معرفی
Dr. Nan Li is a researcher in the Department of Mechanical Engineering at Imperial College London, affiliated with the Metal Forming and Materials Modelling research group. Their work focuses on advanced material processing techniques, particularly in automotive applications, including tailored microstructure development for safety-critical components and optimization of hot and cold stamping processes. Dr. Li holds a PhD in Mechanical Engineering (Imperial College London), a BEng in Thermal Energy and Heating Dynamics Engineering, and an MSc in Automotive Engineering.
Research interests include material modeling for high-strength steel (e.g., boron steel), crashworthiness analysis of vehicle panels, and integration of artificial intelligence (AI) and deep learning into manufacturing optimization. Recent studies emphasize surrogate models for real-time simulations, graph neural networks for crash performance prediction, and novel heat-stamping processes for titanium alloys like Ti6Al4V.
Collaborations with industry partners like SAIC have driven applied research in graded microstructure design for enhanced vehicle energy absorption. Key methodologies involve finite element analysis (FEA), constitutive modeling of polymers and metals, and experimental validation of forming limits under thermal-mechanical conditions.
Publications highlight trends in AI-driven tool compensation, implicit neural representations for geometry optimization, and efficient quench-forming techniques for aluminum and titanium alloys. While no formal awards are listed, Dr. Li’s contributions to lightweight automotive materials and process innovation are notable in the field.
Labs/Teams: Active member of the Metal Forming and Materials Modelling group at Imperial College, collaborating on projects involving additive manufacturing, lattice structure optimization, and high-performance material fabrication for aerospace and automotive sectors.
