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Data Structures for Efficient and Integrated Simulation of Multi-Physics Processes in Complex Geometries

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-04-C-R219
Agency Tracking Number: 04SB1-0167
Amount: $84,760.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SB041-011
Solicitation Number: 2004.1
Timeline
Solicitation Year: 2004
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-04-28
Award End Date (Contract End Date): 2004-12-30
Small Business Information
10406 Stone Ridge Ln
Vienna, VA 22182-1842
United States
DUNS: 080516670
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Wade Huebsch
 Consultant
 (304) 293-3111
 wade.huebsch@mail.wvu.edu
Business Contact
 Andrei Smirnov
Title: Director
Phone: (304) 293-3111
Email: asmirnov@wvu.edu
Research Institution
N/A
Abstract

Advanced data types for simulation of discrete and continuum dynamics in complex 3D geometries are proposed. These data types form the basis of a model-development environment, MulPhys, based on 3D libraries for manipulation of geometrical primitives, object-oriented multi-domain modeling paradigm, continuum solvers on unstructured meshes, and discrete particle solvers. The numerical schemes are based on the methods of continuum and discrete mechanics, such as the control-volume method for the solution of transient flow problems on unstructured meshes, the finite-element method for the solution of elasticity problems for linear, planar and 3D elements, and the Lagrangian particle method for the solution of particle motion in continuum media. The interaction of fluids, structures and particles is accomplished through the coupling of the solvers in a unified multi-solver modeling paradigm. Several prototype example cases of complex continuum mechanical systems are considered. It is proposed to refine and optimize the existing data types to better represent the multi-physics problems in a multi-processor computational environment. At the same time, further extensions and generalization of the data types and multi-modeling schemes are proposed so as to better suite the problems with strong non-locality features, and multi-scale processes.

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

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