Application of an Integrated HPC Reliability Prediction Framework to HMMWV Suspension System

Abstract

This research paper addresses the ground vehicle reliability prediction process based on a new integrated reliability prediction framework. This paper is intended to provide a context for and summary of the 37 page paper published in the proceedings of at the 2010 U.S. Army GVSETS symposium, which discusses the technical details at greater length. The integrated stochastic framework combines the computational physics-based predictions with experimental testing information for assessing vehicle reliability. The integrated reliability prediction approach incorporates several computational steps to achieve reliability prediction at component and system level. The Army can use this framework to improve the reliability of the military ground vehicle fleet, including consideration of all kinds of uncertainty, especially including model uncertainty. The end result will be a tool to use in the design of a new ground vehicle for increased reliability. The paper illustrates the application of the integrated approach to evaluate the reliability of the High-Mobility Multipurpose Wheeled Vehicle (HMMWV) front-left suspension system.

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Document Details

Document Type
Technical Report
Publication Date
Sep 13, 2010
Accession Number
ADA534877

Entities

People

  • Dan M. Ghiocel
  • Dan Negrut
  • David A. Lamb
  • David J. Gorsich

Organizations

  • United States Army Tank Automotive Research, Development and Engineering Center

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Case Studies
  • Corrosion
  • Crack Propagation
  • Fracture (Mechanics)
  • Ground Vehicles
  • High Performance Computing
  • Mechanics
  • Probability
  • Probability Distributions
  • Random Variables
  • Reliability
  • Sensitivity
  • Simulations
  • Stress Analysis
  • Uncertainty
  • Vehicles

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Inertial Navigation Systems.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.