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

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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Category

Academic chapter

Language

English

Author(s)

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • UiT The Arctic University of Norway

Year

2024

Publisher

International Society of Offshore and Polar Engineers

Book

Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference - ISOPE 2024

ISBN

9781880653784

Page(s)

4318 - 4325

View this publication at Norwegian Research Information Repository