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Singular Value Decomposition-based Multiple Model Approach towards Developing Digital Twin Applications in Ship Performance Prediction

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https://hdl.handle.net/10037/35597
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Date
2024
Type
Chapter
Bokkapittel

Author
Taghavi, Mahmood; Perera, Lokukaluge Prasad Channa
Abstract
Representing the entire operational range of an ocean-going vessel with linear equations is often a formidable task. In this research study, a datadriven localized model is presented for ship performance prediction as a part of the digital twin development. For this purpose, different operational conditions of the vessel, i.e., data clusters, are identified using the Gaussian Mixture Models (GMM) coupled with the Expectation Maximization (EM) algorithm. Subsequently, Singular Value Decomposition (SVD) as a part of the Eigensystem Realization Algorithm (ERA) is applied to each cluster to establish the relationships between different operational and navigational variables and capture the system dynamics in localized operational conditions in each cluster.
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Source at https://www.isope.org/.
Publisher
ISOPE
Citation
Taghavi, Perera: Singular Value Decomposition-based Multiple Model Approach towards Developing Digital Twin Applications in Ship Performance Prediction. In: ISOPE 2024. Proceedings of the Thirty-fourth, 2024 International Ocean and Polar Engineering Conference - ISOPE 2024, 2024. International Society of Offshore and Polar Engineers
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  • Artikler, rapporter og annet (teknologi og sikkerhet) [360]
Copyright 2024 The Author(s)

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