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Aspects of Industrial Flow Prediction Using LES in STAR-CCM+

A D Gosman

CD-adapco

Japan STAR Conference 2012, Yokohama

INTRODUCTION

1. Motivation for and nature of LES

2. LES and hybrid variants (in STAR-CCM+)

3. Quality assessment criteria

4. Best practices

5. Validation

6. Industrial applications

LES AND ITS ADVANTAGES

turbulent flows unsteady and have wide range time & length scales

RANS models effects of all scales, and enables calculation of mean motion at low cost, but with loss of accuracy

DNS can capture all scales, but is very expensive

LES models only small scales (

LES/DES DEVELOPMENT IN STAR-CCM+

COLLABORATIONS WITH LEADING RESEARCHERS

1. University of Manchester: Prof D Laurence

2. Penn State University: Prof D Haworth

3. Cornell University: Prof. S Pope

4. Iowa State U.: Prof P Durbin

5. TU Darmstadt: Prof. Janicka

6. University Modena: Prof. S Fontanesi

PARTICIPATION IN EU PROJECTS (ATAAC, WALLTURB, ADVANTAGE)

JOINT PROJECTS WITH INDUSTRIAL PARTNERS

BASIC EQUATIONS

Navier-Stokes Equations

Filtered Equations

Eddy viscosity modelling for subgrid stresses,

LES Equations

SUBGRID MODEL OPTIONS IN STAR-CCM+ - I

1. SMAGORINSKY

Eddy viscosity

, strain rate tensor

length scale

empirical coefficient recommended values are: 0.1, for channel flows (default setting in STAR-CCM+)

0.18, for free shear flows

model requires modification for wall-bounded flows

Sij =1

2

uix j

+u j

x i

Cs 0.07 - 0.18;

SUBGRID MODEL OPTIONS IN STAR-CCM+: - II

2. WALE

Sw gives correct asymptotic behaviour of eddy viscosity near wall, i.e

However modifications may still be required to predict near-wall flow.

Length scale

SUBGRID MODEL OPTIONS IN STAR-CCM+: III

3. DYNAMIC SMAGORINSKY (coming in V8.02)

apply second filter c2 > c : typically c2 = 2c assume small resolved scales and subgrid scales self-similar assume associated stress tensors can be represented by same Smagorinsky expression, i.e.:

Requires evaluation on larger stencil, difficult on unstructured meshes Cs non-smooth, averaging and limiting necessary Requires no modifications for wall-bounded flows.

Thus Cs locally evaluated from:

subgrid:

resolved:

Cs=

NEAR-WALL MODELLING: I- REQUIREMENT

Special requirements for wall-bounded flows because: - boundary layers contain small-scale vortex

structures

- proper resolution requires DNS-type

grids, refinement in all directions; so very

expensive.

- also requires correct near-wall behaviour of subgrid

model:

NEAR-WALL MODELLING II NATURE

Modelling practices used for near-wall region, first node in log-law layer

ensure subgrid viscosity model gives - some models already have this property

ensure length scale bounded by y in log-law region - a few models already have this property

obtain wall shear stress and turbulent viscosity at first mesh point from log-law based wall functions

produce wall-normal mesh distribution as for RANS, ideally with aspect ratio limits as for LES

Additional requirements for first node in buffer layer or laminar sublayer

(not advised additional meshing and modelling requirements)

NEAR-WALL MODELLING III IMPLEMENTATIONS

1. SMAGORINGSKY

introduce near-wall length scale limiter and damping factor

y = wall-normal distance

evaluate wall shear stress w and dynamic viscosity t from Reichart law

2. WALE

no modifications required, provided first node in log-layer

3. DYNAMIC SMAGORINSKY

evaluate wall shear stress w and dynamic viscosity t from Reichart law

length-scale limiter

HYBRID DES MODELLING I INTRODUCTION

Hybrid non-zonal model: - tends to LES in resolved flow

- tends to URANS in unresolved

Automatic selection of length scale according to grid:turbulence length scale

ratio

Preferable to limit URANS to near-wall region

Several variants: - DES, DDES, IDDES

Two URANS variants: k- SST Spalart-Almaras

HYBRID DES MODELLING II EXAMPLE

SPALART-ALMARAS DES MODEL

one-equation model: both high-Re and low-Re versions

tends to Smagorinsky-type LES model when CDES/d < 1

d = wall normal distance, 1 at high Re

n =n tfn1

dissipation rate depends on controlling turbulent length scale

d

GENERAL NUMERICAL ASPECTS

Second order implicit time differencing Both CD and Bounded CD Non-reflecting boundary conditions Synthetic turbulence for inflow BC

