Best Practices for Aerospace Aerodynamics Peter Ewing Agenda - - PowerPoint PPT Presentation

Best Practices for Aerospace Aerodynamics

Peter Ewing

Scen enes es

Pre-processing Solver Settings Post-processing

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh Vo Volume Mesh sh Defi fining Fli ligh ght Ph Phys ysics cs Se Setting ng Up So Solvers rs Au Automated Repo porti ting ng Plotting ng Au Automated Data Extract ction

• n

Pre-processing

Agenda

Ge Geometry Or Origin/Import rt

Geometries ultimately conglomerate in Parts

– Laser scans, extracted mesh topology – External CAD modelers, e.g. CATIA, NX – STAR-CCM+ 3D-CAD – Mesh Operation Parts

Common Denominator: tessellated surfaces

– STL or surface meshes

• “dummy” or “flattened” surface meshes

– Discrete Mesh Operations

• Detached mesh operations are green

– 3D-CAD/CAD Parts

• Analytic representation, blue or solid grey

User should be aware of geometry quality

– Especially for “flattened” Parts!

STAR-CCM+ requires clean, closed geometry:

– To use Boolean operations – To generate a volume mesh

STAR-CCM+ Parts

Import rt Pr Prep ep Su Surface ce Vo Volume me

Aero surfaces & leading edges are complex swept geometries

– These features matter!

Hierarchy of geometry fidelity :

– STAR-CCM+ 3D-CAD – CAD-Clients – CAD Exchange – X_B /X_T then STP/STEP – DBS, STL, IGES

CAD geometry allows several benefits over flattened parts

– Project to CAD – CAD-based Mesh Operations – Feature aligned meshing – Parametric design changes

• 3D-CAD and CAD-Clients

– Persistent Part naming

CAD is Preferred

Direct Link

STAR STAR-CCM+ Bi-direc ectional ional li link nk Soli lidWo Works ks Parameter Trans ansfer er

Import rt Pr Prep ep Su Surface ce Vo Volume me

Pre-processing

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep

Split the body into multiple Part Surfaces:

– Inflow/Outflow/Freestream definitions – Allows tracking of physical convergence – Trailing Edge for custom controls

Rounded edges

Naming conventions enable filtering and efficient identification, e.g.:

– 00 Inlet, 00 Outlet, 00 Freestream, etc. – 01 Wing, 01 Body, 01 Tail, etc. – 02 Symmetry Plane – 03 Interface (Sliding or Overset)

External Aerodynamics Geometry Preparation

DPW4 W4 Geo eometry (up uppe per) r) 3D RA RAE28 2822 Airfoil l for 2D si simula ulation

• n

DPW4 W4 Geo eometry (lo lower) r)

Fil ilter selecti tion

• n box

box

Import rt Pr Prep ep Su Surface ce Vo Volume me

Atmospheric flight:

– Upstream boundary:

Typically velocity inlet in a round/bullet shape Distance is 10-20 characteristic lengths

– Outflow boundary:

Typically a outflow flat plane cut Distance is 20-40 characteristic lengths

Wind tunnel configurations should be matched:

– Duplicate the geometry – Inlet distances typically set as free stream * – Outlet distance should follow free stream distance – Side walls typically set to symmetry * * If inlet conditions are well measured, duplicate

Low-Speed Far-field Boundary Preparation

Velocity Inlet et Pressure e Ou Outf tflow

• w

Exam ample bu bull llet doma domain in

Import rt Pr Prep ep Su Surface ce Vo Volume me

Freestream settings:

– Circular domain will use “Freestream” boundary condition

Upstream position 20-30 characteristic length scales Downstream position 40-50 characteristic length scales

Wind tunnel sections can be difficult to reproduce

– Transonic wind tunnels typically have slatted configurations – Simulations may contain shock reflections to disrupt upstream flow – Unless specific configuration is well documented, run in Freestream

