Speakers

Prof. Xiaogang Liu

Shenzhen Graduate School of Harbin Institute of Technology, China

Prof. Xiaogang Liu acquired his Ph.D. degree in mechanical engineering from the University of Queensland, Australia, andhe is nowa Professor and Doctoral Supervisor of Mechanical engineering and Instrument Science and Technology at the School of Mechanical and Electrical Engineering, Wuhan University of Technology. He has chaired two scientific research projects supported by the National Natural Science Foundation of China, and his academic outputs include academic papers, invention patents and software copyrights in the fields of Intelligent Manufacturing, Contact Mechanics, Mechanical Vibration and Electromechanical Control. As the leader of a provincial teaching and research project about mechanical manufacturing, he summarised these academic outputs into monographs to integrate research and education, and was recognised as Fellow of Higher Education Academy (FHEA). Currently, he is an assessment expert of the national Natural Science Foundation of China, an assessment expert of China Scholarship Council, a senior member of the Chinese Mechanical Engineering Society, an expert of the high-tech industry in Wuhan, and was awarded the “T A Stewart-Dyer Prize/Frederick Harvey Trevithick Prize” by the Institution of Mechanical Engineers in London.

Prof. Hakim Naceur

Department of Mechanical Engineering, Polytechnic University Hauts-de-France, CNRS, UMR 8201 - LAMIH, F-59313 Valenciennes, France

H-index: 29

Hakim Naceur is currently a Professor at INSA Hauts-de-France and the Head of the Mechanical Engineering Department of the Engineering School INSA Hauts-de-France. Prof. Naceur is the Head of the Research team on Computational Structural Mechanics & Energetic Processes at the Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science (LAMIH UMR CNRS 8201) which is a joint research unit of the French National Centre for Scientific Research. He received his Mechanical Engineering degree from the University of Batna (Algeria) in 1993, then his M.S. degree from the University Pierre and Marie Curie (France) in 1994, and his Ph.D. from the University of Technology of Compiegne (France) in 1998.

He started as Assistant Professor (2000-2007), then Associate Professor (2007-2009) at the University of Technology of Compiegne. In September 2009, he moved to the Polytechnical University of Hauts-de-France as a full Professor and since January 2020, he has been a Professor at INSA Hauts-de-France. His research activities concern the computational structural mechanics including the development of advanced meshless techniques applied to multi-material shell structures for energy dissipation in shocks and impacts using homogenization techniques and multi-scale approaches. Other works include the modeling of metal forming processes, additive manufacturing, and optimization algorithms. To date, he authored more than 88 papers in peer-reviewed journals and 140 international conference papers, and book chapters dealing with computational mechanics. 

Speech Title: An automatic procedure for the design and optimization of cellular structures obtained by additive manufacturing

Abstract: The present keynote emphases on the design and numerical optimization of energy-absorbing cellular structures obtained through additive manufacturing. Indeed, recent technological advancements in additive manufacturing allow the design of new materials and geometric cellular shapes that combine lightness with high energy absorption capacity, such as lattice structures. Their use in the transportation sector is of a key interest to simultaneously contribute to structural weight reduction and safety in the event of crashes or impacts.

More precisely, this research concentrates on the development and application of a topological optimization algorithm coupled with a crash simulation software. Using multiobjective functionals based on the plastic work density, the resulting algorithm allows the generation of geometric shapes with significant energy absorption capacity while reducing the whole mass of the structure. On the other hand, the second innovation lies in achieving an optimal variation in the thickness of elementary cell struts for a lattice-based structure. This allows the component to exhibit ideal characteristics, combining lightness with excellent energy absorption capacity.

Further developments concern the introduction of digital twins to overcome some of the encountered additive manufacturing issues during the creation of the parts as well as optimizing their manufacturability.

