EAGER: SSDIM: Data Simulation to Support Interdependence Modeling in Emergency Response and Multimodal Transportation Networks

获取相互依存的关键基础设施（ici）的设计和操作数据现在被认为是开发新的数据分析、设计和决策支持工具的关键。这个探索性研究（EAGER）项目的早期概念资助将通过开发新的数据创建技术和基于模型的方法来模拟ici数据以及人类对ici的认知和/或行为，从而创建并提供ici的合成和模拟数据。它将为多式联运、应急服务、野火和传染病等广泛领域的研究界提供工具，对涉及人类活动和决策的复杂综合决策系统进行建模。将为州和地方交通官员举办有关这些工具的研讨会，以帮助这些利益相关者设计、分析和改进多式联运系统，防止中断和故障。这些新知识将通过基础设施风险管理、应用统计、可靠性工程和时空计算等领域的期刊和会议广泛传播。此外，有业绩记录的pi将促进跨学科教育，招募代表性不足的学生以保持劳动力多样性，并让K-12教师和学生接触尖端研究经验。本项目研究了一种用于集成电路拓扑和数据生成的方法。该研究将(1)创建一个两层框架，该框架集成了异构数据，以对ici的复杂拓扑进行建模，反之亦然；(2)模拟目标综合投资机构的数据，并公开提供这些数据，以评估和改进应急事件的准备工作；(3)论证利用框架和数据确定提高综合投资机构复原力的应急服务可行方案的可行性。为了确保拟议的两层框架充分植根于工程实践，该项目将重点关注国土安全部确定的三个综合信息系统，包括内陆水道（主要水道沿岸的港口、水坝和水闸）、连接或靠近内陆水道的地面运输系统以及应急服务。

Access to data on the design and operation of interdependent critical infrastructures (ICIs) is now recognized as essential for developing new data analytic, design and decision-support tools. This EArly-concept Grant for Exploratory Research (EAGER) project will create and make available synthetic and simulated data on ICIs by developing new data creation techniques and model-based approaches to simulating data on ICIs and human cognition and/or behavior with ICIs. It will provide research communities in broad areas, such as multimodal transportation, emergency services, wildfire and infectious disease, with tools for modeling complex ICIs involving human activities and decisions. Seminars on these tools will be offered to state and local transportation officials to assist these stakeholders in designing, analyzing and improving multimodal transportation systems against disruptions and failures. The new knowledge will be broadly disseminated through journals and conferences in the areas of infrastructure risk management, applied statistics, reliability engineering, and spatiotemporal computation. Moreover, the PIs with track records will promote interdisciplinary education, recruit underrepresented students for maintaining workforce diversity, and expose K-12 teachers and students to cutting-edge research experiences.This project investigates a methodology for topology and data generation for ICIs. The research will (1) create a two-layer framework that integrates heterogeneous data to model the complex topology of ICIs and vice versa; (2) simulate data for targeted ICIs and make the data publicly available for evaluating and improving the preparedness for emergency events; and (3) demonstrate the feasibility of using the framework and data to determine the viable options of emergency services for resilience improvement of ICIs. To ensure that the proposed two-layer framework is well rooted in engineering practice, the project will focus on three ICIs identified by the Department of Homeland Security, including inland waterways (ports, dams and locks along major waterways), ground transportation systems that are connected or close to the inland waterways, and emergency services.