Transonic Far-field Boundary Preparation

Body dy Free eest strea eam m Bou

• undary

ry

Samp ample tran ansoni nic circ rcular doma domain in

Import rt Pr Prep ep Su Surface ce Vo Volume me

Upstream placed fairly close and aligned with shocks generated by the body

– The shock should not interact with the freestream boundary

Outlet boundaries can either be Pressure Outlet or Freestream

– Hypersonic cases – Outlet can be set to “Pressure” field function to extrapolate

Supersonic and Hypersonic Far-field Boundary Preparation

Pressure Ou Outlet et Free eest stream eam Body dy Axis or Symme mmetry ry

Exam ample of

• f hype

personi nic doma domain fo for r Ma Mach 12 12 sphe phere re

Import rt Pr Prep ep Su Surface ce Vo Volume me

What does it do?

– Enables fast turn-around of broken geometry – Standard use case is for unification of assemblies of “broken” (i.e. not clean and closed) Parts

How do I know if I should wrap?

– Inefficient control over the CAD or Parts are flattened – Extensive* Surface Repair work is required:

• Inefficient (or no) control of CAD workflow
• Many CAD based-errors (e.g. too many pieces) to fix

efficiently in CAD

• Too many tessellation errors to efficiently fix in Surface

Repair

– Simulation fidelity is independent of intricate details affected by Wrapper

Features worth investigating:

– Works well in the PBM structure

• Maintains Part Surface naming convention
• Operation can be “Detached” to create new Part

– Partial Wrapping

• Speeds up the wrapping process

– Project to CAD

Wrapping

Used by permission: Sikorsky / American Helicopter Society

Import rt Pr Prep ep Su Surface ce Vo Volume me

STAR-CCM+ Surface Repair Comments

What does it do?

– Checks triangulations for valid clean/closed geometry – Manipulate underlying triangulations (tessellations)

How do I know if I should Surface Repair?

– The underlying Part is not clean/closed manifold – There is no control of the CAD to fix within CAD

If a Part Requires Repair:

– Don’t panic!

• Undo/Forward-do buttons

– Surface Repair can repair the parts:

• Up-to-date guide flags remaining fixes
• Create new Part Surfaces where needed
• Create new Part Curves where needed

Keep in Mind:

– It’s like sewing up a bundle of triangles: Connect dots, zip edges

– Goal is to create a manifold, air-tight surface

Import rt Pr Prep ep Su Surface ce Vo Volume me

Pre-processing

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh

Automatic Surface Repair Model: ‘Off’ Surface Remesher Settings:

– Increase minimum face quality to 0.20

Surface mesher settings:

– Base Size to Characteristic Length/10, e.g.:

• Chord length/10
• Characteristic Body length/10

– Surface Curvature: 36 - 54 – Surface Growth Rate: 1.05 - 1.20

Custom Surface Controls:

– Edge proximity on bodies to 3 – Lifting Surfaces:

• Basic Curvature to 76
• Growth rate to 1.05 - 1.10
• Target Size: Chord/100

– Trailing Edges: Minimum Target Size to ¼ of t.e. thickness – Inlet/Outlet/Freestream/Symmetry Boundaries:

• Target Surface Size to be at least characteristic

length

Automated Surface Mesher Settings

Import rt Pr Prep ep Su Surface ce Vo Volume me

Defau efault set ettings gs

Curva vature=76 76 NACA NACA0010 010 Chord/100 00 Gr Growth = 1.05 05 Proxi

• ximity

ty

Pre-processing

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh Vo Volume Mesh sh

2D Axisy isymmetr tric c Hyp yperson sonic bi-conic conic

2D Automated Meshing (PBM):

– Requires an initial 3D body

• 2D section lies on z-axis
• Does not need to be CAD

– Applications:

• Airfoil analyses
• Test mesh settings
• Testing of physics settings
• Supersonic 2D/Axisymmetric

Directed Mesher (PBM):

– Ordered style grids – High quality grids for supersonic flows – Best practice topology for hypersonic cases – Requires an initial 3D CAD body – Workflow tip:

• Split patches in the CAD-Client or in 3D-CAD
• On Geometry transfer, choose “All CAD Edges” option
• Choose to “Initialize Patches by CAD Edge”
• Allows for macro automation

