Resilience-based decision framework to determine performance targets for the built environment, A

2018 Spring.Includes bibliographical references.Current design codes and standards focus on the design of individual facilities. A typical building is designed with the objective of the life safety of occupants. Even performance-based design approaches assess the required physical performance of an individual structure in order to satisfy prescribed criteria for that structure individually. Thus, even these performance objectives are likely not sufficient for a broad view of community-resilience goals. A modern community is made up of highly coupled networks, and disruptions within one or more networks may lead to disruptions to other networks. If a large number of buildings within a community become non-functional for a long time following an event, either because of physical damage or loss of utilities such as electric power and/or water, the consequences may affect other parts of the community such that, eventually, significant socioeconomic losses occur. Therefore, the current approach for designing individual physical components within a community can be reimagined such that it not only takes into account the performance of a component individually after a catastrophic event but also considers the consequences its design has on a community. The main purpose of this dissertation is to develop a methodology that links the performance of components within the built environment to community-level resilience goals by considering the dependencies and cross-dependencies between components and networks. Therefore, ultimately, this methodology enables disaggregation of the community-level objectives into a set of performance targets for the components of the built environment, which leads itself to the needs of policymakers and community leaders in order to make long-term planning decisions for a community

Predictive and Prescriptive Analytics for Managing the Impact of Hazards on Power Systems

Natural hazards and extreme weather events have the potential to cause significant disruptions to the electric power grid. The resulting damages are, in some cases, very expensive and time-consuming to repair and they lead to substantial burdens on both utilities and customers. The frequency of such events has also been increasing over the last 30 years and several studies show that both the number and intensity of severe weather events will increase due to global warming and climate change. An important part of managing weather-induced power outages is being properly prepared for them, and this is tied in with broader goals of enhancing power system resilience. Inspired by these challenges, this thesis focuses on developing data-driven frameworks under uncertainty for predictive and prescriptive analytics in order to address the resiliency challenges of power systems. In particular, the primary aims of this dissertation are to: 1. Develop a series of predictive models that can accurately estimate the probability distribution of power outages in advance of a storm. 2. Develop a crew coordination planning model to allocate repair crews to areas affected by hazards in response to the uncertain predicted outages. The first chapter introduces storm outage management and explains the main objectives of this thesis in detail. In the second chapter, I develop a novel two-stage predictive modeling framework to overcome the zero-inflation issue that is seen in most outage related data. The proposed model accurately estimates customer interruptions in terms of probability distributions to better address inherent stochasticity in predictions. In the next chapter, I develop a new adaptive statistical learning approach based on Bayesian model averaging to formulate model uncertainty and develop a model that is able to adapt to changing conditions and data over time. The forth chapter uses Bayesian belief network to model the stochastic interconnection between various meteorological factors and physical damage to different power system assets. Finally, in chapter five, I develop a new multi-stage stochastic program model to allocate and relocate repair crews in impacted areas during an extreme weather event to restore power as quickly as possible with minimum costs. This research was conducted in collaboration with multiple power utility companies, and some of the models and algorithms developed in this thesis are already implemented in those companies and utilized by their employees. Based on actual data from these companies, I provide evidence that significant improvements have been achieved by my models.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168024/1/ekabir_1.pd

Résilience systémique d’un territoire composé d’activités essentielles suite à une perturbation majeure – Approches systémique et spatiale

Too many dramatic events occurred over the last ten years have demonstrated the severity and extent of impacts that territories may be confronted with. Damages to critical infrastructures may have a variety of downfall disturbing effects, which can lead territories and society into a huge crisis. Interdependency between these essential activities on the one hand, and between these activities and the population on the other hand, increases their vulnerability. This thesis presents a methodology to better assess direct and indirect impacts of a major disturbance. The issue is addressed from a multi-activity perspective, to take into account territories complexity.In the first stage, a territory is modeled using existing interdependency links between essential activities and the population. The methodology then identifies, based on a defined initial event, possible propagation scenarios and their consequences on services “users”. Finally, this simulation gives an assessment of the territory stakes resilience. This works provides a decision-making tool for the development of activity continuity plans, or risk assessment and mitigation policies.De trop nombreux évènements survenus la décennie passée illustrent la gravité et l’étendue des impacts auxquels les territoires peuvent être confrontés. L'atteinte aux infrastructures critiques peut induire de très nombreux dysfonctionnements en cascade pouvant plonger ce territoire et sa société dans une crise de grande ampleur. Les interdépendances entre ces activités essentielles et celles avec la population accentuent leur fragilité. Afin d'évaluer les impacts directs et indirects d'une perturbation majeure, la méthodologie développée étudie la problématique sous un angle multisectoriel répondant ainsi à une prise en compte de la complexité des territoires. Dans un premier temps, le territoire via ses activités essentielles et sa population est modélisé en s'appuyant sur les liens d'interdépendance existants. Sur la base d'un évènement initial donné, la méthode identifie les scénarios de propagation possibles et leurs conséquences sur les "usagers" concernés par la délivrance des services touchés. Cette simulation permet ainsi d'apprécier la résilience systémique des enjeux du territoire. Basé sur une approche systémique et spatiale, ce travail a pour objectif de fournir une aide à la décision à la planification des mesures de continuité et de rétablissement d'activité ou à la mise en place de mesures de traitement des risques