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CRISP 2.0 Type 1: Accelerating restoration through information-sharing: Understanding operator behavior for improved management of interdependent infrastructure

CRISP 2.0 类型 1：通过信息共享加速恢复：了解操作员行为以改进相互依赖的基础设施的管理

基本信息

批准号：
1832642
负责人：
Allison Reilly
金额：
$ 75万
依托单位：
University of Maryland, College Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832642&HistoricalAwards=false
关键词：
CRISP 2.0 Type Accelerating restoration

项目摘要

Rapid restoration of infrastructure services following a disaster is fundamental for community recovery. Restoration delays may be created when infrastructure sectors are interdependent and when their operators, potentially lacking knowledge of other systems' conditions and restoration plans, mutually wait for others to act. For interdependent infrastructure recovery, the decisions made by the operators has been overlooked in research, yet it is an important factor in quicker recovery times. To improve recovery of interdependent infrastructure systems, there is a fundamental need to broaden the current perspective to include 1) how individual operators make recovery decisions for their infrastructure systems, and 2) how to improve these decisions. This Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) project compares the effectiveness of a variety of interventions, including information sharing, in reducing restoration times. The project uses interdependent chilled water, information technologies, and electric-power infrastructures at the University of Maryland as an initial case study. To explore the usefulness beyond the case study, a collaboration with a U.S. military installation will evaluate the co-management opportunities, given the models, to improve infrastructure recovery time. Graduate students will also be mentored and trained in these approaches to facilitate a multidisciplinary understanding of linked physical and decision structures to improve infrastructure recovery after a failure.This project will produce insights into how operators use information to make decisions in the context of interdependent infrastructure. Technically, the research employs novel tools by integrating regulatory analysis, semi-structured interviews, fault tree analysis, agent-based modeling, and serious gaming, to determine how information, and other nudges and regulatory interventions, alter decisions, and ultimately infrastructure recovery processes. The modeling and serious gaming approaches are strongly grounded in an understanding of the physical behavior, observed operator behavior, and governing decision rules and heuristics of operators. Unique to this study is the intersection of interdependent infrastructure modeling and decision science. This interdisciplinary research seeks to develop a new theoretical understanding of interdependent infrastructure informed by operator behavior and to identify practical interventions that improve the co-management of these interdependent systems. Further value is added by comparing computer simulated infrastructure recovery models that produce a "theoretical" optimum to an operator-revealed "practical" optimum via serious gaming. This presents a significant advance to the interdependent infrastructure field by evaluating the divide between current academic optimization recovery models and actual operator recovery behavior given inducements for better decision-making.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

灾后迅速恢复基础设施服务是社区恢复的基础。当基础设施部门相互依赖，并且其运营商可能缺乏对其他系统的条件和恢复计划的了解，相互等待其他系统采取行动时，可能会造成恢复延迟。对于相互依赖的基础设施恢复，运营商做出的决定在研究中被忽视了，但这是加快恢复速度的一个重要因素。为了改善相互依赖的基础设施系统的恢复，有必要拓宽当前的视角，包括1)单个运营商如何为其基础设施系统作出恢复决定，以及2)如何改进这些决定。这一具有重要弹性的相互依存的基础设施系统和流程(CRISP)项目比较了包括信息共享在内的各种干预措施在减少恢复时间方面的有效性。该项目使用马里兰大学相互依赖的冷冻水、信息技术和电力基础设施作为初步案例研究。为了探索案例研究以外的用处，与美国军事设施的合作将评估在给定模型的情况下共同管理的机会，以缩短基础设施恢复时间。研究生还将接受这些方法的指导和培训，以促进对相互关联的物理和决策结构的多学科理解，以改进故障后的基础设施恢复。该项目将深入了解运营商如何在相互依赖的基础设施的背景下利用信息做出决策。从技术上讲，这项研究使用了新的工具，整合了监管分析、半结构化访谈、故障树分析、基于代理的建模和严肃的博弈，以确定信息以及其他推动和监管干预如何改变决策，并最终改变基础设施恢复流程。建模和严肃的博弈方法牢固地建立在对物理行为、观察到的操作员行为以及管理操作员的决策规则和启发式规则的理解基础上。这项研究的独特之处在于相互依赖的基础设施建模和决策科学的交叉。这项跨学科的研究试图对由运营商行为提供信息的相互依赖的基础设施发展一种新的理论理解，并确定改善这些相互依赖的系统的共同管理的实际干预措施。进一步的价值是通过比较计算机模拟的基础设施恢复模型，这些模型通过严肃的博弈产生一个“理论”最优和一个操作员揭示的“实际”最优。通过评估当前学术优化恢复模型和实际操作员恢复行为之间的差距，从而更好地做出决策，这是对相互依赖的基础设施领域的重大进步。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。