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000 nam5i
001 2210080934811
003 DE-He213
005 20250321105436
007 cr nn 008mamaa
008 240829s2024 si | s |||| 0|eng d
020 a97898197476899978-981-97-4768-9
024 a10.1007/978-981-97-4768-92doi
040 a221008
050 aQA76.76.E95
050 aQ387-387.5
072 aUYQE2bicssc
072 aCOM0250002bisacsh
072 aUYQE2thema
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100 aZhang, Houxiang.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
245 00 aDigital Twins for Vessel Life Cycle Serviceh[electronic resource] :bInnovation in Maritime Industry /cby Houxiang Zhang, Guoyuan Li, Hans Petter Hildre.
250 a1st ed. 2024.
264 aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.
300 aXVIII, 194 p. 87 illus., 74 illus. in color.bonline resource.
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
347 atext filebPDF2rda
505 aIntroduction -- 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 aThis 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.
650 aExpert systems (Computer science).
650 aMarine engineering.
650 aComputer science.
650 aIndustrial engineering.
650 aProduction engineering.
650 aKnowledge Based Systems.
650 aMarine Engineering.
650 aComputer Science.
650 aIndustrial and Production Engineering.
700 aLi, Guoyuan.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
700 aHildre, Hans Petter.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
710 aSpringerLink (Online service)
773 tSpringer Nature eBook
776 iPrinted edition:z9789819747672
776 iPrinted edition:z9789819747696
776 iPrinted edition:z9789819747702
856 uhttps://doi.org/10.1007/978-981-97-4768-9
912 aZDB-2-SCS
912 aZDB-2-SXCS
950 aComputer Science (SpringerNature-11645)
950 aComputer Science (R0) (SpringerNature-43710)
Digital Twins for Vessel Life Cycle Service[electronic resource] :Innovation in Maritime Industry /by Houxiang Zhang, Guoyuan Li, Hans Petter Hildre
종류
전자책
서명
Digital Twins for Vessel Life Cycle Service[electronic resource] :Innovation in Maritime Industry /by Houxiang Zhang, Guoyuan Li, Hans Petter Hildre
저자명
판 사항
1st ed. 2024.
형태사항
XVIII, 194 p 87 illus, 74 illus in color online resource.
주기사항
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.
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