (very coarse) mesh for 360° domain

38

Concluding Remarks

• We have been evaluating OpenFOAM for years, and benchmarking it against other CFD codes.

• A number of projects have been successfully carried out using OpenFOAM at NSWCCD for naval applications.

• Language (C++) barrier and object-oriented programming (OOP) make the learning curve stiff.

• Not all implementations in OpenFOAM are verified and validated.

Thank you!