A Comparison of Damage Functions for Use in Artillery Effectiveness Codes

Abstract

In mathematical combat simulation, it is common to model indirect fire (area) weapons in two independent steps: First, specific detonation points of the incoming warheads are selected using Monte Carlo methods. Then, each target element is located with respect to each warhead detonation point and the probability of achieving some level(s) of damage are determined, usually from the separation and orientation of each warhead-target pair. In practical cases, closed form functions are used to calculate the probability of damage. These functions are most often in one of two forms: the Carleton-von Neumann (Carleton) and the Cookie-Cutter (CC) forms. Indirect fire simulations of this type are commonly done in the Ballistics Research Laboratory, especially as an intrinsic part of analyses using the AURA methodology. When attention was turned toward new, more accurate weaponry, it was seen that the apparent effectiveness of two otherwise identical weapons might be significantly different if a Carleton were used for one and a CC for the other. This observation led to the present study of the Carleton and Cookie Cutter, the formulation of a hybrid function (the Klopcic function) and the development of a user-friendly, menu-driven computer code to calculate the effectiveness of artillery attacks upon collections of different targets.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1990
Accession Number
ADA222589

Entities

People

  • J. T. Klopcic

Organizations

  • Ballistic Research Laboratory

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Army
  • Army Aviation
  • Army Training
  • Artillery
  • Artillery Ammunition
  • Commerce
  • Computers
  • Indirect Fire
  • Miss Distance
  • Operations Research
  • Simulations
  • Standards
  • Test And Evaluation
  • User Friendly
  • Vulnerability
  • Weapons

Readers

  • Calculus or Mathematical Analysis
  • Computational Modeling and Simulation
  • Munitions and Ordnance Engineering