Akademibokhandeln
Jamal A. Abdalla, M. Z. Naser - Artificial Intelligence and Machine Learning in Structural Engineering and Materials, Häftad

Häftad, Engelska, 2027

Del i serien Woodhead Publishing Series in Civil and Structural Engineering

Artificial Intelligence and Machine Learning in Structural Engineering and Materials

Av Jamal A. Abdalla, M. Z. Naser

3099 kr

Kommande

Beskrivning

Artificial Intelligence and Machine Learning in Structural Engineering and Materials explores the profound potential of AI and ML to revolutionize the way structural systems and materials are designed, analyzed, and maintained, unlocking new possibilities for precision, adaptability, and optimization.

The book’s detailed chapters cover a wide range of topics, offering both fundamental knowledge and cutting-edge insights into the integration of these sophisticated technologies. Key areas include structural health monitoring, response and behavior of structural systems under various loads, strengthening, retrofitting, and design enhancement, as well as evaluation of the mechanical properties, durability, sustainability, and resilience of the materials employed. Additionally, the book examines AI and ML applications in reliability, risk, and lifecycle analysis, along with the prediction of structural interactions with environmental factors like wind, fluid, soil, fire, and extreme natural hazards.

This work goes beyond a technically sound and thorough research reference resource, blending data-driven models with traditional engineering methods to refine existing practices, while providing clear, actionable techniques for advancing engineering solutions through the strategic uptake of innovations. Readers are presented with a structured overview of how these tools can fundamentally transform the field, emphasizing their capacity to drive efficiency, lower costs, increase safety, and promote long-term environmental viability.



  • Introduces the most popular ML methodologies, including but not limited to, commonly used supervised learning algorithms in regression, classification, and deep learning
  • Delivers a state-of-the-art and state-of-practice review, as well as the current research developments in AI and ML for structural engineering and materials
  • Provides a standardized framework, guidelines, and a design reference for effectively integrating AI and ML into structural engineering and materials applications
Produktinformation
Utforska kategorier
Mer information

Jamal A. Abdalla holds a bachelor's degree in Civil Engineering from the University of Khartoum (Sudan), a master's degree from Purdue University, and a PhD from the University of California, Berkeley, followed by postdoctoral research at Stanford University. He is a professor of Civil Engineering at the American University of Sharjah (AUS) in the United Arab Emirates. Before joining AUS, Dr. Abdalla held academic positions at Qatar University and the University of Khartoum. His research spans a wide range of areas, including computing in civil engineering, the strengthening and retrofitting of reinforced concrete structures, the application of Artificial Intelligence (AI) and Machine Learning (ML) in structural engineering, and sustainable construction materials. Dr. Abdalla has served as an Associate Editor for the ASCE Journal of Computing in Civil Engineering and currently sits on the editorial boards of several academic journals. Throughout his career, he has conducted workshops, delivered seminars, organized conferences, and served on numerous technical committees. Additionally, he has been actively involved in reviewing papers for both journals and conferences. Dr. Abdalla is a Fellow of both the American Society of Civil Engineers (ASCE) and the Structural Engineering Institute (SEI), and is a registered professional engineer in the State of Virginia, USA. M. Z. Naser is a tenure-track associate Professor at the Department of Civil and Environmental Engineering and Earth Sciences and a member of the Artificial Intelligence Research Institute for Science and Engineering (AIRISE) at Clemson University. At the moment, his research group is creating causal & eXplainable machine learning methodologies to discover new knowledge hidden within systems belonging to the domains of structural engineering and materials science to help realize functional, sustainable, and resilient infrastructure. He is currently serving as the chair of the ASCE Advances in Information Technology committee and on a number of international editorial boards, as well as codal building committees (in ASCE, ACI, PCI, and FiB). He is a registered professional engineer in the states of Michigan and South Carolina.

Butikslager

Ej i lager i butik.

Betyg & recensioner

0 recensioner

Inga recensioner tillgängliga.

Mer från samma serie