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

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$149,766.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
HDTRA1-13-P-0009
Award Id:
n/a
Agency Tracking Number:
T122-005-0129
Solicitation Year:
2012
Solicitation Topic Code:
DTRA122-005
Solicitation Number:
2012.2
Small Business Information
PO Box 781607, San Antonio, TX, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
618026491
Principal Investigator:
Bryan Bewick
Project Engineer
(512) 380-1988
bbewick@protection-consultants.com
Business Contact:
Kirk Marchand
Managing Principal
(512) 380-1988
kmarchand@protection-consultants.com
Research Institution:
Stub




Abstract
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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