Abstract
This thesis transforms the way we understand and monitor rail infrastructure with a digital twin that merges measurement data and physics-based models to deliver instant insights. This thesis will be of particular interest to professionals in the rail industry seeking to answer the following questions: What are the key features in the measurement data? How can an accurate physics-based vehicle-track interaction model be developed for a specific problem? And, how can mearsurement data and models be combined to deliver actionable insights in real-time?
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 2 Mar 2023 |
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Publication status | Published - 2023 |