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The generic methodology for verification and validation applied to medium range anti-tank simulation training devices

Author: Voogd, J.M. · Roza, M.
Type:article
Date:2015
Place: Orlando, FL
Source:2015 Fall SISO Simulation Interoperability Workshop (SIW), 31 August - 4 September 2015, Orlando FL, USA
Identifier: 528061
Article number: 15F-SIW-055
Keywords: Simulation · Wargames · Simulation based training · Verification and validation · Defence Research · Defence, Safety and Security · Human and Operational Modelling · MSG - Modelling Simulation & Gaming · ELSS - Earth, Life and Social Sciences

Abstract

The Dutch Ministry of Defense (NL-MoD) has recently acquired an update of its medium range anti tank (MRAT) missile system, called the GILL. The update to the SPIKE Long Range (LR) weapon system is accompanied with the acquisition of new simulation training devices (STDs). These devices are bought Commercial off the Shelf (COTS). The question arises whether the STDs are valid training means for the NL MoD intended training purposes. In this paper we present the application of the Generic Methodology for Verification and Validation (GM-VV) to the question above. First the intended purpose of the STD’s is determined by executing a training needs analysis, then the verification and validation (V&V) areas of interest are selected based on how the training curriculum depends on the usage of an STD and the uncertainty about its quality. During the V&V study it was found that specific tests would only be possible at a later time, e.g. due to unavailable validation reference data, outside of the time frame of the V&V study, and feasible substitute tests had to be defined. Many findings from the V&V tests indicate the usefulness of the STDs, while others indicate that changes are required, either to the training curriculum or to the STDs. The GM-VV allows for adapting to the scope as well as the graceful degradation of the V&V tests. The NL MoD can build upon the current findings at a later time, e.g. by adding reference data, to further decrease uncertainty, and thus reducing the M&S use risk.