A Practical Probabilistic Analysis Method for Hydrocode-Based Lethality Assessment

Abstract

A new approach for practical hydrocode based lethality assessment is proposed. The approach couples hydrocode impact analysis with more efficient probabilistic analysis methods originally developed by the structural reliability community. The probabilistic methods are based upon advanced reliability methods which utilize reasonable assumptions together with efficient iteration and convergence algorithms to obtain an approximation of the boundary in engagement space that separates those intercepts that negate the threat from those that do not. Once this is accomplished, the lethality is uniquely determined. A specific implementation of the proposed methods is used to determine the lethality for four different threat warhead damage levels in a simulated 2-D intercept space. These approximate results are then compared with a 30,000 sample Monte Carlo solution in order to independently assess the accuracy of the methodology. The error in the calculated lethality obtained using the proposed method ranged from a maximum of 1.9% to a minimum of 0.01% while requiring 16 or fewer impact analyses for each lethality assessment. Additionally, the proposed approach identifies a critical engagement that is useful for providing guidance in improving the lethality and for selecting the most meaningful impact conditions for small scale or rocket sled tests.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA355892

Entities

People

  • James L. Lamb

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computational Science
  • Computations
  • Physics
  • Physics Laboratories
  • Probability
  • Random Variables
  • Reliability
  • Sampling
  • Simulations
  • Statistical Sampling
  • Test And Evaluation
  • Trajectories
  • Two Dimensional
  • Weapon System Effectiveness
  • Weapon Systems

Readers

  • Explosive Engineering.
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • Space