Dr Lik-ho Tam
School of Transportation Science and Engineering, Beihang University
China
Summary: With increasing demand for environmental protection and carbon neutrality, the quest for economical, eco-friendly, and sustainable structures is of vital importance. Fibre-reinforced composite materials with remarkable properties have emerged as viable candidates for these engineering structures. However, understanding and predicting their properties are very challenging due to the hierarchical structures and interfaces within the systems. In this seminar, the multi-scale and machine learning investigations will be presented for characterizing the complex structures and properties of composite materials. As the adhesion between fiber and matrix is governed by interactions between molecular constituents, a molecular modelling framework is used for understanding microscopic behaviour of fiber/matrix interface. After that, a scale-bridging computational technique, namely the coarse-grained modelling approach, will be presented for simulating fiber-reinforced composite at extended length scale. Following these, a multi-scale combined with machine learning approach will be introduced for investigating vibrations of composite materials. The mechanism of intriguing phenomena as observed in these composite materials will be discussed. By linking up interface with composites, the discussion on how understanding multi-scale structures can help us design better load-bearing composites will be presented.
Brief CV:
Dr. Lik-ho Tam works at School of Transportation Science and Engineering at Beihang University as an Assistant Professor. Dr. Tam obtained his B.Eng. in Aircraft Design & Engineering (2011) from Beihang, his M.Sc. in Materials Engineering & Nanotechnology (2013) and Ph.D. in Civil Engineering (2016) from City University of Hong Kong (CityU). After that, he carried out postdoctoral research at CityU and Beihang respectively. Dr. Tam’s research focuses on the structural design, property characterization, and engineering applications of composite materials and structures using a multi-scale and machine learning approach, so as to advance the science and engineering knowledge for enhancing the structural resilience and reducing the carbon footprint of infrastructure systems in transportation engineering. Currently, Dr. Tam has published over 60 articles, including around 30 first/corresponding-author SCI articles in journals Composites Part B: Engineering, Composite Structures, Construction and Building Materials, Applied Surface Science, and Mechanical Systems and Signal Processing, and around 10 first/corresponding-author EI articles. To date, Dr. Tam has been awarded several grants from National Natural Science Foundation of China and China Postdoctoral Science Foundation. Meanwhile, Dr. Tam has served as the Editorial Board Member in several international journals.