The safety and serviceability of in-service structures and infrastructure systems are often threatened by natural hazards. Owners and decision makers are especially concerned about the resilience of an asset (structure or infrastructure), namely its ability to be in readiness for, to absorb, recover from, and adapt to disruptive events. Climate change is increasingly producing nonstationary natural hazards such as wind hazards, and concurrent multiple hazards may result in especially severe performance reduction. This book focuses on hazard modelling and resilience methods, and their application in engineering cases. It presents the state of the art of the theory, methodology, and applications related to infrastructure resilience, and offers practical approaches to enhancing resilience for engineers, policy makers, and researchers.
Climate change generates new nonstationary natural hazards and severe concurrent multiple hazards This focuses on hazard modelling and resilience methods, and their applications, presenting the theory, methodology, and practical applications for engineers, policy makers, and researchers.
Chapter 1 Introduction
Chapter 2 Sustainable Climate Resilience for Critical Energy Infrastructure
in Developing Countries: Needs and Challenges
Chapter 3 Climate-resilient structures and infrastructures: hazards, methods,
and applications
Chapter 4 Navigating new waters: ensuring cyber and climate resilience in
industrial water systems
Chapter 5 Unpacking The BLACK Box of Enabling Infrastructure Resilience to
Climate Change: Time to Address the Soft Elements of Organisations for
Ensuring Better Decisions
Chapter 6 Adapting Infrastructure to a Changing Climate with Extreme Event
Attribution Assessments
Chapter 7 Hazard and Risk Assessment in Nonstationary Environments for
Engineering Applications
Chapter 8 Climate Impact Analytics for the US Freight Rail Network: Extreme
Temperatures as a Case Study
Chapter 9 Disaster Recovery Modeling for Residential Buildings and Its Policy
Implications
Chapter 10 Fragility Assessment of Building Portfolios under Natural Hazards
Using Machine Learning and Poisson Binomial Distribution
Chapter 11 Predictive modelling of hail impact damage on toughened glazing
panels
Chapter 12 Performance modelling of aluminium building cladding under hail
hazards
Chapter 13 The Impact of Climate Change on Maritime Transport and Port
Infrastructure Resilience
Chapter 14 Machine Learning-Driven Resilience Assessment: Integrating Dynamic
Bayesian Networks and Machine Learning for Predicting Critical Infrastructure
Resilience Against Disasters
Chapter 15 Optimizing Hurricane Evacuation Decisions Under Climate Change
Chapter 16 Adoption of Green Building Strategies: A Case of Enhancing
Infrastructure and Superstructure Resilience in Zimbabwe
Cao Wang is Senior Lecturer and ARC DECRA Fellow at the University of Technology Sydney, Australia. He is a member of the Committee on Probability and Statistics in the Physical Sciences (C(PS)2) and the Bernoulli Society for Mathematical Statistics and Probability.
Bilal M. Ayyub is Professor and Director of the Center for Technology and Systems Management at the University of Maryland, USA. He is a distinguished member of ASCE, an honorary member of ASME, and a co-chair of the ASCE-NOAA Task Force on Climate Resilience in Engineering Practice, and he has chaired the ASCE Committee on Adaptation to a Changing Climate.
Michael Beer is Professor and Head of the Institute for Risk and Reliability, Leibniz Universität Hannover, Germany. He is also part-time Professor at the University of Liverpool and guest Professor at Tongji University and Tsinghua University, China. He is the Chairman of the European Safety and Reliability Association (ESRA) and serves on the Executive Board of the International Safety and Reliability Association (IASSAR), on the Executive Board of the European Association of Structural Dynamics (EASD), and on the Board of Directors of the International Association for Probabilistic Safety Assessment and Management (IAPSAM). He is a fellow of the Alexander von Humboldt-Foundation.
