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Modeling and simulation of large-scale systems: A systematic comparison of modeling paradigms
Graz University of Technology, Austria.
University of Nottingham, UK.
KTH, Royal Institute of Technology, Sweden.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-5888-8626
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2020 (English)In: Applied Mathematics and Computation, ISSN 0096-3003, E-ISSN 1873-5649, Vol. 365, article id 124713Article, review/survey (Refereed) Published
Abstract [en]

A trend across most areas where simulation-driven development is used is the ever in- creasing size and complexity of the systems under consideration, pushing established methods of modeling and simulation towards their limits. This paper complements existing surveys on large-scale modeling and simulation of physical systems by conducting expert surveys. We conducted a two-stage empirical survey in order to investigate research needs, current challenges as well as promising modeling and simulation paradigms. Furthermore, we applied the analytic hierarchy process method to prioritise the strengths and weak- ness of different modeling paradigms. The results of this study show that experts consider acausal modeling techniques to be suitable for modeling large scale systems, while causal techniques are considered less suitable.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 365, article id 124713
Keywords [en]
Modeling, Simulation, Physical modeling, Large-scale systems
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-75984DOI: 10.1016/j.amc.2019.124713OAI: oai:DiVA.org:ltu-75984DiVA, id: diva2:1351192
Note

Validerad;2019;Nivå 2;2019-09-18 (johcin)

Available from: 2019-09-13 Created: 2019-09-13 Last updated: 2019-09-18Bibliographically approved

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