The goal to improve the resilience of social systems – communities and their economies – is increasingly adopted by decision makers. This unique and comprehensive Handbook focuses on the interdependencies of these social systems and the technologies that support them. Special attention is given to the ways in which resilience is conceptualized by different disciplines, how resilience may be assessed, and how resilience strategies are implemented. Case illustrations are presented throughout to aid understanding.

This book provides basics and selected advanced insights on how to generate reliability, safety and resilience within (socio) technical system developments. The focus is on working definitions, fundamental development processes, safety development processes and analytical methods on how to support such schemes. The method families of Hazard Analyses, Failure Modes and Effects Analysis and Fault Tree Analysis are explained in detail. Further main topics include semiformal graphical system modelling, requirements types, hazard log, reliability prediction standards, techniques and measures for reliable hardware and software with respect to systematic and statistical errors, and combination options of methods. The book is based on methods as applied during numerous applied research and development projects and the support and auditing of such projects, including highly safety-critical automated and autonomous systems. Numerous questions and answers challenge students and practitioners.

There has not yet been a comprehensive method that goes behind 'human error' and beyond the failure concept, and various complicated accidents have accentuated the need for it. The Functional Resonance Analysis Method (FRAM) fulfils that need. This book presents a detailed and tested method that can be used to model how complex and dynamic socio-technical systems work, and understand both why things sometimes go wrong but also why they normally succeed.

Presenting critical insights on how economic activity is constrained by the environment’s ability to provide material and energy resources, this timely Research Agenda explores how humanity shapes, and is shaped by, environmental change and sustainability challenges. Chapters highlight how, under these constraints, people may seek to improve their lives and standards of living without undermining the abilities of others to do so now or in the future.

This handbook aims at modernizing the current state of civil engineering and firefighting, especially in this era where infrastructures are reaching new heights, serving diverse populations, and being challenged by unique threats. Its aim is to set the stage toward realizing contemporary, smart, and resilient infrastructure. The Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures draws convergence between civil engineering and firefighting to the modern realm of interdisciplinary sciences (i.e., artificial intelligence, IoT, robotics, sensing, and human psychology). As such, this work aims to revolutionize the current philosophy of design for one of the most notorious extreme events: fire. Unlike other publications, which are narrowed to one specific research area, this handbook cultivates a paradigm in which critical aspects of structural design, technology, and human behavior are studied and examined through chapters written by leaders in their fields. This handbook can also serve as a textbook for graduate and senior undergraduate students in Civil, Mechanical, and Fire Protection engineering programs as well as for students in Architectural and social science disciplines. Students, engineers, academics, professionals, scientists, firefighters, and government officials involved in national and international societies such as the American Society of Civil Engineers (ASCE), Society of Fire Protection Engineers (SFPE), National Fire Protection Association (NFPA), and Institute of Electrical and Electronics Engineers (IEEE), among others, will benefit from this handbook.

Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.

The systems that surround us are often multidimensional, and complex, consisting of a large collection of networked components with convoluted connections between them. Designing and managing such systems can be challenging, particularly in organizations. Designing and Managing Complex Systems introduces readers to the theory of complex systems, examining the role of human within larger systems, the factors that affect system performance, and how such systems can be optimized. The first section reviews the history of one particularly fruitful approach to complexity, one based on knowledge of the human nervous system. Next, the author discusses the current understanding of complex systems in a variety of domains including physical, biological, mechanical, and organizational. Within these chapters the author also introduces the idea that there are marked similarities in how complexity is successfully managed across these different domains and how the ideas from one domain can be useful in other domains. Next, these ideas are synthesized into a framework for successfully designing and managing complex systems. The fourth section focuses on case studies concerning failures and successes within complex systems. - Provides an overview of the background and scope of complexity science - Reviews current understanding of complex systems in a variety of domains (physical, biological, mechanical, and organizational) - Introduces the idea of using successful techniques from one domain to help design and manage complex systems in other domains - Includes case studies analysing failures and successes within complex systems