Volume 4 Number 4 (Jul. 2014)
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IJAPM 2014 Vol.4(4): 280-285 ISSN: 2010-362X
DOI: 10.7763/IJAPM.2014.V4.299

Monte Carlo Simulations of Weapon Effectiveness Using Pk Matrix and Carleton Damage Function

Pawat Chusilp, Weerawut Charubhun, and Pattadon Koanantachai

Abstract—Carleton damage function has been commonly utilized to describe the weapon-target interaction in the weapon effectiveness analyses. This function is simplified from the actual weapon lethality data and these simplifications can affect the analysis results. This paper investigates the difference between results of Monte Carlo simulations to determine the probability of target damage that utilize the Carleton damage function and the results of the same simulations that utilize a non-simplified probability of kill (Pk) matrix. A problem of multiple shots of an unguided artillery weapon against an area target was chosen as a case study. Two sets of Monte Carlo simulations to determine the probability of damage on a target were performed for several numbers of shots and target sizes. The first set of simulations utilized the Pk matrix while the second set utilized the Carleton damage function. Statistical analyses were performed. It was suggested that there was difference between the results of two sets of simulations but the effect size was small.

Index Terms—Damage function, probability of damage, Monte Carlo simulation, weapon effectiveness.

Pawat Chusilp, Weerawut Charubhun, and Pattadon Koanantachai are with Defence Technology Institute, 47/433 Changewattana Road, Pakkred, Nonthaburi 11120, Thailand (e-mail: pawat.c@dti.or.th, weerawut.c@dti.or.th, pattadon.k@dti.or.th).

Cite: Pawat Chusilp, Weerawut Charubhun, and Pattadon Koanantachai, "Monte Carlo Simulations of Weapon Effectiveness Using Pk Matrix and Carleton Damage Function," International Journal of Applied Physics and Mathematics vol. 4, no. 4, pp. 280-285, 2014.

General Information

ISSN: 2010-362X (Online)
Abbreviated Title: Int. J. Appl. Phys. Math.
Frequency: Quarterly
DOI: 10.17706/IJAPM
Editor-in-Chief: Prof. Haydar Akca 
Abstracting/ Indexing: INSPEC(IET), CNKI, Google Scholar, EBSCO, Chemical Abstracts Services (CAS), etc.
E-mail: ijapm@iap.org
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