Fast Self-Adaptive Algorithms for Generating Hardbody Thermal Histories

Award Information
Agency:
Department of Defense
Amount:
$99,998.00
Program:
STTR
Contract:
HQ0147-11-C-7665
Solitcitation Year:
2010
Solicitation Number:
2010.B
Branch:
Missile Defense Agency
Award Year:
2011
Phase:
Phase I
Agency Tracking Number:
B10B-003-0024
Solicitation Topic Code:
MDA10-T003
Small Business Information
Stellar Science Ltd Co
6565 Americas Parkway NE, Suite 725, Albuquerque, NM, -
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
092174635
Principal Investigator
 D. Stafford
 Senior Resarch Physicist
 (877) 763-8268
 shanedodsbir@stellarscience.com
Business Contact
 Conrad Poelman
Title: Contracting Officer
Phone: (877) 763-8268
Email: cpdodsbir@stellarscience.com
Research Institution
 University of New Mexico
 Professor J Kniss
 Department of Computer Science
Mail stop: MSC01 1130
Albuquerque, NM, 87106-
 (505) 277-2967
 Nonprofit college or university
Abstract
To reduce the cost of new hardware development, the Missile Defense Agency (MDA) is developing fast new computational tools that enable in-the-loop hardware testing. The MDA and contractors have developed high-fidelity scene modeling tools such as the Fast Line-of-sight Imagery for Target and Exhaust-plume Signatures (FLITES) to test optical signature trackers. Currently, these high-speed tools are not capable of computing thermal histories for hardbody targets, an important requirement for infra-red signature prediction. Stellar Science and the University of New Mexico (UNM) will leverage their extensive expertise in thermal modeling, synthetic image generation, software engineering, and multi-processing to provide a method for generating hardbody thermal histories in real time. The innovative self-adaptive algorithm will enable engineers with workstations, specialized graphics processing units (GPUs), or clusters to use the same validated code base across computing platforms by automatically selecting the best optimizations for the particular architecture. The algorithm will then adjust the fidelity of the simulation to meet the real-time requirement. Within Phase I, we will implement a prototype of the self-adaptation and a prototype API that can be used to begin integration of the real-time thermal solver into scene-modeling tools.

* information listed above is at the time of submission.

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