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Soil-Structure Interaction (SSI) Effects for Fully and Partially Buried Structures

Award Information
Agency: Department of Defense
Branch: Defense Threat Reduction Agency
Contract: HDTRA1-13-P-0009
Agency Tracking Number: T122-005-0129
Amount: $149,766.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: DTRA122-005
Solicitation Number: 2012.2
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-03-11
Award End Date (Contract End Date): 2013-10-10
Small Business Information
PO Box 781607
San Antonio, TX -
United States
DUNS: 618026491
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Bryan Bewick
 Project Engineer
 (512) 380-1988
Business Contact
 Kirk Marchand
Title: Managing Principal
Phone: (512) 380-1988
Research Institution

Protection Engineering Consultants (PEC) proposes to develop a coarse-grain neural network modeling approach for efficient simulation of shock propagation through geological media including soil-structure interaction. In the coarse-grain approach, fast-running computational elements are developed which are an order of magnitude larger than typical FE elements, and the elements are driven by neural network-based equations as opposed to physics-based equations. Typically FRMs cannot extrapolate to problems beyond the boundaries of the data set used to develop the models. Moreover, the size of the data set required increases geometrically with the number of independent variables needed as input variables to the FRMs. A more robust approach will help to increase the applicability of the developed FRM, while still maintaining the requirement for rapid execution of the problem. The coarse-grain neural network modeling approach is a novel approach to develop a tool that is versatile and still retains the FRM requirement of rapid execution.

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

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