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Ming Zhang

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

Research Interests

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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.

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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.

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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

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Editor Board Member:

  • Frontiers in Energy Research

MH2 Offshore Hydrogen System

MH2 Offshore Hydrogen System

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