Plenary Lectures

Prof. YuanTong Gu (Queensland University of Technology)

Physics-informed Machine Learning: a powerful computer modelling framework for engineering and science

 

Prof. Jung-Wuk Hong (Korea Advanced Institute of Science and Technology)

Recent Advances in Nonlocal Methods for Computational Mechanics

 

Prof. Michael Kaliske (Technische Universität Dresden)

Theoretical-numerical Approaches to Damage and Fracture Analysis of Structures

 

Semi-Plenary Lectures

Prof. Tsuyoshi Ichimura (The University of Tokyo)

 

Prof. Kiao Inthavong (RMIT University)

Revealing respiratory physiology defence of inhaled airborne particles through multiphase flow simulations

 

Prof. Artem Korobenko (University of Calgary)

Advances in Variational Multiscale Methods for Optimizing Wind and Marine Energy Systems

 

Prof. Xinzheng Lu (Tsinghua University)

Generative-AI Design and Intelligent Optimization of Building Structures

Traditional building structure design methods are inefficient and heavily dependent on engineers' expertise. Emerging generative AI technologies, while promising, require enhancements in the safety and cost-effectiveness of their designs. This study introduces an integrated generative AI and intelligent optimization framework for building structure design. Leveraging generative AI, the intelligent generation algorithm generates feasible design schemes by learning from existing drawings and considering constraints of architectural layout, design conditions, mechanical principles, and empirical rules. Accelerated by data-driven and domain knowledge-enhanced computational models and evaluation functions, the intelligent optimization algorithm refines AI-generated designs swiftly. The proposed method, integrating intelligent generation and optimization, ensures design safety and cost-efficiency, and mitigates the challenges of scarce and poor-quality training data faced by AIs. Case studies demonstrate that the structural designs produced by the proposed method are on par with those of human experts, meeting design criteria and enhancing efficiency. The proposed intelligent design platform has been adopted by over a hundred design and research institutes, impacting thousands of engineering projects.

 

Prof. Akiko Matsuo (Keio University)

 

Prof. Hiroshi Okada (Tokyo University of Science)

 

Prof. Zohar Yosibash (Tel Aviv University)

Autonomous finite element analysis of fracture prediction in human bones applied in clinical practice