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HIGHLY ACCURATE SKIN FRICTION AND HEATING RATE PREDICTIONS USING NOVEL ADAPTIVE…

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
12349
Program Year/Program:
1990 / SBIR
Agency Tracking Number:
12349
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Computational Mechan
7800 Shoal Creek Austin, TX 78757 0102
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1990
Title: HIGHLY ACCURATE SKIN FRICTION AND HEATING RATE PREDICTIONS USING NOVEL ADAPTIVE TECHNIQUES
Agency / Branch: DOD / USAF
Contract: N/A
Award Amount: $49,968.00
 

Abstract:

ACCURATE AND EFFICIENT PREDICTION OF SKIN FICTION AND HEATING RATES FOR SUPERAND HYPERSONIC VEHICLES HAS LONG BEEN A GOAL OF COMPUTATIONAL FLUID DYNAMICS (CFD). THE USE OF STANDARD CFD METHODS TO RESOLVE THE NEAR-WALL BOUNDARY LAYER (WHICH IS ESSENTIAL FOR GOOD PRECITIONS OF AIRFOIL BEHAVIOR) USING A LARGE NUMBER OF GRID POINTS IS SELDOM FEASIBLE, OFTEN INACCURATE, AND IF DONE, ALWAYS REQUIRES EXCESSIVE COMPUTATIONAL POWER AND EXPENSE. CONSEQUENTLY, THE OBJECTIVE OF THIS SBIR PROJECT IS THE DEVELOPMENT OF INNOVATIVE COMPUTATIONAL PROCEDURES WHICH DO NOT SUFFER FROM THE PROBLEMS OF CONVENTIONAL FINITE DIFFERENCE CODES AND YET STILL PROVIDE HIGHLY ACCURATE PREDICTION OF SKIN FRICTION AND HEATING RATES FOR HYPERSONIC FLOWS. THIS WILL BE ACHIEVED USING HIGHER-ORDER POLYNOMIALS TO MODEL THE BOUNDARY-LAYER IN CONJUNCTION IWHT LOCAL GRID REFINEMENT. AUTOMATIC ADAPTIVE STRATEGIES THAT WILL EITHER REFINE THE GRID LOCALLY (H-ADAPTATION) OR ENRICH THE POLYNOMIAL BASIS (P-ADAPTATION) WILL BE EMPLOYED. THESE NOVEL ADAPTIVE STRATEGIES WILL BE APPLIED FOR THE FIRST TIME TO HYPERSONIC FLOWS ABOUT ARBITARILY-SHAPED VEHICLES USING A NEW PARABOLIC NAVIER-STOKE ALGORITH. THE FINAL PRODUCT WILL BE A UNIQUE AND POWERFUL SOFTWARE PACKAGE FOR MODELING THREE-DIMENSIONAL HYPERSONIC FLOWS. ???????????

Principal Investigator:

Dr Stephen R Kennon
5124670618

Business Contact:

Small Business Information at Submission:

Computational Mechanics Co Inc
3701 N Lamar - Ste 201 Austin, TX 78705

EIN/Tax ID:
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No