Shadmani / Nikoo / Gandomi Ocean Wave Energy Technology

Fundamentals of Wave Farm Design
Erscheinungsjahr 2025
ISBN: 978-3-031-95040-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 231 Seiten

This book demonstrates the transformative power of optimization algorithms in advancing ocean wave energy. It blends theory with practice to explain how computational optimization can dramatically enhance the efficiency and performance of wave energy converters - devices that harness the power of ocean waves for renewable energy. The books illustrations and detailed tables provide visual and comparative insights into the interactions between various algorithmic approaches and wave energy systems, helping make complex engineering concepts accessible to non-specialists. With real-world case studies and innovative perspectives on algorithmic optimization in wave farm design, this book serves as a comprehensive gateway to understanding not only the fundamentals of wave energy but also the cutting-edge techniques steering the field toward a more sustainable future.

Zielgruppe

Graduate

Autoren/Hrsg.

Shadmani, Alireza

Nikoo, Mohammad Reza

Gandomi, Amir H.

Inhaltsverzeichnis

1. Wave Energy Fundamentals and Calculation.- 2. Boundary Element Methods.- 3. Wave Energy Converter Principles and Geometry Design.- 4. Layout Design Characteristics and Cost Evaluation.- 5. Power Take-Off Control of WECs.

Über Autor(innen)

Dr. Mohammad Reza Nikoo is an Associate Professor of the Department of Civil and Architectural Engineering at Sultan Qaboos University, Oman (2021-present), and a member of the Iranian Federation of Young Elites (2008-present). He was awarded the prestigious Oman National Research Award 2024 and was recognized as one of the world’s top 2% scientists in 2024, based on Stanford's Top 2% Scientists Ranking. He is also the top-ranked Civil Engineer in Oman in the 2024 Scientists Ranking.

Dr. Nikoo has served as an Honorary Visiting Fellow at the University of Technology Sydney (UTS), Australia, for four consecutive years (2022, 2023, 2024 and 2025). Previously, he was an Associate Professor in the Department of Civil and Environmental Engineering at Shiraz University, Shiraz, Iran, from 2017-2021. During his tenure at Shiraz University, he was selected as the Top Young Researcher for three consecutive years (2018-2020) and Iran’s Eminent Young Scientist in 2020.

He has supervised 12 Ph.D. and 45 MSc theses and published over 190 journal papers, 85% of which are in Q1 Journals. The impact of his research is evident in his 5864 citations (H-index=42).

Amir H. Gandomi is a Professor of Data Science at the Faculty of Engineering & Information Technology, University of Technology Sydney. He is also affiliated with Obuda University, Budapest, as a Distinguished Professor. Prior to joining UTS, Prof. Gandomi was an Assistant Professor at the Stevens Institute of Technology and a distinguished research fellow at BEACON Center, Michigan State University. Prof. Gandomi has published over three hundred journal papers and 12 books, which have collectively been cited 65,000+ times (H-index=111). He has been named one of the most influential scientific minds and received the Highly Cited Researcher award from Web of Science for six years. In a recent study at Stanford University, released by Elsevier, Prof Amir H Gandomi is ranked 24th most impactful researcher in the AI and Image Processing subfield in 2023! He has received multiple prestigious awards for his research excellence and impact, such as the 2024 IEEE TCSC Award for Excellence in Scalable Computing (MCR), the 2023 Achenbach Medal, and the 2022 Walter L. Huber Prize, the highest-level mid-career research award in all areas of civil engineering. He has served as associate editor, editor, and guest editor in several prestigious journals, such as AE of IEEE Networks and IEEE IoTJ. Prof Gandomi is active in delivering keynotes and invited talks. His research interests are global optimisation and (big) data analytics using machine learning and evolutionary computations in particular.

Alireza Shadmani serves as a Research Assistant at the Faculty of Engineering and Information Technology at the University of Technology Sydney. He holds a master’s degree in Coastal, Ports, and Marine Structures Engineering from Amirkabir University of Technology (Polytechnic Tehran), which is ranked among the top five universities in Iran according to the 2024 US News ranking. Alireza possesses extensive experience in optimizing wave energy converters and developing wave energy generation models. He has recently published several research papers focusing on these areas.