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3-D Modeling of Rocket Motor Plumes

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: FA9300-04-C-0044
Agency Tracking Number: 031-1001
Amount: $1,848,850.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: MDA03-061
Solicitation Number: 2003.1
Timeline
Solicitation Year: 2003
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-09-28
Award End Date (Contract End Date): 2009-06-30
Small Business Information
6210 Keller's Church Road
Pipersville, PA 18947
United States
DUNS: 929950012
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Neeraj Sinh
 Vice President & Technica
 (215) 766-1520
 sinha@craft-tech.com
Business Contact
 Neeraj Sinha
Title: Vice President & Technica
Phone: (215) 766-1520
Email: sinha@craft-tech.com
Research Institution
N/A
Abstract

Characteristics of missile plume signature emissions have a great potential to enhance defensive capabilities in a number of important areas related to early (boost-phase) detection and identification of the missile system/rocket motor. Missile defense technologies where plume modeling plays a significant role include: early warning launch detection (ELDT), post launch warning detection; missile typing algorithms; discrimination; and, background clutter discrimination. The goal of this Phase II effort is the development of a fast-running, engineering plume flowfield model, RPFM-3D, for providing 3D Visible/UV-LWIR/RCS/RF signatures of "real-world" threat missiles with complex features, e.g. gas generators, jet steering vanes and fins, thrust vector control (TVC), etc. Absence of such modeling has hindered maximum exploitation of plume signatures for threat detection and tracking. It will support development & testing of algorithms for hit to kill, "plume to hardbody" handover, aim point selection, etc. The final product of this program will be an engineering-oriented, reliable software tool usable by the boost-phase intercept community. The model will implement innovative Artificial Neural Network techniques in combination with robust numerical algorithms, automatic grid generation and a user-friendly plume-oriented, GUI-driven Expert Interface to provide a rapid turnaround capability within a high throughput, parallel architecture framework.

* Information listed above is at the time of submission. *

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