MULTI-SCALE DISCRETE-EVENT SIMULATION FRAMEWORK FOR DYNAMIC COMBAT EFFECTIVENESS ASSESSMENT

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Simulation is a widely used tool in the development of weapon systems. It is a cost-effective alternative to expensive testing campaign and also allows exploration of a larger design space. In this paper, a multi-scale discrete-event simulation framework for weapon effectiveness analysis is presented. The proposed discrete-event modelling approach is a flexible and composable framework with interchangeable models. Physical models are implemented as black boxes within specialised modules and are invoked as state transition functions to update state variables. In this way, high and low resolution modelling can be combined as required. High resolution non-deterministic simulations are required for parameters’ uncertainty propagation along the projectile’s path. Sampling methods are integrated into the framework, wherein, parameters are defined using probabilistic distributions. As an illustration, the framework is used to evaluate the effectiveness of a tank weapon system against a fleet of drones. In this case study, Monte Carlo methods are used, more efficient sampling methods can be used.

Original languageEnglish
Title of host publicationModelling and Simulation 2024 - 38th Annual European Simulation and Modelling Conference 2024, ESM 2024
EditorsJose David Nunez-Gonzalez, Manuel Grana Romay, Philippe Geril
PublisherEUROSIS
Pages161-168
Number of pages8
ISBN (Electronic)9789492859334
Publication statusPublished - 2024
Event38th Annual European Simulation and Modelling Conference, ESM 2024 - San Sebastian, Spain
Duration: 23 Oct 202425 Oct 2024

Publication series

NameModelling and Simulation 2024 - 38th Annual European Simulation and Modelling Conference 2024, ESM 2024

Conference

Conference38th Annual European Simulation and Modelling Conference, ESM 2024
Country/TerritorySpain
CitySan Sebastian
Period23/10/2425/10/24

Keywords

  • Discrete Event Simulations
  • Julia
  • Monte Carlo
  • Uncertainty Quantification

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