Advanced Computational Algorithms for Simulating Weapon-Target Interaction

Award Information
Agency:
Department of Defense
Branch:
Army
Amount:
$749,973.00
Award Year:
2004
Program:
STTR
Phase:
Phase II
Contract:
W911NF-04-C-0106
Agency Tracking Number:
A2-1313
Solicitation Year:
2003
Solicitation Topic Code:
ARMY03-T03
Solicitation Number:
N/A
Small Business Information
ACTA, INC.
2790 Skypark Drive, Suite 310, Torrance, CA, 90505
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
131277725
Principal Investigator
 G. Wije Wathugala
 Principal Investigator
 (310) 530-1008
 wathugala@actainc.com
Business Contact
 James Hudson
Title: Vice President
Phone: (310) 530-1008
Email: hudson@actainc.com
Research Institution
 Los Alamos National Laboratory
 W. B VanderHeyden
 Group T-3 P.O. Box 1663, Mail Stop B216
Los Alamos, NM 87545, NM, 87545
 (505) 667-9099
 Federally funded R&D center (FFRDC)
Abstract
This STTR project will develop and validate a robust, scalable computational capability for the simulation of weapon-target interactions of interest to the Army. The proposed algorithm is based on the FLIP (Fluid Implicit Particle) - MPM (Material Point Method) - MFM (Multiphase Flow Method) approach and CartaBlanca nonlinear solver environment developed at Los Alamos National Laboratory. CartaBlanca can solve coupled problems involving (a) failure and penetration of solids, (b) heat transfer, (c) phase change, (d) chemical reactions, and (e) multiphase flow. It is designed with GUI capabilities to utilize multiple processors on a single computer or on computer clusters. In Phase I, we demonstrated the feasibility of using CartaBlanca to simulate a bullet perforating a metal plate and bullet penetrating a metal plate backed by high explosives. In Phase II, we plan to improve CartaBlanca performance in parallel computers and compare CartaBlanca predictions with legacy codes such as EPIC. Then we plan to perform a formal model validation of CartaBlanca by comparing its predictions with experimental data using ACTA's Nonlinear Model V&V Toolbox for projectiles penetrating metal and concrete targets. In Phase III, we plan to use CartaBlanca to train a Fast Running Model for predicting weapon-target interaction problems.

* information listed above is at the time of submission.

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