Quasi-2D Core Volume Mesh Models

NLF-0

• 0416

16 Import rt Pr Prep ep Su Surface ce Vo Volume me

Trimmer or Polyhedral are both acceptable topologies

– Refinement in flow regions of interest are key to capturing flow features in the simulation

Polyhedral mesh:

– Aerospace cases mesh in serial – Pseudo-random orientation of faces reduces numerical dissipation – Smooth growth away from bodies – Optimizer can increase mesh quality – Prefer to control mesh based solely on remeshed surface

• Volume controls to catch the hard spots

Trimmer mesh model:

– Massively parallel – Faster, requires less memory – Aligning the trimmer mesh model to the main flow directions can reduce numerical dissipation – Mesh refinement/coarsening in factors of 2

• Use of volume control to control location of transitions

Core Volume Mesh Models

Lockheed Martin Public Release: ORL201102002

Import rt Pr Prep ep Su Surface ce Vo Volume me

Gr Growt wth Rate Off ff

Polyhedral Mesher Settings

– Growth Rate: Can be ‘off’ or ‘on’

Reduces cell count between geometry gaps

– Optimization Cycles

Increase Optimization cycles to 1-4 Effective in aiding Adjoint case convergence

Polyhedral Controls

– If Volume Growth Rate ‘On’

Volume Growth Rate to 1.2 Maximum cell size to characteristic length

– Mesh Density

Leave at defaults

– If a volume control exists in the mesh

Volumetric Control Blending to 0.5

Polyhedral meshing for Aerospace

Gr Growt wth Rate On On Import rt Pr Prep ep Su Surface ce Vo Volume me

Trimmer Mesher Settings

Trimmer Mesh Model Settings

– Typically left at defaults – Mesh in parallel

Typical control settings

– Volume Growth Rate

Slow to Very Slow

– Maximum Cell Size to characteristic length – Maximum Core/Prism Transition Ratio

Anywhere between 2-5

Import rt Pr Prep ep Su Surface ce Vo Volume me

Settings:

– Stretching function: Hyperbolic Tangent – Stretching Mode: Wall Thickness – Minimum Thickness Percentage: 0.01 – Layer Reduction Percentage: 0.0

Make conformal prisms in all layers

– Near Core Layer Aspect Ratio: =<1.0

Typically set to 1.0 or 0.75

Requires two inputs:

– Wall Thickness – Prism Layer Total Height – Translation:

Wall Thickness = a “low y+ mesh” or “high y+ mesh” Prism Layer Total Height = Boundary Layer Thickness

Prism Layer Mesher Model

RAE28 E2822 Airfoil il HLP LPW4 W4 Import rt Pr Prep ep Su Surface ce Vo Volume me

High y+ mesh notes:

– Sub layer and buffer region is modelled by one grid cell

• Wall y+ value should be > 30
• Wall y+ value < 300.0

– Typically has 8-14 prism layers – Implicitly assumes that the boundary layer is turbulent and will try to reproduce the log layer behavior

Low y+ mesh notes:

– Attempt to integrate/resolve entire boundary layer

• Wall y+ value should be ~< 1

– Values << 1.0 will not improve results

• Should not be > 5.0

– Has at least 10 prisms in y+ < 30 region – Typically 24-32 prism layers – Flows that are not modelled with a transition model should not be taken as predictive transition modelling – Explicitly model the trip on tripped boundary layers

“High y+ mesh” vs. “Low y+ mesh”

Low Low y+: : Fir First gri rid po point nt High gh y+: : Fir First gri rid po point nt

5 10 15 20 25 1 10 100 U+ Y+ Viscous sublayer Buffer-layer Log-layer Defect-layer

Import rt Pr Prep ep Su Surface ce Vo Volume me

Knife-edges lead to cells with high skewness angles

– High skewness angles create numerical instabilities – Counter is to create refinements on the edge

