PHD at Harbin Engineering University, China
Yang CHEN, Ph.D., is a dedicated researcher specializing in ship and marine structures design and manufacture. Currently pursuing a Ph.D. at Harbin Engineering University, his focus lies in predicting motion responses of marine engineering through deep learning and digital twin technologies. With a Master’s from the same institution and a Bachelor’s from Zhejiang Ocean University, Yang has garnered numerous accolades, including scholarships and awards for his academic excellence. His research contributions span predictive mooring tension models for semi-submersible platforms, showcasing his expertise in offshore intelligent operation and maintenance. Yang’s innovative work holds promise for enhancing safety and efficiency in maritime industries.
Professional Profiles:
Scopus profile
Orcid profile
Education:
Ph.D. Student College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China 09/2021 – Present Major: Ship and Marine Structures Design and Manufacture Research Area: Motion response prediction of marine structures; Deep learning; Marine engineering digital twin; Offshore intelligent operation and maintenance Thesis Title: Research on the motion response and mooring tension prediction method for semi-submersible production platforms M.Sc. Harbin Engineering University, Harbin, China 09/2020 – 06/2021 B.S. Zhejiang Ocean University, Zhoushan, China 09/2016 – 06/2020
Honors and Awards:
The First Prize Scholarship for Harbin Engineering University [2023] The Three-good students for Harbin Engineering University [2023] The Second Prize Scholarship for Harbin Engineering University [2022] The Second Prize Scholarship for Harbin Engineering University [2021] Zhejiang Ocean University Youth May Fourth Medal [2020]
Research Area:
Motion response prediction of marine structures, Offshore intelligent operation and maintenance, Deep learning, Marine engineering digital twin.
Research Works:
Lihao Yuan, Yang Chen, Yingfei Zan, Shenghua Zhong, Meirong Jiang, Yaogang Sun. A novel hybrid approach to mooring tension prediction for semi-submersible offshore platforms. Ocean Engineering, 287, 115776, 2023. Lihao Yuan, Yang Chen, Zhi Li. Real-time prediction of mooring tension for semi-submersible platforms[J]. Applied Ocean Research, 2024, 146: 103967.
Research Focus:
Yang CHEN, Ph.D., specializes in predictive modeling and analysis within the realm of marine engineering. His research focus primarily lies in developing innovative methods for predicting mooring tension in semi-submersible offshore platforms. With a keen interest in utilizing hybrid approaches and real-time data processing, Yang aims to enhance the efficiency and safety of offshore operations. By integrating deep learning techniques and digital twin technologies, he seeks to provide accurate and timely predictions, crucial for optimizing the performance of marine structures. Yang’s contributions represent a significant advancement in the field, promising practical solutions for the challenges faced in offshore engineering and operation management.
Publications (TOP NOTES)
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