
Ming Zhang
Research Associate, PhD
Department of Naval Architecture, Ocean & Marine Engineering
Univerisity of Strathclyde
Email: ming.zhang.100@strath.ac.uk
Research Interests

Wave Energy Converter Hydrodynamics




Ship Manoeuvring




Real-Time Control




Machine Learning




Offshore Green Hydrogen




Education Background:
-
Sep 2018 - Sep 2022: Ph.D. researcher in Naval Architecture, Ocean and Marine Engineering Department, University of Strathclyde, UK.
-
Sep 2011 - Mar 2018: MSc, BSc in Structure Design and Construction of Naval Architecture and Ocean Engineering Department, Harbin Engineering University.

Employment Background:
-
Sep 2021 - Present: Research Assistant in University of Strathclyde, Glasgow, UK.
-
Mar 2020 - Mar 2021: Teaching Assistant in University of Strathclyde (NM436 Dynamics of Offshore Structure; NM423 Seakeeping and Manoeuvring; NM325 Offshore Oil and Gas Production Systems).
Publication:
-
Zhang, M., Hao, S., Wu, D., Chen, M-L., & Yuan, Z-M. (2022). Time-optimal obstacle avoidance of autonomous ship based on nonlinear model predictive control. Ocean Engineering, 266(Part 1), [112591]. https://doi.org/10.1016/j.oceaneng.2022.112591
-
Huo, F., Zhao, Y., Zhang, J., Zhang, M., & Yuan, Z. M. (2023). Study on wave slamming characteristics of a typical floating wind turbine under freak waves. Ocean Engineering, 269, 113464.
-
Stark C, Xu Y, Zhang M, et al. Study on applicability of energy-saving devices to hydrogen fuel cell-powered ships[J]. Journal of Marine Science and Engineering, 2022, 10(3): 388.
-
Zhang M. , et al. Real-time Control of Wave Energy Converter Based on LSTM RNN based Wave Prediction. Online conference, 28-29 April 2022.
-
Li T., Zhang M., et.al. Real-time Control of WECs Based on NAR,NARX and LSTM Artificial Neural Network. ISOPE2022, Shanghai.
-
Zhang M. Yuan Z.M. *. Time-optimal Autonomous Berthing Based on Nonlinear Model Predictive Control. 6th MASHCON 2022, Glasgow, 22-26 May 2022.
-
Zhang M., et al. Development of a Novel Wave-Force Prediction Model Based on Deep Machine Learning Algorithms. ISOPE2020, Virtual, October 2020.
-
Zhang M.. Development of a Novel Wave-force Prediction Model based on LSTM-NARX Algorithms. WSOS2020 workshop, Glasgow, 5-8 February 2020, Glasgow, UK.
-
Zhang M.. Real-time Control of Wave Energy Converter Based on LSTM Prediction based on LSTM-NARX Algorithms. WETNAOE2019 workshop, 14-15 November 2019, Hiroshima, Japan.



Project Involvement:
-
Apr 2022 - Present: Maritime Hydrogen Highway, Maritime Research and Innovation UK (MarRI-UK) initiative supported by the Department for Transport (DfT)
-
Sep 2021 - Apr 2022:Transition to hydrogen powered ocean-going and short-sea shipping with enabling retrofit technologies (TransShip), UK research innovate (UKRI).
-
Sep 2021 - Present: Investigation on Real-time Control Method of Wave Energy Converter Based on Machine Learning Wave Prediction, supported by National Natural Science Foundation of China (NSFC).
-
Multibody system hydrodynamics | Zhang, Ming (PI), EPSRC (Engineering and Physical Sciences Research Council), 1/07/18 → 1/07/21
-
Maritime Robotics Society Academic Adviors of Autonomous Control Team

Editor Board Member:
-
Frontiers in Energy Research
