Digital Twins for Vessel Life Cycle Service Innovation in Maritime Industry /

This book introduces the development of the digital twin of the marine infrastructure in Norway, which will be a significant scientific and operational achievement for the industry, making efficient and safe offshore operations possible. It enables data exchange safely and easily between different s...

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Bibliographic Details
Main Authors: Zhang, Houxiang (Author), Li, Guoyuan (Author), Hildre, Hans Petter (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Edition:1st ed. 2024.
Subjects:
Online Access:https://doi.org/10.1007/978-981-97-4768-9
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245 1 0 |a Digital Twins for Vessel Life Cycle Service  |h [electronic resource] :  |b Innovation in Maritime Industry /  |c by Houxiang Zhang, Guoyuan Li, Hans Petter Hildre. 
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505 0 |a Introduction -- Part 1. Maritime Digital Twins -- Chapter 1. State of the Art -- Chapter 2. Co-simulation Mechanism as Digital Twins Platform -- Chapter 3. Data Collection and Transmission -- Chapter 4. Models and Sub-domain Models for Digital Twins -- Chapter 5. Enabling Tools for Onboard Support -- Part 2. Digital Twin Application and Case Studies -- Chapter 6. Remote Control Centre -- Chapter 7. Ship Docking and Motion Control -- Chapter 8. Simulation Based Pre-Training -- Chapter 9. PHM System -- Chapter 10. Demanding Pre-operation -- Chapter 11. Research Challenges. 
520 |a This book introduces the development of the digital twin of the marine infrastructure in Norway, which will be a significant scientific and operational achievement for the industry, making efficient and safe offshore operations possible. It enables data exchange safely and easily between different sub-systems, modules, and various applications. A complete digital twin ship will be presented in details. Thus, the twin ship can provide an integrated view of the ship’s various physical and behavioral aspects in different stages, and allow simultaneous optimization of functional performance requirements. In addition, it enables advanced control and optimization, e.g., creating more reliable prediction for flexible objectives (time, output, emissions, fuel consumption), and executing day-ahead and long-term planning for operations. More importantly, several related applications and case studies are presented in the end to confirm the effectiveness of the digital twin system. The research work is not only interesting for academia, also for industry. 
532 8 |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. 
532 8 |a No reading system accessibility options actively disabled 
532 8 |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com 
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