Proceedings of the 5th International Conference on Sustainability in Civil Engineering - Volume 2 (eBook, PDF)

ICSCE 2024, 23-25 October, Hanoi, Vietnam
Redaktion: Thanh, Nguyen-Viet; De Roeck, Guido; Nguyen-Quang, Tuan; Bui-Tien, Thanh; Nguyen-Ngoc, Long

• Format: PDF

Produktbeschreibung

This book contains the proceedings of the 5th International Conference on Sustainability in Civil Engineering, ICSCE 2024, held on October 23-25, 2024, in Hanoi, Vietnam. It presents the expertise of scientists and engineers in academia and industry in the field of bridge and highway engineering, construction materials, environmental engineering, engineering in Industry 4.0, geotechnical engineering, structural damage detection and health monitoring, structural engineering, geographic information system engineering, traffic, transportation and logistics engineering, and water resources, estuary, and coastal engineering. This book caters to academics, researchers, industrial practitioners, policymakers who are interested in sustainable development as an indispensable trend in the field of civil engineering.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 412
• Erscheinungstermin: 20. Juni 2025
• Englisch
• ISBN-13: 9789819652068
• Artikelnr.: 74623931

Autorenporträt

Assoc. Prof. Dr. Thanh Nguyen-Viet is a vice dean of the Faculty of Civil Engineering at the University of Transport and Communications, Hanoi, Vietnam. He graduated Ph.D. program in 2012 at Hohai University, China, and he won an outstanding Ph.D. Candidate Award in 2013. Dr. Thanh's research areas are estuary and coastal hydrodynamics, sediment transport, and harbor and inland waterways engineering. He published more than 60 scientific papers, of which 31 papers on Web of Science and Scopus and one book of conference proceedings published by Springer Nature. Dr. Thanh is the principal investigator of two international research projects, four ministerial-level research projects, and three national standards in the field of maritime and inland waterway transport. Prof. Dr. Thanh Bui-Tien is an expert in civil engineering, specializing in structural health monitoring, AI, digital twin, intelligent transportation, and structural damage diagnosis of bridges. He is currently the dean of the Faculty of Civil Engineering at the University of Transport and Communications in Vietnam. He obtained bachelor of engineering degree in bridge engineering from the University of Transport and Communications (UTC) in Vietnam in 2000 and his Ph.D. in civil engineering from the University of New South Wales (UNSW), Australia, in 2007. He has held academic positions at various institutions, including lecturing at UNSW and UTC and postdoctoral research at Université de Liège and KU Leuven. Prof. Thanh has published numerous papers in peer-reviewed prestigious journals and has contributed to many conferences and seminars around the world. Assoc. Prof. Dr. Tuan Nguyen-Quang, the vice dean of the Faculty of Civil Engineering at the University of Transport and Communications, Vietnam, specializes in the behavior of materials and structures, new construction materials, and technologies. He graduated from this university in 2006 and later earned a master's degree in 2007 and a Ph.D. in 2011 from Ecole Nationale des Travaux Publics de l'Etat (ENTPE) in France. With over 15 years of research experience in transport construction materials, especially asphalt mixtures, he has contributed significantly to the field. Since 2016, he has been a member of the editorial board for the Road Materials and Pavement Design Journal. Assoc. Prof. Dr. Tuan Nguyen-Quang has authored 80 scientific papers in both national and international journals and two scientific books. Prof. Nguyen Ngoc Long is a people's teacher of Vietnam and former president of the University of Transport and Communications, Vietnam. Prof. Long, with over 40 years of experience in civil engineering, has made significant contributions to the field, particularly in bridge engineering, structural health monitoring, and damage detection through vibration analysis. He leads multiple research activities spanning a broad spectrum of domains and has been instrumental in advancing both theoretical and practical aspects of infrastructure engineering. Since 2018, professor Long has chaired the International Conference on Sustainable Civil Engineering (ICSCE), fostering global collaboration and knowledge exchange in civil engineering. He also serves as the main coordinator for numerous national and international projects focusing on the construction and maintenance of bridges, further demonstrating his expertise and leadership in the field. Emeritus Prof. De Roeck is currently affiliated with the Department of Civil Engineering, Section Structural Mechanics at Katholieke Universiteit Leuven (KU Leuven), Belgium. He got a Ph.D. in structural mechanics from KU Leuven in 1975, and he received his doctor of science degree in 1981. Prof. De Roeck has published thousands of papers. He is a senior specialist in the field of structural health monitoring, static and dynamic analysis of mechanical structures, structure damage detection, dynamic system identification, soil interaction with structures, nonlinear constitutive soil models, and composite materials.

Inhaltsangabe

Air Quality Prediction Using Deep Learning Approaches.- Utilizing Accelerometer Data and LSTM Model for Road Surface Detection.- Air Passenger Forecasting: Leveraging the Power of Autoregressive Models.- Performance Of Machine Learning For Predicting Load-Carrying Capacity Of Nonlinear Steel Trusses.- Evaluating Regression And Classification Surrogate Models For Sizing Optimization Of Nonlinear Steel Trusses.- Fuzzy Structural Analysis using Rao-kNNC-based Approach.- Multi-objective optimization of I-shaped steel plate girders using NSGA-II.- Using Classification and ANN Model to Predict Slump and Compressive Strength of Normal and High-Early Strength Concrete: A Study at a Concrete Batching Plant in Binh Thuan, Vietnam.- Application of Long Short-Term Memory Networks in Bridge Damage Detection.- An effective damage detection approach for a truss bridge using a hybrid deep learning model.- etc.