Geotechnical Modeling and Intelligent Systems - Tapa dura

Acerca del autor

Dr. Gaofeng Zhao, Professor at Tianjin University's School of Civil Engineering, is a leading expert in computational geomechanics. He earned his Ph.D. from EPFL, Switzerland, and was formerly a senior lecturer at The University of New South Wales, Australia. Dr. Zhao developed NumericalBox3D, a high-performance simulation software widely applied in rock engineering. His contributions to the Distinct Lattice Spring Model (DLSM) and Four-Dimensional Lattice Spring Model (4D-LSM) have advanced applications in underground engineering and material science. With over 100 SCI-indexed publications and an H-index of 33, he is recognized as a Stanford Top 2% Global Scientist. He serves as Associate Editor for the International Journal of Rock Mechanics and Mining Sciences (IJRMMS) and Intelligent Geoengineering (IGEO). Additionally, he is the President of the Commission on Discontinuous Deformation Analysis of the International Society for Rock Mechanics and Rock Engineering (ISRM) and the Deputy Director of the Artificial Intelligence Committee of the Chinese Society for Rock Mechanics and Engineering (CSRME). Dr. Zhao has received numerous awards, including the Qian Qihu Award from CSRME, the First-Class Natural Science Award from China’s Ministry of Education, Australia’s Discovery Early Career Researcher Award (DECRA), among others.

De la contraportada

This open access book provides insights into research topics related to geotechnical engineering simulations. With the development of computing power and artificial intelligence, research methods in geotechnical engineering are gradually shifting from field surveys and physical experiments toward simulation and prediction. Through simulations, it is possible to infer the impact of engineering structures on soil and rock masses, as well as their response to natural disasters such as earthquakes, landslides, and debris flows, allowing for early planning of mitigation measures.

Inside, readers will find cutting-edge studies on microbial soil stabilization, finite element simulations, centrifuge modeling, and machine learning applications. Topics include advanced material characterization, predictive modeling of tunnels and slopes, AI-enhanced monitoring systems, and risk mitigation strategies for deep excavations and mining subsidence. These contributions illustrate how intelligent systems are optimizing both design and safety across a wide range of geotechnical scenarios.

This volume is an essential resource for researchers, engineers, and graduate students seeking to leverage intelligent technologies for more efficient, accurate, and resilient geotechnical solutions. With its integration of theory, experimentation, and smart modeling, it offers a forward-looking perspective on the future of infrastructure in a rapidly evolving technological landscape.