Custom Surface Settings on Trailing Edges

– Create models with finite trailing edges – Use Prism Layer Thickness Reduction

Avoids prism layer collapse on trailing edges Avoids oddly shaped cells in the rear

Prism Layer Techniques for Trailing Edges

(or Hypersonic Leading Edges)

O-Grid, No Retract O-Grid, Retract TE Custom Settings

Import rt Pr Prep ep Su Surface ce Vo Volume me

Automated Mesh Refinement

STAR-CCM+ can perform automated mesh refinement :

– Table based refinement

Custom Field Function metric for refinement Tabulate cell size refinement metric

– JAVA macro-driven volumetric control

Conceptually, flow field contains arbitrary cells that contain refinement metrics Threshold Derived Parts are exported as STL files STL files can be wrapped to create volumetric control

– New Feature in 10.02 – Adjoint based mesh refinement

JAVA macro can drive adjoint-based mesh refinement

Blunt Nose*; Mach 6.8; AoA 20 Initial Remesh 1 Remesh 2 *Courtesy Lockheed Martin Missiles & Fire Control

Original Refined

AGARD RAE 2822 Adjoint Refinement Solution based refinement

Ph Physics cs So Solvers rs

Pre-processing Solver Settings

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh Vo Volume Mesh sh Defi fining Fli ligh ght Ph Phys ysics cs

RANS – Reynolds Averaged Navier Stokes

– Most common choice for external aerodynamics

• Robust, well studied
• Steady state simulations: 2D, Axisymmetric, 3D
• Obtains the average of all resolved flow features

– Extra equations add a turbulent viscosity to the dynamic viscosity in the Navier-Stokes Equations – − is the turbulence model of choice

• Enables use of − , − transition model
• Does not preclude the use of − and its variants

– “All y+” wall model is the preferred choice – Boundary conditions:

• Typically left as default, but can use measured values
• Decay of inflow turbulent quantities can be mitigated

by activating the Ambient Source Term (ASM)

– Do not use with the transition model

– Solver settings:

• Not uncommon to increase Turbulent Viscosity Limiter, e.g.:

1e8

Turbulence: RANS

NLF-0

• 0416

16 HLP LPW4 W4 Ph Physics cs So Solvers rs

URANS – Unsteady Reynolds Averaged Navier Stokes

– Run in 2D, Axisymmetric, 3D – Adds unsteady term to the RANS equations – Common choice for rotor performance

• Sliding mesh setup
• About 2 degrees per time step

– If nothing dynamically changes about the geometric configuration during the simulation, risks reverting to RANS

DES –Detached Eddy Simulation

– Legitimate in 3D simulations, always unsteady – Popular choice for performance simulations

• Not prohibitively more expensive than 3D URANS
• IDDES = Improved Delayed DES

– default mode – modern method

– Blend of RANS and Large Eddy Simulation

• RANS near-wall, LES everywhere else
• Far less turbulent viscosity in the LES regions

Unsteady Turbulence: URANS vs DES vs LES

TLG: DES ES Buffe uffeting ng ana analys ysis s 2012 2012 STAR Glob

• bal Confe
• nference Talk

lk Roto

• tor wake from
• m a ROBIN body

body

Ph Physics cs So Solvers rs

LES – Large Eddy Simulation

– Legitimate in 3D simulations, always unsteady – Not particularly popular choice in external aero

More expensive than RANS and DES

– High mesh counts required near walls

– Needed to properly resolve structures of transitioning flows

Laminar

– Navier Stokes Equations solved directly without any turbulence model – Low-speed to supersonic simulations will not likely use this – Hypersonic simulations that are not interested in boundary layer will choose in conjunction with a high y+ (>100) mesh

Turbulence: LES and Laminar

2012 2012 STAR Korean ean Confe

• nference: Sat

atish Kuma umar B. et et al. l. “Tr “Tran ansiti ition

• n flow

flow and and ae aero-acousti tic ana analys ysis of

• f NACA0018”

0018” ALM: LM: Bow sho hocks on

• n re-ent

entry ry of

• f the

the Crew Exploration

• n Veh

ehicle le

Ph Physics cs So Solvers rs

2D Simulation Enables:

– Fast testing for unknown physics phenomena

Shock position for grid refinement Solver settings

– Simulations for 3D axisymmetric shapes – RANS/URANS turbulence modelling

Transition location using − , − _ Onset of trailing edge stall

3D Simulation Enables:

– RANS, URANS, DES, LES – Complex geometry interactions – Stall Prediction

What can you get in a 2D vs. 3D simulation?

