testing of openfoam cfd code for plane · pdf filecfd'11, 21-23 june 2011, trondheim...

CFD'11, 21-23 June 2011, Trondheim NORWAY

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TESTING OF OPENFOAM CFD CODE FOR PLANE TURBULENT BLUFF BODY FLOWS WITHIN CONVENTIONAL URANS APPROACH

Dmitry LysenkoIvar ErtesvågDepartment of Energy and Process Engineering, NTNU, Trondheim

Kjell RianComputational Industry Technologies AS, Trondheim


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Outline

• Motivation

• Numerical method

• High performance computing

• Turbulent bluff body flows modeling & validation– Modeling & validation

– Laminar and turbulent flows over a circular cylinder

– Turbulent bluff-body (triangular rod) flows in a channel

– Turbulent supersonic flow over a plane wedge-plate model

• Summary


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Motivation (I)

• High efficient compressible solver for turbulent reacting flows modeling based on the OpenFOAMtoolbox:

– Compressible RANS/URANS

– Compressible LES

– Reacting LES


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Motivation (II)

• Why OpenFOAM?

+ Open Source (GPL)

+ High fidelity C++ library

+ Geometrical flexibility (unstructured grids/data structures)

+ Capability (more important than speed)

+ Multiphysics (chemical reactions, solid particles … )

+ Scalability (increased resolution and compute speed)

+ R&D (new models development and incorporate more physics)

± Wide list of solvers options/settings …

– Certification

– Documentation (and validation/verification)

– Default values

– Pre/Post utilities Open Source but…

• More popular and popular in CFD world-wide community

+ IOSCFD conference

+ Annular OF workshop


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Numerical Method

&

HighPerformance

Computing


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Numerical method• Turbulence simulation approach

• URANS based on modified k-ε model of Launder and Sharma 1974

• Low-Reynolds-number formulation (Y+~1)

• Spatial discretization• FVM based on PISO algorithm (rhoPisoFOAM)

• 2nd order NVD scheme for viscous terms

• 4th order for inviscid terms

• Temporal discretization• 2nd order implicit backward Euler method (BDF2)

• Dynamic adjustable time stepping (CFL<1)

• Linear algebra and accuracy• ICCG (1x10-7)

• Thermodynamics• Ideal gas

• Const for viscosity and other properties

• Boundary conditions• Fixed profiles for inlet

• NRBC for outlet

• Isothermal non-slip for walls


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High performance computing (I)• Some observations1

• CPU clockrates not increasing– Heat generation ~ Clockrate3

– Practical limit: 3-6 Ghz (ITL, AMD, IBM)

• CPU increase by orders of magnitude only via massive parallelism

• MPI communication overheads limit domain size– Fast solvers: O (100Kpts)

– Disparity CPU/Rest increasing ->Number will not decrease

– Lower limit

• Almost perfect scaling once: Npts > 0.1M CPU– Cut-off number depends on MPI/RAM speed ratio

– Time for 1 Timestep with Npts = 0.1M: 0.75-7.50 sec

– Will not change significantly

• LES/DES/DNS runs will take a long time – Re=106-107

―> 107 Timesteps @ 1 sec/step = 2777 hrs = 115 days

1 R. Löhner. Increasing the number of cores for Industrial / Legacy codes: approaches, implementation and timings //

23rd International Conference on Parallel Computational Fluid Dynamics 2011. May 16-20, 2011, Barcelona, Spain.


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High performance computing (II)

• Consequences– Execution time > T(Limit)

• Time/Step/Pt fixed if processor speed not increasing

– Number of useful MPI nodes < N(Limit)

• Problem size/100Kpts

– Corollary: LES/DNS runs will remain expensive

• Large number of grid points (>109)

• Large number of time steps (>105)

– RANS Grids Relevant for Another ~25 Years

• Geometry (Good Body-Fitted Grids)

– Zalesak’s uncertainty principle holds

• Compute speed * Results < Z


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High performance computing (III)

• Know the limits of your problem/application

– Useful parallelism limited

– Multiphysics -> many load imbalances possible (chemical reactions, particles and fluids and more … )

– Over-simplification can be very costly

• STALLO HPC facility


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High performance computing (IV)

• OpenFOAM strong scalability study at STALLO HPC facility

Comparison of the strong scalability for 3D laminar

lid-driven cavity flow with different grid’s sizes of

150×150×150 (2), 200×200×200 (3) and

250×250×250 (4) with an ideal case (1) and ANSYS

FLUENT data (5-7) taken from http://www.ansys.com/Support/Platfo

rm+Support/Benchmarks+Overview.

Note: All OpenFOAM data include I/O

operations.

In detail: D. Lysenko, I. Ertesvåg & K. Rian.

Turbulent separated flows modeling using

OpenFOAM and ANSYS FLUENT technologies in

HPC environment // 23rd International Conference

on Parallel Computational Fluid Dynamics 2011.

May 16-20, 2011, Barcelona, Spain.


