Beschreibung:
This book gathers peer-reviewed contributions presented at the 3rd International Conference on Structural Engineering and Construction Management (SECON'22), held in Angamaly, Kerala, India, on 1-3 June 2022. The meeting served as a fertile platform for discussion, sharing sound knowledge and introducing novel ideas on issues related to sustainable construction and design for the future. The respective contributions address various aspects of numerical modeling and simulation in structural engineering, structural dynamics and earthquake engineering, advanced analysis and design of foundations, BIM, building energy management, and technical project management. Accordingly, the book offers a valuable, up-to-date tool and essential overview of the subject for scientists and practitioners alike, and will inspire further investigations and research.
This book gathers peer-reviewed contributions presented at the 3rd International Conference on Structural Engineering and Construction Management (SECON’22), held in Angamaly, Kerala, India, on 1-3 June 2022. The meeting served as a fertile platform for discussion, sharing sound knowledge and introducing novel ideas on issues related to sustainable construction and design for the future. The respective contributions address various aspects of numerical modeling and simulation in structural engineering, structural dynamics and earthquake engineering, advanced analysis and design of foundations, BIM, building energy management, and technical project management. Accordingly, the book offers a valuable, up-to-date tool and essential overview of the subject for scientists and practitioners alike, and will inspire further investigations and research.
Chapter 1: PALFNet: A Soil Erosion Control Geotextile using Pineapple Leaf Fiber.- Chapter 2: Vulnerability Assessment of a Core Shelter: Basis for Development of a Flood and Wind Map.- Chapter 3: Effect of Openings in Post-Tensioned Shear Wall with External Energy Dissipating Reinforcements Under Cyclic Loading.- Chapter 4: Prediction of Compressive Strength and Workability Characteristics of Self-Compacting Concrete Containing Fly Ash Using Artificial Neural Network.