Ph Physics cs So Solvers rs

Key Idea: Simulating a continuously transient behavior in a discrete fashion

Unsteady Time Stepping

U( U(t) t) Time (t) t)

T/20 /20 is a a goo good sta tart rt

Ph Physics cs So Solvers rs

2015: 2015: STAR Glob

• bal : Ov

Overs rset with Zero Gap ap Demo emo

Pre-processing Solver Settings

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh Vo Volume Mesh sh Defi fining Fli ligh ght Ph Phys ysics cs Se Setting ng Up So Solvers rs

Physics Continuum Solver Choice

Segregated Solver

– SIMPLE – Continuity and momentum yield a pressure-correction equation – Mildly compressible flows, but not appropriate for shock capturing – Flow regimes:

• Incompressible
• Low speed
• High speed, subsonic; Mach < ~0.5

– Consider local flow Mach numbers!

– Lower memory requirements, faster than Coupled solver

Coupled Solver

– Continuity, momentum, energy are solved simultaneously – Equation of state yields pressure – Flow regimes:

Incompressible Low speed High speed, subsonic; Mach < ~0.5 All other flow speeds for Mach > ~0.5

– Designed for hyperbolic nature of equations and shocks

– Higher memory requirements

Low Speed: P weak function

• f ρ, T

High Speed: P strong function

• f ρ, T

Ph Physics cs So Solvers rs

If Using the Segregated Solver

– Simulations that use this solver should start with good initial conditions

• Constant velocity in the direction of the flow
• Smoothly ramping velocity from wall using field function
• Constant temperature set to flow conditions
• Turbulent quantities are typically default

– URFs are typically not ramped

• Rotor cases typically ramp or step RPM

– Unsteady simulation initialization

• Begin from steady state RANS solution
• Turn on Unsteady Solver

If Using the Coupled Solver

– Roe FDS – Initial condition:

• Constant velocity in direction of flow
• Constant temperature set to flow conditions

– CFL: 20-50 – Grid Sequencing Initialization ‘On’ – Expert Driver ‘On’

Solver Settings: Incompressible to Ma<0.5

Ph Physics cs So Solvers rs

Coupled Solver Suggested Settings:

– Transonic (0.5 < Ma < 1.0):

Roe FDS if no local Ma > 1.0 CFL from 5.0 to 50.0

– Supersonic (1.0 < Ma < 4.0):

AUSM+ CFL from 5.0 to 20.0, 20/Ma

– Grid Sequencing Initialization

Turn on

– Expert Driver to ‘On’ – If no Expert Driver:

Ramp CFL from 1 to 1000 Ratio of CFL Number : Explicit relaxation factor = 3:1

Solver Settings: Transonic to Supersonic

Ph Physics cs So Solvers rs

Solver Settings: Hypersonic (Ma > 4)

Implicit Coupled Solver Suggested Settings:

– Typical CFL ~ 1.0-5.0 – Grid Sequencing Initialization – Expert Driver

Ramp CFL from 1 to 1000

– CCA Turned On – If no Expert Driver:

Ramp CFL from 1 to 1000 Ratio of CFL Number : Explicit relaxation factor = 3:1

Physics Continuum Settings:

– AUSM+ – May choose gradient reconstruction value between 1.0 and 2.0

Sometimes an almost 2nd order will converge

Mach 16 Sho hock ck-sho hock ck interacti tion

• n on a cy

cylinder er Mach 11.3 Blun unt Bi Biconic ic Mach 6.77 77 blunt cone: NASA SA TN TN-D1606 606

Ph Physics cs So Solvers rs

GSI Input:

