Fast Self-Adaptive Algorithms for Generating Hardbody Thermal Histories

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,998.00
Award Year:
2011
Program:
STTR
Phase:
Phase I
Contract:
HQ0147-11-C-7665
Agency Tracking Number:
B10B-003-0024
Solicitation Year:
2010
Solicitation Topic Code:
MDA10-T003
Solicitation Number:
2010.B
Small Business Information
Stellar Science Ltd Co
6565 Americas Parkway NE, Suite 725, Albuquerque, NM, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
092174635
Principal Investigator:
D. Stafford
Senior Resarch Physicist
(877) 763-8268
shanedodsbir@stellarscience.com
Business Contact:
Conrad Poelman
Contracting Officer
(877) 763-8268
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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