Comparison Between the M256 120-MM Tank Cannon Jump Test Experiments and ARL's Gun Dynamics Simulation Codes for Prototype KE

Abstract

The interaction between the gun system and projectile cannot be directly measured during the launch event, leaving the interaction to be inferred from the exit state conditions of the projectile through various recording devices. The only direct means of studying the in-bore motion of the projectile and projectile-gun system interaction is through numerical simulation. The best approach for validation of the Army Research Laboratory's (ARL) gun-projectile dynamic simulation codes is comparison with projectile motion data obtained from ARL ballistic jump test experiments. In such tests, four or more sets of orthogonal radiograph images (x-rays) are typically used to characterize the state of the projectile at muzzle exit. The results from the x-rays can be directly compared to the predictions made by the gun-projectile dynamic simulations. This paper describes the methodology used to compare recent jump test data to gun-projectile dynamic simulations and presents comparisons for seven 120 mm prototype kinetic (KE) energy projectiles. The projectiles contain significant differences in their charge, subprojectile, and sabot designs that span the design parameters encountered in cartridge development.

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Document Details

Document Type
Technical Report
Publication Date
Apr 26, 2001
Accession Number
ADP012463

Entities

People

  • B. J. Guidos
  • C. D. Livecchia
  • J. F. Newill

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Boresights
  • Cameras
  • Center Of Gravity
  • Dynamics
  • Experimental Data
  • Exterior Ballistics
  • Impact Point
  • Instrumentation
  • Line Of Fire
  • Measurement
  • Projectiles
  • Propellants
  • Simulations
  • Statistical Analysis
  • Three Dimensional
  • X Rays

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • ballistics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference