Jinsheng (Frank) Lai 「赖近昇」

I am a M.Eng. student in Civil Engineering at South China University of Technology, Guangzhou, China.

My work is centered on offshore renewable energy systems, structural systems, and AI-driven engineering methods. I am especially interested in how advanced materials, floating wind turbines, wave energy converters, and data-driven modeling can support more resilient and sustainable infrastructure.

Research Interests: machine learning and structure-control co-design for offshore renewable energy systems, with a focus on floating wind turbines, wave energy converters, and full-lifecycle fatigue optimization.

Email: frankjslai@gmail.com


News


Publications

GFRP blade section CT scanning

Mechanical Properties and Feasibility of GFRP from Decommissioned Large-Scale Wind Turbine Blades for Wave Energy Converter: A Case Study.

Y.-W. Li, J.-S. Lai, B.-Z. Zhou, and L. Cheng. Polymers, 18(7), 892, 2026. SCI Q1, IF=4.9.

[Paper]

Offshore wind O&M reinforcement learning framework

Applications of Deep Reinforcement Learning in Optimization of Offshore Wind Power Operation and Maintenance.

Jinsheng Lai. ICEPET, 2026. [Paper]

GFRP and duplex stainless steel joint design

Performance of Hybrid Bonded-Bolted Joints between GFRP from Decommissioned Wind Turbine Blades and Duplex Stainless Steel for Marine Application.

J.-S. Lai and Y.-W. Li. Manuscript in preparation, target: Engineering Structures, 2026. [Paper]


Selected Research

Wave energy converter system design

High-Value Repurposing of Decommissioned Wind Blade GFRP: Materials, Joints, and Marine Applications

Conducted material characterization of retired blade GFRP through mechanical testing and CT scanning, developed GFRP-duplex stainless steel bonded/bolted joint designs, and investigated an articulated multi-body wave energy converter through hydrodynamic simulation and wave tank testing.

CT Scanning, Mechanical Testing, Abaqus, AQWA, Wave Tank. Images: materials, testing, joint design, system.

DDPG-based intelligent O&M framework

Modeling and Intelligent Operation and Maintenance of Offshore Wind Systems

Conducted fully coupled aero-hydro-servo-elastic simulations of semi-submersible floating wind turbine platforms, and developed a Deep Deterministic Policy Gradient based intelligent O&M framework for sequential decision-making, net revenue improvement, and fault reduction against baseline models.

AQWA, OpenFAST, Sesam, Python, DDPG.

3D-printed metamaterial specimens

Compressive Response of 3D-Printed 2D Metamaterial Reinforced Composites with Diversified Geometries

Tested and evaluated the compressive behavior of 24 diverse 2D composite architectures, and proposed a comprehensive performance evaluation coefficient to screen for designs with superior specific energy absorption and specific strength.

3D Printing, Mechanical Testing.

BP neural network architecture

Crack Recognition Based on Backpropagation Neural Networks

Engineered a Multi-Layer Perceptron neural network with optimized activation functions and cross-entropy loss with backpropagation for automated Structural Health Monitoring.

Python, Neural Networks, SHM.

SAP2000 steel frame model with dampers

Vibration Damping Performance Analysis of Graded Yield Metal Dampers in a Steel Frame Structure

Investigated the energy dissipation mechanism of graded yield metal dampers in steel frame structures through modal decomposition response spectrum analysis and elastic time-history analysis across minor, moderate, and major earthquake scenarios.

SAP2000, Seismic Analysis.

Coir-FRP concrete specimens

Flexural Property and Mechanism of Coir-FRP Seawater and Sea-Sand Concrete for Artificial Fish Reefs

Optimized coir-fiber-matrix compatibility through combined chemical modification, tested flexural strength, integrated a non-linear MATLAB prediction model, and used SEM analysis to study the fiber bridging toughening mechanism.

Lab Testing, MATLAB, SEM.


Education

South China University of Technology (Project 985), Guangzhou, China
M.Eng. in Civil Engineering, Sep. 2024-Expected Jun. 2027. GPA: 3.63/4.0. Admission with entrance exam waived.
Hainan University (Project 211), Haikou, China
B.Eng. in Civil Engineering, Sep. 2020-Jun. 2024. GPA: 3.61/4.0 (88.26/100).

Honors & Awards

  1. Outstanding Graduate, Hainan University, 2024.
  2. First Prize, National University Structural Design Information Technology Contest, China, 2023.
  3. First-Class Comprehensive Scholarship, Hainan University, 2021 and 2022.
  4. Meritorious Student, Hainan University, 2021 and 2022.

Skills

Programming: Python, MATLAB, Linux, AI-assisted scripting with Claude Code and Codex.
Simulation: ABAQUS, ANSYS AQWA, OpenFAST, Sesam.
Languages: Chinese (native), English (IELTS 7, Mar. 2026).