STAR-CCM+ solver has specific features for LES/DES simulations

second order implicit time differencing blended centered spatial differencing (BCD - alternative to CD for low-quality meshes) for LES momentum

blended second order/BCD differencing for DES non-reflecting boundary conditions synthetic turbulence inflow condition layered prismatic near-wall mesh

QUALITY ASSESSMENT CRITERIA FOR LES

1. A-priori ratio integral scale/mesh size = lint /

lint = Cm0.75k3 / 2 /e use RANS estimate

want ratio < 0.5 accuracy depends on RANS solution

2. Fraction resolved kinetic energy kres/ktot

want ratio > 0.8

kres 1

2u'1

2 u'22 u'3

2 ; ui' u i u i; ktot kres ksgs

3. Ratio LES predicted turbulence scale/mesh size

obtain length scale from energy spectrum

4. Ratio turbulent: laminar viscosity

ideally close to unity, minimizes modelling error contribution

5. Other, e.g. Index of Resolution Quality

LES BEST PRACTICES

1. Generate RANS solution first and use:

- integral length scale distribution as guide to construct LES mesh.

- as initial conditions for LES

- for aeroacoustics, can also estimate frequency resolution distribution

2. Discretisation practices:

- 2nd order time,

- CD or BCD momentum

- second order scalars

3. Ensure proper boundary conditions, particularly at

- inflow: realistic turbulent simulation using SEM

- free boundaries and outflow: non-reflecting

4. Set time step to maintain Courant number Co = udt/dx 0.1- 0.5 5. Run simulation for sufficient time to:

- eliminate initial condition effects,

- get statistically representative results (e.g. true time/ensemble average)

Additional more stringent requirements for aeroacoustics

VALIDATION: I HOMOGENEOUS TURBULENCE DECAY

Comparison with DNS predictions of Wray

Wray, A. 1998 Decaying isotropic turbulence. In AGARD Advisory Rep. 345

VALIDATION: II BACKWARDS-FACING STEP

Comparison with measurements of Kasagi and Matsunaga

Kasagi, N., and Matsunaga, A., "Three-Dimensional Particle-Tracking Velocimetry Measurementof Turbulence

Statistics and Energy Budget in a Backward-Facing Step Flow," Int. J. Heat & Fluid Flow, Vol. 16, No. 6, (1995).

VALIDATION: III - T JUNCTION

S.T. Jayaraju, E.M.J. Komen: Nuclear Research and Consultancy Group (NRG), Petten, The Netherlands

LES of mixing of streams of different temperature at T junction

Comparison with velocity and temperature measurements

T JUNCTION (contd)

Mean, RMS velocities at 2.6D

Mean, RMS velocities at 1.6D

Wall temperatures

INDUSTRIAL APPLICATION: RANGE

Aerospace

wing transition, high lift devices landing gear aeroacoustics jet noise Automobile/truck

full vehicle aerodynamics aeroacoustics mirror/window, sunroof HVAC fan, ducts, nozzles turbocharger Combustion

gas turbine reciprocating engine fires building, tunnel, pool Nuclear

steam line/SRVs, T-junctions rods, spacers, turbulators, vibration Other

wind turbine, smoke/hazard release

AIRFOIL TURBULENT TRANSITION AND AEROACOUSTICS

Wall-resolved LES of flow over airfoil at 6o angle of attack

Comparison with surface pressure and noise measurements

Relevant to wings, fans, turbines.

Surface pressure

SPL spectrum

AEROACOUSTICS: AIRCRAFT LANDING GEAR

DES of aircraft forward landing gear Comparison with fluctuating surface pressure measurements

SPL

VEHICLE EXTERNAL AERODYNAMICS: DES SIMULATIONS OF TRUCK AND SUV

Effect of yaw angle on drag coefficient of

truck

Effect of underbody modifications

on drag coefficient of SUV

VEHICLE AEROACOUSTICS AUTOMOBILE WING MIRROR

STAR

Meas

DES of wing mirror flow Comparison with fluctuating pressure at downstream points

Deviation from measurement at estimated cut-off frequency

COMBUSTION: SANDIA FLAME D VALIDATION

LES of Sandia D turbulent diffusion flame Smagorinsky, PPDF combustion model 4.1M cell mesh

SANDIA FLAME D (CONTD)

Mean axial velocity RMS axial velocity

Mean mixture fraction RMS mixture fraction

SUMMARY

1. STAR-CCM+ has an extensive capability for performing LES and DES

2. The methodology has been validated for a range of industrially-relevant

cases

3. Numerous industrial applications have been made in diverse areas

including aerodynamics, thermal analysis, aeroacoustics and combustion.

4. The methodology is being improved and extended, with the help of

collaborations with leading research institutes.