Article
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Dynamic Reduction-based Virtual Models for Digital Twins-A Comparative Study
Version 1
: Received: 13 June 2022 / Approved: 15 June 2022 / Online: 15 June 2022 (10:19:29 CEST)
A peer-reviewed article of this Preprint also exists.
Maulik, S.; Riordan, D.; Walsh, J. Dynamic Reduction-Based Virtual Models for Digital Twins—A Comparative Study. Appl. Sci. 2022, 12, 7154. Maulik, S.; Riordan, D.; Walsh, J. Dynamic Reduction-Based Virtual Models for Digital Twins—A Comparative Study. Appl. Sci. 2022, 12, 7154.
Abstract
Digital twins are the foundation of autonomous off-road vehicles. Dynamic reduction methods are one of several ways to develop digital twins for off-road vehicles. The article commences with a comprehensive overview of the most widely used dynamic reduction methods and then introduces performance metrics for assessing their efficacies in the context of digital twins. The paper additionally includes a detailed mathematical derivation of the state-space representation for reduced-order finite element models. The state-space representation of the reduced finite element models facilitates their export to problem-solving environments for dynamic analysis. The state-space models are eventually solved utilizing the built-in libraries of numerical solvers in textual and graphical programming platforms. In addition, the article identifies the set of solvers that best suit the simulation of virtual models for off-road vehicles. This article also includes an evaluation of the simulation results of digital models with modes ranging from 0 to 30 Hz. In addition, the article demonstrates the lower bound of the frequency range necessary and sufficient to be retained in off-road vehicle virtual models. Finally, the paper presents the simulation outcomes for digital models of commercial off-road vehicles with custom-built control, electrical, and control systems.
Keywords
digital twin; Industry 4.0; MATLAB; ANSYS; simulation; crane; modal analysis; dynamic substructuring; dynamic reduction; component modal synthesis
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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