Empirical Seismic Vulnerability and Resilience Assessment of Building Clusters

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  • Empirical Seismic Vulnerability and Resilience Assessment of Building Clusters Book Detail

  • Author : Si-Qi Li
  • Release Date : 2024-03-18
  • Publisher : Elsevier
  • Genre : Technology & Engineering
  • Pages : 623
  • ISBN 13 : 0443216398
  • File Size : 84,84 MB

Empirical Seismic Vulnerability and Resilience Assessment of Building Clusters by Si-Qi Li PDF Summary

Book Description: Empirical Seismic Vulnerability and Resilience Assessment of Building Clusters analyzes the seismic vulnerability analysis of four types of structures and studies and discusses the evaluation of structural damage using risk analysis and shaking table test methods. It does not consider the contribution of typical empirical structural seismic damage data to structural vulnerability assessment and prediction. It is recognized that the impact of earthquakes on large-scale areas is extensive, not only on a building but also on a group of buildings. The book is based on the research background of typical seismic damage characteristics of 11 types of engineering structures. It analyzes the characteristics of the vulnerability of various structures and provides measures and methods to improve the vulnerability of various structures. Combined with probability risk, reliability, machine learning, and other means, vulnerability prediction and evaluation models are established, respectively, and the rationality of the models is verified by hundreds of onsite earthquake damage survey data. Increases engineers' theoretical and practical knowledge of field investigation to help improve their efficiency and the quality of future work Includes the analysis of hundreds of earthquake field survey data Provides a vulnerability assessment of diversified structural experience

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Seismic Vulnerability of Structures

Seismic Vulnerability of Structures

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This book is focused on the seismic vulnerability assessment methods, applied to existing buildings, describing several behaviors and new approaches for assessm