– Physics Continuum Initial Conditions

How it Works:

– Runs the Euler equations on successively refined series of grids, from coarse grid to finest (real) grid

Result:

– Field starts at near-flight conditions

Recommended Settings:

– Sweeps per grid level = 200 – Tolerance = 0.005

Notes

– No reason for special velocity initial conditions – Develops preliminary shock locations

Grid Sequencing Initialization (GSI)

Wrapped Rocket GSI Initial Condition After GSI 1000 Iterations

Ph Physics cs So Solvers rs

When:

– High Mach number aerodynamic cases

CCA Input:

– Updated Coupled Solver flow field

How it works:

– Solves an elliptic equation for pressure corrections – Updates the cell pressures (w/underrelaxation) – Corrects the face mass fluxes and cell velocities – Updates density, total enthalpy, etc. appropriately

Results:

– Can result in faster convergence for stiff problems

• Mixed high Mach and low Mach numbers
• Internal compressible flows
• Temperature dependent properties

Settings:

– URF typically set 0.1 - 0.3

Continuity Convergence Accelerator

With CCA Without CCA

“Continuity Convergence Acceleration of a Density-Based Coupled Algorithm,” Caraeni et al., AIAA Fluid Dynamics Conference, 24 - 27 June 2013, San Diego, CA Ph Physics cs So Solvers rs

Scen enes es

Pre-processing Solver Settings Post-processing

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh Vo Volume Mesh sh Defi fining Fli ligh ght Ph Phys ysics cs Se Setting ng Up So Solvers rs Au Automated Repo porti ting ng Plotting ng Au Automated Data Extract ction

• n

Interpreting the Residuals

Mission statement: Simulations should be as accurate as possible.

– Residual values are a global metric of convergence – Local convergence may get lost when only using residual values

Residuals are used as a metric to judge overall quality of the simulation Used in both steady and unsteady simulations Example Residual Plots:

St Steady ady Unsteady eady

Po Post st

Checking Convergence with Engineering Criteria

Both Steady and Unsteady Simulations Create Plots of Quantitative Data

– Skin Friction Coefficient – Mass imbalance (especially for high speed flows) – Lift – Drag – Moments

Plot versus inner iteration, make sure metrics asymptotically converge onto a value

– For steady simulations, asymptotic behavior – For unsteady simulations, asymptotic behavior within the prescribed time step’s iterations

Po Post st

Requires additional planning up front

– Testing CAD robustness – Post-processing change in data sets

Use JAVA to drive changes

Benefits:

– Automated sweeps

3D-CAD parameterization CAD-client bi-directional capability

– Fire-and-forget – Reduces burden on heavy scripting

Small pieces of JAVA can be inserted into process

– Rotating the coordinate systems

– Visualization of large data sets

Post-processing is collected in single tool Visualize multi-variable interactions

Optimate & External Aero

Po Post st

Common practice to post-/troubleshoot on special big-memory machines

– External aerodynamics cases can be more than 20M cells – Difficult to run multiple iterations for troubleshooting purposes

Download, identify mesh issues, remesh, re-submit to queue, crash, re-download, make rhetorical statement: “There’s got to be another way.”

STAR-CCM+ client-server architecture

– Data is post-processed by parallel cores – Visualization on workstation graphics

Benefits:

– Increased framerates – Volume rendering – Line Integral Convolutions

Post-Process Interactively on a Cluster

28.8M cell ll DPW4 model on 4 nodes @ 64 cores es Client locati tion

• n: Lo

Los Ang ngeles, CA CA Se Server locati tion: Detroit, MI MI

Po Post st

Scen enes es

Pre-processing Solver Settings Post-processing

Agenda

Ge Geometry Or Origin/Import rt Ge Geometry Pr Prep ep Su Surface Mesh sh Vo Volume Mesh sh Defi fining Fli ligh ght Ph Phys ysics cs Se Setting ng Up So Solvers rs Au Automated Repo porti ting ng Plotting ng Au Automated Data Extract ction

• n

Thank You Time for any questions