Special Collection on Resilience Quantification and Modeling for Decision Making

Although substantial progress has been made in science and technology toward improved performance of the built environment, natural disasters, acts of terrorism, infectious diseases outbreaks, and social unrest have persistently been responsible for loss of life, disruption of commerce and financial networks, damaged property, and loss of business continuity and essential services during the last two decades. Many physical infrastructures are vulnerable to natural hazards (e.g., along coastlines and in earthquake-prone regions) as well as human-made hazards, and the risk across the world of damage due to hazardous events continues to increase. Major research activities on resilience-based engineering have been supported and coordinated by large research groups and networks. However, even with this progress, the engineering community is facing many new challenges. During 2018 alone at least 300 disasters related to natural hazards were reported worldwide, reminding us that destructive events still threaten the lives of millions, and the property, social structure, and economic well-being of individuals, communities, and countries all over the world. Today, the main question is how do we use resilience-based seismic engineering to steward our built environment and make it safer, more resilient, and more sustainable in the future? The aim is to develop a common global vision for resilience-based design, while recognizing unique regional traditions. It is the objective of this special collection to present and assess strategies on how to improve community resilience against a major event. This special collection compiles a set of original papers by academics and professionals at the forefront of resilience quantification and design today. The contributions are six: (1) Ceferino et al. (2018) focuses on a probabilistic approach to measure the casualties due to earthquakes; (2) Bruneau and Reinhorn (2019) expressed their opinion about resilience based on their experience on decades of research at Multidisciplinary Earthquake Engineering Research Center (MCEER); (3) Emanuel and Ayyub (2019) have developed resilience models incorporating stakeholder preferences using four fundamental system performance and stakeholder preference models; (4) Kammouh et al. (2019) present an indicator-based method for measuring urban community resilience that is based on the PEOPLES framework; (5) Tabandeh et al. (2019) present a probabilistic model to predict the broad societal impact of disruptive events over time in terms of their impact on the well-being of individuals; and (6) Nocera et al. (2019) present a probabilistic formulation to predict the recovery process of a system based on past recovery data to assess the probability of exceeding a target value of functionality at any time.

Overall, the collection of papers offers new, forward-looking ideas for community resilience, including decision-making support, probabilistic models of recovery, socioeconomic quantification models and system-level logic. Collectively, they point to interdisciplinary efforts to formulate new approaches and metrics that jointly consider pre-event and during-event performance along with postevent functionality goals using a probabilistic approach and stakeholder preference models.

The research leading to these results has received funding from the European Research Council under the Grant agreement no. ERC_IDEal reSCUE_637842 of the project Integrated Design and control of Sustainable Communities during Emergencies (IDEAL RESCUE). The guest editors would like to thank the SHMII Committee on Resilient Structures and Infrastructure (CORSI) of the International Society for structural Health Monitoring of Intelligent Infrastructures that sponsored this special collection and all the authors for their ideas, rigor, and continued commitment. The contributions in this special collection are timely in practice, thus empowering professionals, academics, and communities at large to improve resilience.