Spiryagin, M., Edelmann, J., Klinger, F., & Cole, C. (2023). Vehicle system dynamics in digital twin studies in rail and road domains. Vehicle System Dynamics. https://doi.org/10.1080/00423114.2023.2188228
E325-01 - Forschungsbereich Technische Dynamik und Fahrzeugdynamik
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Journal:
Vehicle System Dynamics
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ISSN:
0042-3114
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Date (published):
2023
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Number of Pages:
50
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Publisher:
Taylor & Francis
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Peer reviewed:
Yes
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Keywords:
vehicle system dynamics; rail; road; digital twin; ion modelling; advanced model; multiphysics model; multidisciplinary model; big data; machine learning; artificial intelligence; connected and automated road vehicles; design; safety analysis; predicitve maintenance; monitoring; optimisation
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Abstract:
A digital twin is aimed to be a virtual model designed to accurately replicate a physical system in the digital world. This is why digital twins have become quite popular in recent years in both rail and road domain applications, and some researchers and engineers have started considering the term as a buzz word that attracts increased interest in their research. In some cases, this leads to misunderstandings regarding the digital twin concept, especially if the discussion relates to digital twins built on physics-based models. This paper’s detailed review has been performed to address this issue considering the application of vehicle system dynamics theories as a basis for development of digital twins and the implementation process in digital twin studies. The results show that most works are focusing on digital twin developments at the ‘top level of the pyramid’ and more comprehensive research and investigation studies are needed in terms of the application of vehicle system dynamics in design and construction of digital twins. This paper adopts and summarises the possible directions for the development of a future framework in terms of disciplines relevant to vehicle system dynamics and presents a forecasting roadmap on future development strategies of digital twins.
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Research Areas:
Modeling and Simulation: 50% Computational System Design: 50%