CRISP Type 2: Interdependencies in Community Resilience (ICoR): A Simulation Framework

自然灾害工程学的研究，以及更广泛地说，灾害科学，寻求发展一门关于减轻自然灾害影响的科学。然而，这项研究是由许多高度专业化的学科完成的，每个学科都致力于处理总体挑战的一个子集。现在迫切需要跨学科的研究人员合作，使所做的研究具有整体性，从而为灾害科学中的问题找到全面、完整的解决方案。计算被广泛应用于所有学科的灾害科学研究。因此，计算建模可以用作连接各学科的共同语言。该项目规划的综合计算平台将作为这一纽带。用户将能够将来自多个学科的个人计算模型和模拟连接到该平台，并同时运行它们，以探索自然灾害期间和之后不同社会系统之间发生的复杂相互作用。能够以最小的努力与其他模型无缝对接，将促进传统上不合作的研究人员之间的全新合作，使自然灾害工程和灾害科学领域的新研究得以进行，从而产生新的贡献。具体地说，在这个项目中，新的理解将导致政策、伤亡率和社区复原力之间发生的复杂互动。这将帮助政策制定者确定需要哪些政策变化才能显著影响社区对自然灾害的适应能力。该项目还将有助于培养一支技能更高的劳动力队伍。从事这个项目的学生将在土木工程、社会科学和计算机科学的交叉点上获得真正的多学科教育。这些学生将获得的独特技能将使他们能够为自然灾害工程和灾害科学的未来做出重大贡献，并将他们定位为这些领域的思想领袖。因此，该项目既服务于NSF的科学使命，也服务于其发展一支具有科学意识的工作队伍的使命。极端的自然灾害，如地震和飓风，可以在社会的关键基础设施系统之间引发错综复杂的相互依存关系，包括建成环境(例如，建筑物和桥梁)、社会组织要素(例如，社会力量和凝聚力)以及制度安排(例如，政策、政治、经济和减灾)。通过采用一套既定的软件互操作性标准，将开发一个模拟框架，允许来自不同自然灾害研究子领域的研究人员将他们的模型连接在一起，以研究基础设施相互依赖对社区复原力的影响。这些相互依存关系是复杂和动态的；例如，在飓风中，社区的每一栋建筑都是人们的庇护所，同时也是风载导弹的潜在目标和来源。过去没有充分研究这些相互依存关系，因为这一问题具有广泛的跨学科性质，而且缺乏以综合方式研究它们的工具。这个项目将解决这个问题。此外，还将根据基础设施健壮性、社会组织和政策之间的相互作用来评估社区复原力。基础设施的健壮性直接影响伤亡率。伤亡率是社会组织的直接职能，虽然它们取决于事发前实施的政策，但它们也影响着未来的政策。通过将这项研究中开发的工具应用于地震和飓风情景作为案例研究，将对政策之间的互动(特别是随着它们在过去几十年中的演变)、成本、伤亡率和社区复原力进行建模，目的是寻求对它们复杂互动的新见解。这些研究将探讨需要在多大程度上实施政策变化，以显著影响社区的复原力水平。量化这些价值将使最具成本效益的变化具有针对性，从而有助于指导未来针对复原力的政策变化。它们还将允许对复杂的社区复原力问题的出现进行有纪律的研究，这是一个被认为对所有科学分支都极其重要的跨学科主题。

Research in natural hazards engineering, and, more broadly, disaster science, seeks to develop a science behind mitigating the effects of natural hazards. However, this research is being done by a multitude of highly specialized disciplines, each dedicated to handling a subset of the overall challenge. There is now an urgent need for researchers across disciplines to collaborate, so that the research done is holistic in nature, so as to find comprehensive, complete solutions to the problems in disaster science. Computation is widely used in disaster-science research across all the disciplines. Thus computational modeling may be used as a common language to link the disciplines. This project's planned integrative, computational platform will serve as this link. Users will be able to connect individual computational models and simulations from multiple disciplines to the platform and simultaneously run them to explore the complex interactions that take place between the different systems of society during and after natural hazard disasters. The ability to seamlessly interface with other models with minimal effort will foster entirely new collaborations between researchers who do not traditionally work together, enabling new studies within the natural hazards engineering and disaster science fields, leading to new contributions. Specifically in this project, new understanding will result of the complex interactions that take place between policy, casualty rates and community resilience. This will help policy makers determine what policy changes are needed in order to significantly influence a community's level of resilience to natural disasters. This project will also contribute to a better-skilled workforce. Students who will work on this project will attain a truly multi-disciplinary education at the intersection of civil engineering, social science and computer science. The unique skills that these students will acquire will allow them to make significant contributions to the future of natural hazards engineering and disaster science and position them as thought leaders in these fields. Thus, this project serves both the NSF's science mission as well as its mission to develop a science-aware workforce.Extreme natural hazards, such as earthquakes and hurricanes, can trigger intricate inter-dependencies between the critical infrastructure systems of society, including the built environment (e.g., buildings and bridges), elements of social organization (e.g., social power and cohesion), and institutional arrangements (e.g., policies, politics, economics, and disaster mitigation). By employing an established set of standards for software interoperability, a simulation framework will be developed to allow researchers from different natural hazards research sub-fields to link their models together to study the effects of infrastructure interdependencies on community resilience. These interdependencies are complex and dynamic; e.g. in a hurricane, each building of the community shelters people while being a potential target of and source for wind-borne missiles. The interdependencies have not been adequately studied in the past because of the broadly interdisciplinary nature of the problem and the lack of tools to study them in an integrated manner. This project will address this issue. In addition, community resilience will be assessed in terms of the interactions that arise between infrastructure robustness, social organization, and policy. Infrastructure robustness directly influences casualty rates. Casualty rates are a direct function of social organization, and while they depend on the policies in effect prior to the event, they also influence future policy. By applying the tools developed in this research to seismic and hurricane scenarios as case studies, interactions between policies (especially as they have evolved over the past decades), cost, casualty rates, and community resilience will be modeled with the objective of seeking new insights into their complex interactions. The studies will address the extent to which policy changes need to be implemented to significantly influence a community's level of resilience. Quantifying these values will allow the most cost-effective changes to be pin-pointed and therefore help to direct future changes in policy targeting resilience. They will also allow the disciplined study of emergence in the complex community resilience problem, an interdisciplinary topic recognized as extremely important to all branches of science.