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

自然灾害工程的研究，以及更广泛地说，灾害科学的研究，寻求发展一门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进行的，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进行合作，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。计算在灾害科学研究中被广泛应用于各个学科。因此，计算建模可以作为一种共同的语言来连接学科。该项目计划的综合计算平台将作为这一纽带。用户将能够将多个学科的单独计算模型和模拟连接到平台上，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。以最小的努力与其他模型无缝连接的能力将促进传统上不一起工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成为可能，从而产生新的贡献。具体来说，在这个项目中，将对政策、伤亡率和社区复原力之间复杂的相互作用产生新的理解。这将有助于决策者确定需要哪些政策变化，以显著影响一个社区对自然灾害的复原力水平。该项目还将有助于提高劳动力的技能。参与该项目的学生将获得真正的土木工程、社会科学和计算机科学交叉的多学科教育。这些学生将获得的独特技能将使他们对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，这个项目既服务于美国国家科学基金会的科学使命，也服务于培养具有科学意识的劳动力的使命。极端的自然灾害，如地震和飓风，可以触发社会关键基础设施系统之间复杂的相互依赖关系，包括建筑环境（如建筑物和桥梁）、社会组织要素（如社会力量和凝聚力）和制度安排（如政策、政治、经济和减灾）。通过采用一套已建立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联系在一起，以研究基础设施相互依赖对社区恢复力的影响。这些相互依存关系是复杂而动态的；例如，在飓风中，社区的每座建筑都是人们的避难所，同时也是风载导弹的潜在目标和来源。由于这个问题具有广泛的跨学科性质，并且缺乏以综合方式研究它们的工具，过去没有对相互依赖进行充分的研究。这个项目将解决这个问题。此外，将根据基础设施稳健性、社会组织和政策之间的相互作用来评估社区恢复能力。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功能，虽然它们取决于事件发生前的有效政策，但它们也会影响未来的政策。通过将本研究中开发的工具作为案例研究应用于地震和飓风情景，将对政策（特别是在过去几十年中政策的演变）、成本、伤亡率和社区复原力之间的相互作用进行建模，目的是寻求对其复杂相互作用的新见解。这些研究将探讨需要在多大程度上实施政策变化，才能显著影响一个社区的复原力水平。量化这些值将使最具成本效益的变化得以精确定位，从而有助于指导未来针对恢复力的政策变化。他们还将允许对复杂的社区恢复力问题中的涌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.