Keynote Lecture: AI-powered digital twins for intelligent asset management of offshore energy infrastructures towards greener transition and early warnings for extreme conditions

Renewable energy sector indispensably requires farming infrastructures to enable energy systems and energy transmission. Offshore wind structures have gained significant momentum in recent years because they can generate more electricity per amount of capacity installed from stronger and more stable wind. However, the farming infrastructures (e.g. wind turbine, offshore platform &amp; jacking, mooring system, and foundation) experience adverse climate conditions and often require timely actions to retrofit, repair and/or reconstruct. This presentation will highlight recent advancements in the application of AI-powered digital twins for efficiently managing their assets and components. In this presentation, ongoing collaborative research at the University of Birmingham and Jiangsu University of Science and Technology will be portrayed. It aims to demonstrate the recent advances in artificial intelligence to enable digital twins capable of implementing circular economy practices, while offering early warnings for intelligent, optimal asset maintenance and operations. The research outcome will improve lifecycle sustainability and systems resilience of offshore and energy industry. This is well aligned with United Nation's Sustainable Development Goals.<br/><br/>Keynote speaker: Dr Sakdirat Kaewunruen is a Reader in Railway and Civil Engineering, University of Birmingham. Dr Kaewunruen has extensive experience in both industry and academia. He is a Chartered Engineer and has over 25 years of experience within civil and railway industry (with over a decade practicing in industry). He has over 600 technical publications that have been translated for practical impacts and industry standardisation. He has actively served on many industry committees including ISO, CEN, BSI standard committees, PWI panel, and Concrete Society Midlands; and is Chief Editor of Frontiers in Built Environment (Transportation and Transit Systems). He is a UK delegate in management committees of two EU COST Actions: CircularB and Eco4All, which are the world's largest networks for circularity scientists and practitioners. He has also been globally recognised in the World's Top 100 Most Cited Scientists in Civil Engineering by Stanford University and Elsevier.

Publication Details

Journal
University of Birmingham Research Portal (University of Birmingham)
Published
2025-04-01
Primary Topic
Marine and Offshore Engineering Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Keynote Lecture: AI-powered digital twins for intelligent asset management of offshore energy infrastructures towards greener transition and early warnings for extreme conditions

University of Birmingham Research Portal (University of Birmingham)
Marine and Offshore Engineering Studies
article

Keynote Lecture: AI-powered digital twins for intelligent asset management of offshore energy infrastructures towards greener transition and early warnings for extreme conditions

article en

Abstract

Renewable energy sector indispensably requires farming infrastructures to enable energy systems and energy transmission. Offshore wind structures have gained significant momentum in recent years because they can generate more electricity per amount of capacity installed from stronger and more stable wind. However, the farming infrastructures (e.g. wind turbine, offshore platform &amp; jacking, mooring system, and foundation) experience adverse climate conditions and often require timely actions to retrofit, repair and/or reconstruct. This presentation will highlight recent advancements in the application of AI-powered digital twins for efficiently managing their assets and components. In this presentation, ongoing collaborative research at the University of Birmingham and Jiangsu University of Science and Technology will be portrayed. It aims to demonstrate the recent advances in artificial intelligence to enable digital twins capable of implementing circular economy practices, while offering early warnings for intelligent, optimal asset maintenance and operations. The research outcome will improve lifecycle sustainability and systems resilience of offshore and energy industry. This is well aligned with United Nation's Sustainable Development Goals.<br/><br/>Keynote speaker: Dr Sakdirat Kaewunruen is a Reader in Railway and Civil Engineering, University of Birmingham. Dr Kaewunruen has extensive experience in both industry and academia. He is a Chartered Engineer and has over 25 years of experience within civil and railway industry (with over a decade practicing in industry). He has over 600 technical publications that have been translated for practical impacts and industry standardisation. He has actively served on many industry committees including ISO, CEN, BSI standard committees, PWI panel, and Concrete Society Midlands; and is Chief Editor of Frontiers in Built Environment (Transportation and Transit Systems). He is a UK delegate in management committees of two EU COST Actions: CircularB and Eco4All, which are the world's largest networks for circularity scientists and practitioners. He has also been globally recognised in the World's Top 100 Most Cited Scientists in Civil Engineering by Stanford University and Elsevier.

University of Birmingham Research Portal (University of Birmingham)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Marine and Offshore Engineering Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.