Machine Learning Applications in Structural Engineering is a practical guide to machine learning in structural engineering. With first-hand examples of machine learning applications, this book is a vital reference for both entry-level readers and advanced professionals. For experts, the book offers insights into emerging applications that are shaping the future of the discipline, making it a compelling choice for engineers looking to leverage machine learning for smarter, more resilient structural solutions. This accessible style makes complex concepts manageable, and the book offers clear explanations while showcasing the potential of machine learning as a versatile tool for advancing structural engineering practices.
It is aimed at engineers, researchers, and students with an interest in integrating new, machine learning technologies into daily practice. Readers will find a balance of foundational theory with hands-on, data-driven solutions tailored to meet real-world demands.
It is aimed at engineers, researchers, and students with an interest in integrating new, machine learning technologies into daily practice. Readers will find a balance of foundational theory with hands-on, data-driven solutions tailored to meet real-world demands.
Table of Contents
1. Concrete Technology and Machine Learning Applications2. Earthquake Engineering Models with Machine Learning
3. Wind Engineering
4. Steel Structure
5. Structural Health Monitoring and Predictive Maintenance
6. Data Integration and Model Optimization in Structural Engineering
7. Case Studies in Machine Learning for Structural Engineering
Authors
Rahul Biswas Assistant Professor, Applied Mechanics Department, Visvesvaraya National Institute of Technology (VNIT) Nagpur, India. Dr Rahul Biswas is an Assistant Professor in the Applied Mechanics Department at Visvesvaraya National Institute of Technology (VNIT) Nagpur, India. Dr Biswas's primary research interests centre around concrete technology and the utilization of sustainable materials in concrete. Additionally, he is actively involved in exploring the application of machine learning in the field of structural engineering Pijush Samui Associate Professor, Department of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India.Dr. Samui is an Associate Professor in the Department of Civil Engineering at NIT Patna, India. He received his PhD in Geotechnical Engineering from the Indian Institute of Science Bangalore, India, in 2008. His research interests include geohazard, earthquake engineering, concrete technology, pile foundation and slope stability, and application of AI for solving different problems in civil engineering. Dr. Samui is a repeat Elsevier editor but also a prolific contributor to journal papers, book chapters, and peer-reviewed conference proceedings.
Panagiotis G. Asteris Full Professor, Computational Mechanics Laboratory, School of Pedagogical & Technological Education, Athens, Greece. Professor Asteris received his B.S., M.S., and PhD in Civil Engineering from the National Technical University of Athens, Greece. He is currently a Full Professor and the Head of the Computational Mechanics Laboratory, and the Head of the Civil Engineering Department of the School of Pedagogical and Technological Education, Athens. Prof. Asteris is a trailblazer in the field of computational structural engineering. His research spans diverse areas, including artificial neural networks, soft computing, applied and computational mathematics, and masonry materials and structures. He is also the editor-in-chief of two international scientific journals and a member of the editorial board of more than ten international journals.