Prof. Jiang Guo

Dalian University of Technology, China

H-index: 26

Prof. Jiang Guo is currently a professor and doctoral supervisor at the Dalian University of Technology (DUT). He was selected for the National Overseas High-level Talent Introduction Program-Youth Project, and the young top-notch talents of Liaoning Province's "Xing Liao Talent Program". He received his Ph.D. from The University of Tokyo in 2013. After graduation, he joined RIKEN as a researcher. In October 2015, he became a scientist at A*STAR (Agency for Science, Technology and Research). He has been actively engaged in developing and applying new optical aspheric and microstructure grinding and polishing processes for over a decade. He has published more than 80 journal papers in the top journals in the fields of manufacturing, optics, precision instrumentation, material processing and electrochemistry. He holds more than 30 international and national invention patents. He presided over more than 20 projects, such as the Japan Society for the Promotion of Science (JSPS) Youth Fund, the General Program of the National Natural Science Foundation of China, and the National Key Research and Development Program. He has won more than 10 academic awards, such as the Revitalization Award of the Japan Machine Tool Promotion Association and the Outstanding Research Achievement Award of the Chinese Students Association in Japan. He is currently a senior member of the Chinese Mechanical Engineering Society, a member of the European Society for Precision Engineering and Nanotechnology (EUSPEN), the American Society for Precision Engineering (ASPE) and Asian Society for Precision Engineering and Nanotechnology (ASPEN), etc. He is also the reviewer for over 50 SCI journals. He serves on the editorial board and youth editorial board of several international journals and as a reviewer for over 50 international journals.

His research interests include ultraprecision machining, polishing, measurement, mechatronics, and neutron optics.

Prof. Ying-Ren Chien

National Ilan University, China

Vice Chair of IEEE CESoc Virtual Reality, Augmented Reality, and Metaverse (VAM), IEEE Senior Member, H-index: 15

Ying-Ren Chien received the B.S. degree in electronic engineering from the National Yunlin University of Science and Technology, Douliu, Taiwan, in 1999, and the M.S. degree in electrical engineering and the Ph.D. degree in communication engineering from the National Taiwan University, Taipei, Taiwan, in 2001 and 2009, respectively. In 2012, he joined the Department of Electrical Engineering, National Ilan University, Yilan City, Taiwan, where he has been a Full Professor and the Chair, since 2018. His research interests are consumer electronics, multimedia denoising algorithms, adaptive signal processing theory, active noise control, machine learning, the Internet of Things, and interference cancelation. He received the Best Paper Awards, including ICCCAS 2007, ROCKLING 2017, and IEEE ISPAS 2021. He also received the IEEE CESoc/CTSoc Service Awards in 2019, the NSC/MOST Special Outstanding Talent Award in 2021 and 2023, the Excellent Research-Teacher Award in 2018 and 2022, and the Excellent Teaching Award in 2021. Since 2022, he has been the Vice Chair of IEEE CESoc Virtual Reality, Augmented Reality, and Metaverse (VAM).

Title: Affine-projection-like maximum correntropy criteria algorithm for robust active noise control

Abstract: Impulse noise (IN) can seriously degrade the performance of conventional active noise control (ANC) algorithms. Here, we present a novel feedforward ANC algorithm based on an information-theoretic learning framework with the data-reuse scheme of affine-projection-based algorithms. Inspired by the maximum correntropy criterion (MCC), the proposed algorithm is referred to as the modified filtered-x affine-projection-like MCC (MFxAPLMCC). Furthermore, we developed an objective function to maximize the correntropy between the system's desired vectors and the secondary path's output vectors to enhance robustness. Moreover, linear approximation reduces computational complexity, and the optimal step size is derived mathematically to accelerate convergence and increase the noise reduction ratio. The MFxAPLMCC algorithm was thoroughly evaluated in terms of stability and computational complexity; numerical simulations were used to confirm the effectiveness in terms of average noise reduction. The efficiency of our method was verified using three types of input: (1) symmetric alpha-stable (S α S) IN, (2) a mixture of sinusoidal and IN, and (3) in-vehicle engine acceleration noise. We also verified the tracking capability of the adaptive algorithm for a case in which the primary path changes abruptly. Furthermore, the real measured acoustic path for ANC in-ear headphone development was used to validate the proposed method in real environments. The proposed algorithm significantly outperformed comparative ANC algorithms in convergence rate and noise reduction ratio. We also confirmed that the theoretical bound for stable step size coincides with the numerical results. The parameter sensitivity of the MFxAPLMCC was analyzed as well.