Agent Based Simulation and Optimization (ABSO) Tool for HPRF Dynamic Surface Engagement

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-14-P-1106
Agency Tracking Number: N132-134-0913
Amount: $80,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2014
Solicitation Year: 2013
Solicitation Topic Code: N132-134
Solicitation Number: 2013.2
Small Business Information
15400 Calhoun Drive, Suite 400, Rockville, MD, 20855-
DUNS: 161911532
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Evan Clark
 Senior Research Scientist
 (301) 294-4635
 eclark@i-a-i.com
Business Contact
 Mark James
Title: Director, Contracts and
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract
An Agent based Simulation and Optimization (ABSO) tool is proposed for evaluating HPRF weapon effectiveness in defending maritime assets against small boat attacks using dynamic sea surface engagement scenarios. For this effort, IAI will combine and extend i) Ray Tracing and Radiative Transfer (RT2) engine and ii) Ontology and Distributed-agent based Composable (ODCS) simulation framework. The RT2 engine will be used to simulate HPRF propagation and multipath loss, upon weapon engagement. It will be combined with a target response model that computes the RF energy transferred to the electronics based on probabilistic Coupling Cross Section (CCS) data of attacker"s boat. Using ODCS framework, the user can configure i) defender agents with behaviors such as patrolling, interception, and approach, that are combined with USV physics models and rules of engagement, and ii) attacker agents with behaviors such as swarming, diversionary, ranged attack and destroy. The key innovation is that user configures simulation design space (e.g., speed range and reference track envelop settings) instead a simulation scenario. A Gaussian process regression analysis and visualization technique will be developed to generate a weapon effectiveness response surface with minimum number of Design of Experiment data points accounting for uncertainties in the simulation scenarios.

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

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