Optimized Numerics for Missile Aero-Propulsive Flow Modeling on Massive Clustered Computational Resources

Award Information
Agency: Department of Defense
Branch: Army
Contract: W31P4Q-06-C-0188
Agency Tracking Number: A052-159-0943
Amount: $119,895.00
Phase: Phase I
Program: SBIR
Awards Year: 2006
Solicitation Year: 2005
Solicitation Topic Code: A05-159
Solicitation Number: 2005.2
Small Business Information
COMBUSTION RESEARCH & FLOW TECHNOLOGY, I
6210 Keller's Church Road, Pipersville, PA, 18947
DUNS: 929950012
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Donald Kenzakowski, Jr.
 Senior Research Scientist
 (215) 766-1520
 kenzakow@craft-tech.com
Business Contact
 Sanford Dash
Title: President & Chief Scientist
Phone: (215) 766-1520
Email: dash@craft-tech.com
Research Institution
N/A
Abstract
High-fidelity flowfield simulations of US Army interest for tactical and hypersonic missile aeropropulsive applications require replacement of simplified modeling approximations with more accurate but complex formulations. These improvements have incurred significant computational cost through use of higher-order numerics, dense computational meshes, and advanced turbulent and thermochemistry models with disparate time-scales that introduce additional non-linear transport equations and numerical stiffness issues. Software-based optimizations are needed to improve simulation throughput for system design parametric studies and evaluation purposes. Use of massively parallel computer clusters can extend simulation capability to 3D flowfields but alone cannot address the performance issue; innovative algorithm improvements are needed to complement available hardware resources. The opportunity presented seeks to significantly boost simulation output, without compromising accuracy, using automated dynamic load balancing techniques for parallel systems that compensate for non-uniform computational work distributions from varying physical processes (chemistry, particulate interactions) across the domain. Additionally, improved convergence algorithms are proposed to facilitate use of advanced thermochemistry and turbulence models in an efficient manner and to exploit differing time-stepping requirements through adaptive implicit algorithm selection.

* information listed above is at the time of submission.

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