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Turbulent

Bluff-BodyFlows

Modeling&

Validation


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Modeling & Validation• Solvers

� Compressible formulation

� RhoPisoFoam // OpenFOAM (v.1.7.1)

� Pressure-based // ANSYS FLUENT (supplementary)

• Turbulence closure� K-ε model of Launder and Sharma (1974)

� K-ε Realizable model of Shih (1975)

� Low-Reynolds-number formulation for all cases (Y+ ~1)

• Grids � Unstructured viscous

� Structured viscous and polar O-type

� Grid convergence study (for most cases)

• Test cases� Laminar (Re=140) and Turbulent (Re=3900) compressible (M=0.2) flows over a

circular cylinder

� Turbulent (Re=17500 & Re=45000) bluff-body (a triangular cylinder) weak compressible (M~0.05) flows in a channel

� Turbulent supersonic (Re=5x106 & M=2) over a plane wedge-plate model

• Side-by-side comparison of the numerical and lab test data


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Laminar compressible (Re=140 and M=0.2) flow over a circular cylinder

Integral Parameters

Description of the computational

grids: curvilinear O-type

orthogonal (a), unstructured

triangular (b) and unstructured

triangular with dynamic

adaptation (c).

Time evolution of the lift (a) and drag (b) coefficients and comparison of time averaged

pressure coefficient distribution over the cylinder’s base (c): 1-3 – current numerical

results (1 – compressible flow, O-type mesh, 2,3 – incompressible flow, O-type and

unstructured meshes, respectively); 4 – Inoue and Hatakeyama (2002); 5,6 – Grove et

al. (1964).The contours (d) of instantaneous radiated density gradient field.

a b

c


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Turbulent compressible flow over a circular cylinder at Re=3900 and M=0.2

Integral Parameters

Normalized mean x-velocity in the wake centerline. Exp: 3 –

Lourenco and Shih, (1993), 4 – Ong and Wallace, (1996), 5,6 –

PIV and HWA by Parnaudeau et al. (2008). Present calculations:

1 – OpenFOAM, 2 – FLUENT.

Normalized mean x-velocity variance in the wake centerline.

Exp: 5,6 – PIV and HWA by Parnaudeau et al. (2008). Present

calculations: 1 – OpenFOAM, 2 – FLUENT.


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Turbulent compressible (Re=17500 and M=0.03) bluff-body flow in a channel (Exp by Fujii 1978 and 1981)

Mean Cp

distribution (a) and

normalized

turbulence kinetic

energy (b) in the

wake centerline; 1

– Sullerey (1975),

2 – Fujii

(1978,1981); 3,4 –

OpenFOAM.

A general view of the experimental test rig (a) taken from

Fujii (1978), computational domain (b) and the fragments

of the designed grids (c-d) at the vicinity of the bluff-body.

Time-averaged recirculation zone (Exp – the upper

side and numerical results – the down side).

Integral Parameters


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Turbulent compressible (Re=45000 and M=0.05) bluff-body flow in a channel (Exp by Sjunnesson 1991// Volvo test rig)

The sketch of the Volvo test rig (a) taken from Sjunnesson

(1991) and the general view of the computational domain (b).

Results comparison of the measured (1) time-averaged normalized x-

velocity (a) and turbulence kinetic energy (b) profiles in five cross

sections with x-coordinates of -2.5, 0.375, 1.525, 3.75 and 9.4 against

numerical predictions: Open-FOAM (2) and FLUENT (3). 1 – Exp

by Sjunnesson (1991).

Integral Parameters


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Near wake zone downstream the bluff-body visualization: (a) –

PIF method, (b) – numerical results.

Turbulent supersonic (Re=5x106 and M=2) flow over a 2D wedge-plate model (Exp by Scarano & van Oudheusden2003, 2005)

The sketch of a wind tunnel (TST-27), Delft University of

Technology from Humble, Scarano and van Oudheusden (2005).

Flow visualization

and flow features:

Front shock (1);

Shoulder (2) and

base (3) expansion

fans; Shear layer

(4); Recompression

waves (5).

Integral Parameters

a

b


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Verification test matrix & numerical method accuracy

Note: B – aspect/blockage ratio; B = D/H


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Summary

• The strong scalability study for OpenFOAM demonstrated

the modest parallel efficiency of 50-60% for working

problems sizes with 256-512 CPU/Cores

• RhoPisoFOAM was validated against several plane

turbulent separated bluff-body flows

• Numerical results shown consistency between OpenFOAM

and ANSYS FLUENT and lab test data

• The demonstrated solvers accuracy was ~ ±20% for main

integral (and local) flow parameters


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Acknowledgements

• This work was conducted as a

part of the CenBio Center for

environmentally-friendly energy

• We are very appreciated to the

Norwegian Meta center for

Computational Science (NOTUR)

for providing the uninterrupted

HPC computational resources and

the useful technical support

testing of openfoam cfd code for plane · pdf filecfd'11, 21-23 june 2011, trondheim...

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