主题：Conducting fracture state characterization through a computational algorithm

主讲人：Prof. Louis Wong，the University of Hong Kong

时间：2024年7月14日上午10:00-11:30

地点：太阳成集团tyc234cc主页南414室

邀请人：吴志军教授

报告摘要：

Digital technologies have great potential to improve capabilities and efficiency in geotechnical work. Geologists often spend considerable time logging rock cores and creating investigation records, which are vital for engineering practices. A project at the University of Hong Kong (HKU) is leveraging advances in AI and mobile devices to develop a web-based application that aids rock core logging, potentially transforming geotechnical practice. This seminar will focus on creating a computational algorithm that automatically determines the fracture index (FI) of core runs using fracture spacing data. The primary evaluation indicator is the variance of fracture spacing values. The algorithm automatically groups fractures seen in core images, considering the uniformity of fracture spacing when calculating the FI. The anticipated research outcomes aim to enhance routine core logging practices, which are presently performed manually and prone to human errors.

主讲人简介：

Prof. Wong serves as the Associate Head (Research) of the Department of Earth Sciences at HKU. He holds a PhD in geotechnical engineering from MIT and a BSc in Earth Sciences from HKU. His experience spans various slope engineering and underground construction projects in Hong Kong, Singapore, and the United States. He has authored over 130 journal articles in engineering geology, rock mechanics, and underground engineering (Google Scholar Citation > 11k, H-index 58).  Prof. Wong ranks among the top 1% of researchers globally in his field based on citations. He has received multiple awards, delivered keynote lectures at international conferences, and was honored with the prestigious Richard Wolters' Prize in 2014 by the International Association of Engineering Geology and the Environment. Since 2018, Prof. Wong has served as the Editor-in-Chief of the Bulletin of Engineering Geology and the Environment. His current research focuses on developing predictive models for thermo-hydro-mechanical (THM) coupling processes in underground fire engineering and utilizing AI technologies to enhance engineering geological practices.

Refer to the Google Scholar link below for his publications (https://scholar.google.com.hk/citations?user=j_BFCYsAAAAJ&hl=en )