Towards a framework for more robust validation and verification of simulation models for systems of systems

Bernard P. Zeigler, James J. Nutaro

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

We present a framework for verification and validation of simulation models of System of Systems that is based on an existing framework for modeling and simulation. The framework addresses problems arising especially in recently emerging Systems of Systems such as cyber-physical autonomous cooperative systems. The design of such systems presents challenges to the currently employed independent use of simplified models for formal verification or brute-force simulations which are severely limited in the range of conditions they can test. The proposed framework is applied to integration of formal analytic and simulation verification methods where there is a need to have confidence that the properties proved for idealized abstract models also hold in more realistic models which gave rise to the abstractions. Taking both logical and probabilistic perspectives clarifies the situation and suggests where more research is needed.

Original languageEnglish
Pages (from-to)3-16
Number of pages14
JournalThe Journal of Defense Modeling and Simulation: Applications, Methodology, Technology
Volume13
Issue number1
DOIs
StatePublished - Jan 1 2016

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. This manuscript has been co-authored by an employee of UT-Battelle, LLC, under Contract DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes

Keywords

  • Discrete Event System Specification
  • Experimental frames
  • Intended use
  • Modeling and simulation
  • Validation
  • Verification

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