Multi-Scale Modeling and Large-Scale Transient Simulation of Ballistic Fabric

Abstract

Ballistic fabrics such as Kevlar and Zylon are finding new uses not only as shielding for personnel but also in commercial and military aircraft protecting flight-critical components in the event of a high-speed ballistic impact. Since experimental tests on these materials are often expensive and time consuming, a computational model amenable to largescale numerical simulations on massively parallel processors would provide an ideal alternative. To this effect, a novel multi-scale approach has been developed for modeling ballistic fabric that extracts information from the micro-scale fibril material properties to build the macro-scale sheet. This approach incorporates the stochastic nature of the material due to the random variations in the yarn caused by the weaving process. Representing these variations is critical to capturing the heterogeneous damage and failure of the material as confirmed by experimental tests. A parallel implementation of the proposed multi-scale method has been developed with particular attention to the contact problem. The paper will focus on all of these issues and report on massively parallel large-scale computations for large sheet applications with both performance and validation results.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA503529

Entities

People

  • C. Farhat
  • D. Powell
  • T. J. Zohdi

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Aircraft Industry
  • Aircrafts
  • Algorithms
  • Applied Mechanics
  • Computational Mechanics
  • Computational Science
  • Computations
  • Computers
  • Engineering
  • Materials
  • Mechanics
  • Multiscale Modeling
  • Parallel Processors
  • Scale Models
  • Shielding
  • Simulations

Readers

  • Explosive Engineering.
  • Nanocomposite Materials Science
  • Parallel and Distributed Computing.