Torch

Faculty and Department

  • Faculty of Science and Engineering
  • School of Engineering

Qualifications

  • BEng
  • MSc
  • PGCLTHE
  • PhD / DPhil

Summary

Dr. Wan is a Lecturer in the School of Mechanical Engineering at the University of Hull. He is also a Chartered Engineer (CEng) and a member of the Institution of Mechanical Engineers (IMechE). He holds a professional membership at the Institute of Materials, Minerals and Mining (IOM3). He is also a Fellow of the Higher Education Academy (FHEA).

Dr. Wan obtained his PhD degree from the University of Edinburgh in 2020 on computational modelling of fibre-reinforced composite materials. Then he took up a short-term postdoc position in the same group working on the prototype of green manufacturing of carbon fibre-reinforced composites for 3D printing. Since 2021, he has worked as a research fellow at the Queen's University Belfast with local industrial collaborators from the aerospace (Collins Aerospace and Spirit Aerosystems, Belfast) and maritime (Artemis Technologies Ltd) industries, addressing the challenges in the application of AI in the composite structural design. From 2023, he moved to the world-leading Bristol Composites Institute (BCI) as a research associate and worked as a core team member at the unique Rolls-Royce Composites University Technology Centre (UTC). He has been working on the multiscale modelling and digital twinning of engineering structures for sustainable energy. He then moved to a visiting position at the University of Bristol and joined the University of Hull in 2024.

Stress Analysis and Applications of Finite Element Analysis (Level 6)

Stress Analysis and Dynamics of Mechanical Systems (Level 5)

Recent outputs

View more outputs

Journal Article

Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling

Wan, L., Ullah, Z., Yang, D., & Falzon, B. G. (2023). Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling. Composite Structures, 312, Article 116837. https://doi.org/10.1016/j.compstruct.2023.116837

A novel approach for 3D discrete element modelling the progressive delamination in unidirectional CFRP composites

Wan, L., Sheng, Y., McCarthy, E. D., & Yang, D. (2023). A novel approach for 3D discrete element modelling the progressive delamination in unidirectional CFRP composites. Engineering Fracture Mechanics, 277, Article 108982. https://doi.org/10.1016/j.engfracmech.2022.108982

A micromechanics and machine learning coupled approach for failure prediction of unidirectional CFRP composites under triaxial loading: A preliminary study

Chen, J., Wan, L., Ismail, Y., Ye, J., & Yang, D. (2021). A micromechanics and machine learning coupled approach for failure prediction of unidirectional CFRP composites under triaxial loading: A preliminary study. Composite Structures, 267, Article 113876. https://doi.org/10.1016/j.compstruct.2021.113876

Research interests

Developing advanced engineering materials and structures (i.e. Carbon/Glass Fibre-Reinforced Composites) relies on a profound understanding of underground physics of their behaviours following elasticity-plasticity-damage-failure. At different length scales, from micro-, to meso- until macro- scales, they perform differently. Manufacturing induced defects, multiPhysics, multiDamages interact intricately, serving as the gateway to final material/structure failures. My ambition is to uncover these multiscale complexities, extending scientific insights into the application of digital tools in the reconstruction of materials/structures.

My research focuses on understanding the life-cycle behaviour of complex, hierarchically structured FRP composite materials via computational methods and set up a digital twin for them to monitor/predict the behaviours. This requires the combination of digital tools (i.e. computational modelling and structure health monitoring techniques) at different time and length scales. I have been working on developing multiscale and multiphysics computational methods to advance the understanding of the microstructure-property-performance relationship of FRP composite materials, so as to provide best performance of structures with the optimal engineering materials via a well-informed digital twin.

My research interests lie in the topics:

Computational modelling and composite materials

Multiscale and MultiPhysics modelling

Finite element and discrete element methods

Digital twin

3D printing

Postgraduate supervision

Dr. Wan welcomes PhD applications in

Computational modelling and composite materials

Multiscale and MultiPhysics modelling

Finite element and discrete element methods

Digital twin

3D printing

Journal peer reviewer

Reviewer for Thin-Walled Structures

2023

Reviewer for Polymer Composites

2023

Reviewer for Engineering failure analysis

2023

Reviewer for Engineering with computers

2023

Membership/Fellowship of professional body

FHEA

2023

MIMechE

2022

CEng

2022

MIMMM

2022

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