Viscous CFD Code Validation - STAR-CCM+mdx2.plm.automation.siemens.com/.../Presentation/3_CRMSolutions… · Viscous CFD Code Validation 19 March 2013 CD-adapco STAR-CCM+ Code Validation

Aerodynamic Simulation

using STAR-CCM+

Viscous CFD Code Validation

19 March 2013

CD-adapco STAR-CCM+

Code Validation Efforts

Kenneth E. Xiques

CRM Solutions

4092 Memorial Pkwy SW, Suite 200

Huntsville, AL 35803

Objectives

•Validate/Verify and Apply Cart3D, Loci/CHEM and STAR-CCM+ CFD codes

– Loci/CHEM is a research code developed by Mississippi State

– STAR-CCM+ is a Commercial code developed by CD-adapco

– Cart3D is a Cartesian Euler code developed by Nasa Ames

•Test geometry repair and grid generation capabilities

•Test range and power of Physics models

– Viscous modeling, Turbulence Models, Non-Newtonian Fluids

– Moving bodies (6 dof)

– Propulsion, Chemically Reacting Flows, Real Gas

•Determine level of required expertise for productivity

– Ease of use and practicality

•Test efficiency and accuracy in prediction of aerodynamics for complex geometries

Primary Questions

• Is prediction of aerodynamics over complex missile geometries using RANS CFD codes possible and practical in a production environment?

•What are the computational resource and manpower requirements to perform such analyses?

•Can Viscous CFD be performed efficiently and accurately within current resource constraints without relying on CFD specialists?

•Can STAR-CCM+ attack a broader range of problems than available with current in-house software?

•Would such analyses enhance the range and accuracy of CFD data produced at CRM for current customers?

Analysis Criteria

•Perform analysis in most general form without refinement based on CFD experience

– How much expertise does it require

•Determine the relative robustness and accuracy that can be achieved with relatively simple, ‘canned’ approaches

– Establish standard practices and procedures for problem types

•Limit time, computer resources and expertise required to go from CAD to database delivery of analysis within the required accuracy constraints.

CRM Linux Cluster

600 Intel Cores, 7TB Disk Space, Redhat RHEL O/S

• 130 Dell 1955 Blades • 2 Intel dual core Xeon processors • 4 cores per blade • 16 GB memory per blade

• 10 Dell M600 blades • 2 Intel quad core Xeon processors • 8 cores per blade • 16 GB memory per blade

• 7 TB disk space in Raid 5-0

• 2 x Dell PowerVault MD1000

• Diskless configuration • 3 x Dell 1950 file servers • RedHat Enterprise Linux

Metis Geometry

Metis Computational Grid Plane Section

METIS Grid Mid-Body Plane Section

METIS Tail Grid

METIS Surface Mesh

METIS Surface Mesh - Feature Curves

METIS(d0) Mach Contours M=0.7, 0 deg aoa (Rho, KOM)

Gear Mach Contours with Mesh M=0.26, 0 deg aoa (Rho, KOM)

Gear Mach Contours M=0.26, 0 deg aoa (RHO,Lam)

Gear Mach Contours with Mesh (body) M=0.26, 0 deg aoa (Rho, Lam)

Scud B Jet Vane Effectiveness study

SCUD B Missile Geometry

SCUD B Missile Jet Vanes Geometry

Scud Run Matrix

SCUD B Surface Mesh

SCUD B Surface Mesh (nozzle)

SCUD B Surface Mesh (tail)

SCUD B Mach Contours M=3 STAR-CCM+

SCUD B Mach Contours M=3

SCUD B Mach Contours M=3 45 deg. plane

SCUD B Gauge Press (clipped) M=3 STAR-CCM+

A53D02 Missile Geometry

Nose Surface Mesh

Tail Surface Mesh

Fin Surface Mesh

Nose Grid

Tail Grid

Mach Contours – Mach 0.9

Temp Contours – Mach 0.9

Mach Contours - Mach 3

Temp Contours - Mach 3

Mach Contours - Mach 10

CFD Code Comparison for Drag

Finner Geometry

Nose Mesh

Tail Grid

Forebody Grid

Mach Contours – Mach 0.9

Mach Contours – Mach 0.9

Temp Contours – Mach 0.9

Mach Contours – Mach 2.03

Finner CFD Drag Data

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 1 2 3 4 5 6 7 8 9 10

Dra

g C

oef

fici

en

t

Mach

Star_Total

Star_BSE

Star_Shear

LC_Total

Finner Experimental Drag Data

FM3 Geometry

FM3 Computational Grid

FM3 Surface Grid Nose

FM3 Surface Grid Canard

FM3 Surface Grid Slot

FM3 Surface Grid Tail

FM3 Surface Grid Tail

FM3(d0) Mach Contours with Mesh M=2.0, 0 deg aoa (Rho, KOM)

FM3(d0) Temp Contours M=1.6, 0 deg aoa (Rho, KOM)

FM3(d15) Mach 1.6 Contours 3 deg aoa (Rho, KOM)

FM3(d0) CFD Drag Data

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.5 1 1.5 2 2.5 3

Dra

g C

oef

fici

en

t

Mach

POLYS

TETS

LC

SHEAR P

SHEAR T

FM3(d15) CFD Drag Data

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.5 1 1.5 2 2.5 3

Dra

g C

oef

fici

en

t

Mach

POLYS

TETS

LC

SHEAR P

SHEAR T

Conclusions

•STAR-CCM+ code is superior for CAD geometry repair, surface remeshing and initiating analysis (all codes tested were robust and accurate)

– The more difficult the geometry the greater the time advantage

– Can be mastered quickly by non-expert

– Grids can be used to feed other codes

•Requires sizable computational resources for most problems of interest

•Seamless switch to different Physics models and BC’s

•Roe’s scheme is unstable for Mach > 3 flows but very accurate for Mach < 3

•AUSM+ scheme is very stable, robust and accurate

•Needs automated solution adaptation capability

•Superior solution monitoring and data reduction capabilities

• Important Physics models still under development

Future STAR-CCM+ Work

•Continue drag study

– Complete Missile run matrices using STAR-CCM+

– Use Solution Adaptation

– Compare with available data

•Perform Moving body analyses for V/V work (Finner and Manpad)

– Compare with Available data

•Perform Heat Transfer Analyses (Blunt Body and Base Heating)

– Compare to Holden Data

• Perform Jet Interaction Problem (Binary Gas)

• Perform Jet Interaction Problem (Reacting Gas)

• Perform Store Separation Analysis (6-DOF)

•Acoustics

– Bombay Cavity (Acoustics, Store Separation, Fluid Structure)

– Landing Gear (fixed and Moving Body)

– Cavity Launch (Acoustics, Ventilation)