EFRI-RESIN: Assessing and Managing Cascading Failure Vulnerabilities of Complex, Interdependent, Interactive, Adaptive Human-based Infrastructure Systems

PI姓名：Robert Bea研究所：加州大学伯克利分校提案编号：0836047该奖项是作为研究和创新新兴前沿（NSF 07-579）征集子主题弹性和可持续建筑结构（树脂）的一部分的竞争结果。 该研究项目是一项跨学科的合作研究，旨在创建，验证和应用新的风险评估和管理（RAM）方法，以评估和改进相互依赖的复杂基础设施系统（ICIS）的设计，运营和维护。最近由于卡特里娜飓风造成的大新奥尔良地区ICIS的失败明确表明，人，组织，社会，文化和政治方面的考虑是确保ICIS的可靠性和性能的主要因素。 为了理解和改善ICIS的行为，有必要将物理/环境科学（技术）与社会科学（人类和组织因素）相结合。 研究小组将研究加州萨克拉门托-圣华金三角洲的防洪、配水和供电系统。 这些系统嵌入在一个复杂而敏感的生态系统中。 它们还与其他重要的ICIS共存，如通信，运输和紧急服务。 像美国其他地区的ICIS一样，随着时间的推移，由于老化、维护延迟、社会需求增加和自然灾害，其有效性和性能受到侵蚀。 这项研究的最终目标是了解如何提高ICIS的弹性和可持续性，同时保持其他重要的性能特征，如可服务性，安全性，耐用性和兼容性。这项研究建立在二十多年的跨学科合作研究的基础上，在此期间，研究了600多起涉及ICIS的重大事故和灾害。 过去的研究导致ICIS工程RAM方法的制定和测试。 这项研究解决了下一代RAM方法开发中的两个重要组成部分：（1）ICIS的故障概率P[F]，以及（2）故障后果C[F]。 反过来，P[F]包含两种不同类型的不确定性：（1）内在的（自然的和分析的），P[I]，和（2）外在的（人的和组织的），P[E]。 研究的目标是实现更现实的P[F]和C[F]评估，以确定减轻和控制P[F]和C[F]的新方法，并改善如何将风险信息传递给政策制定者和决策者。该提案的主要智力价值是整合环境、物理和社会科学，为ICIS的有效设计、运行和性能开发全面的RAM方法。这项研究对研究和实践社区以及社会的主要好处是：（1）能够改善ICIS的评估和管理，（2）改善未来工程师的教育，（3）建立先进的地理信息系统（GIS），以实施提高ICIS可靠性和质量所需的技术

PI name: Robert BeaInstitution: University of California-BerkeleyProposal Number: 0836047This award is an outcome of the competition as part of the Emerging Frontiers in Research and Innovation (NSF 07-579) solicitation under the subtopic Resilient and Sustainable Infrastructures (RESIN). The research project is a collaborative interdisciplinary study to create, validate, and apply new Risk Assessment and Management (RAM) methods to assess and improve the design, operation, and maintenance of interdependent complex infrastructure systems (ICISs). The recent failures of ICISs for the Greater New Orleans area due to Hurricane Katrina demonstrate unequivocally that human, organizational, social, cultural, and political considerations are major factors in assuring the reliability and performance of ICISs. To understand and improve the behavior of ICISs, it is necessary to integrate the physical / environmental sciences (technology) with the social sciences (human and organizational factors). The research team will study the California Sacramento - San Joaquin Delta flood protection, water distribution, and power supply systems. These systems are embedded in a complex and sensitive ecosystem. They also co-exist with other important ICISs such as communications, transportation, and emergency services. Like ICISs in other parts of the U.S., their effectiveness and performance have eroded over time due to age, deferred maintenance, increasing societal demands, and natural hazards. The ultimate goal of this research is to learn how to improve the resiliency and sustainability of ICISs, while maintaining other vital performance characteristics such as serviceability, safety, durability, and compatibility. The research builds on more than two decades of collaborative interdisciplinary research during which over 600 major accidents and disasters involving ICISs were studied. The past research has resulted in the formulation and testing of engineering RAM methods for ICISs. This research addresses two vital components in the development of next generation RAM methods: (1) the probability of failure, P[F], of ICISs, and (2) the consequences of failures, C[F]. In turn, P[F] incorporates two different types of uncertainties: (1) Intrinsic (natural and analytical), P[I], and (2) Extrinsic (human and organizational), P[E]. The goals of the research are to achieve more realistic assessments of P[F] and C[F], to identify new means for mitigating and controlling P[F] and C[F], and to improve how risk information is delivered to policy and decision makers. The proposal's primary intellectual merit is the integration of the environmental, physical, and social sciences for the development of comprehensive RAM methods for the effective design, operation, and performance of ICISs. The primary benefits of this research to the research and practice communities, and to society, are to: (1) enable improved assessments and management of ICISs, (2) improve the education of future engineers and, (3) build advanced Geographic Information Systems (GISs) to implement the technologies required to improve the reliability and quality of ICISs