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SCC-CIVIC-PG Track B: UNUM: Unification for Underground resilience Measures

SCC-CIVIC-PG Track B: UNUM: Unification for Underground resilience Measures
SCC-CIVIC-PG 轨道 B:UNUM:统一地下复原力措施
批准号:
2043736
负责人:
Debra Laefer
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-01-15 至 2021-06-30
关键词:

项目摘要

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中文摘要
翻译
据预测,自然灾害将对城市人口构成越来越大的威胁。鉴于社区对公用事业服务的依赖以及公用事业服务的互连和互操作性质,一个社区的基础设施问题可能会对其他社区产生直接和/或连锁影响(例如,一个地区的变压器过载可能会使远处社区的服务瘫痪)。提高自然灾害的复原力需要充分了解地下的使用情况和社区对此的兴趣,以确定威胁和脆弱性,并设计有效的缓解战略。为了直接应对这一挑战,统一地下复原力措施(Unum)项目建议以9/11纽约市(NYC)世贸中心袭击后设想的方式审查地下数据开发、集成和互操作性选项。地下数据的三维(3D)集成、查看和查询可以改进风险识别、实施具有成本效益的缓解和冗余措施,并加强与目前几乎无法获得基础设施信息的社区的沟通。此类基础设施信息通常保存在专有系统中,存储在单独的竖井中,并且可能采用不兼容的格式。克服目前的数据集成障碍需要设计无缝、可互操作的3D数据存储和可视化系统,并愿意在采取适当安全措施的情况下共享数据。UNUM将召集所有相关利益攸关方达成必要的数据共享协议、安全安排和利益攸关方关切事项,以实现纽约市两个社区的第二阶段实施。UNUM支持地下数据定义和交换模型(Muddi)[开放地理空间联盟(OGC)领导的标准化地下公用事业信息的数据建模工作]。在第一阶段,将与包括政府机构、地方公用事业公司、社区团体和政治领导人在内的31个独特的利益攸关方举行个人和小组会议和信息收集。Unum专注于纽约市的两个社区:布鲁克林的日落公园和曼哈顿的中央商业改善区,预计将生成适用于整个纽约市和其他地区的数据收集、共享和应用建议。第二阶段将通过Muddi数据模型为两个社区实施第一阶段建议。这些社区试验台将用于完善基础设施数据集成战略,该战略可应用于美国多个司法管辖区,以帮助评估关键基础设施系统的威胁和漏洞,并识别单点故障和连锁效应的触发因素。该项目将为多方利益相关者的参与提供有效的模型,并为地下数据模型的实施提供详细的路线图。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。
英文摘要
Natural disasters are predicted to pose increasing threats to urban populations. Given community reliance on utility services and the interconnected and interoperable nature of utility services, infrastructure issues in one neighborhood may have direct and/or cascading effects in others (e.g. a transformer overload in one area may cripple services in distant neighborhoods). Improving natural hazard resilience requires full knowledge of subsurface usage and community interests in them to identify threats and vulnerabilities as well to design effective mitigation strategies. To directly address this challenge the Unification for Underground Resilience Measures (UNUM) project proposes examining subsurface data development, integration and interoperability options in ways envisioned after the 9/11 New York City (NYC) World Trade Center attack. Three-dimensional (3D) integration, viewing, and querying of subsurface data can enable improved risk identification, the implementation of cost-effective mitigation and redundancy measures, and enhanced communications with communities which currently have little access to infrastructure information. Such infrastructure information is typically held in proprietary systems, stored in separate silos, and likely to be in incompatible formats. Overcoming current data integration barriers requires the design of seamless, interoperable, 3D data storage and visualization systems and a willingness to share data with appropriate security measures in place. UNUM will assemble all relevant stakeholders for the necessary data sharing agreements, security arrangements, and stakeholder concerns to enable a Stage 2 implementation for 2 NYC neighborhoods.UNUM embraces the Model for Underground Data Definition and Interchange (MUDDI) [an Open Geospatial Consortium (OGC) led data modeling effort for standardizing underground utility information]. In Stage 1, individual and group meetings and information gathering will take place with 31 unique stakeholders including government agencies, local utility companies, community groups, and political leaders. UNUM focuses on two NYC neighborhoods: Sunset Park, Brooklyn and the Grand Central Business Improvement District, Manhattan and is expected to generate data gathering, sharing, and application recommendations applicable across NYC and beyond. Stage 2 will implement Stage 1 recommendations through the MUDDI data model for the two neighborhoods. These community test beds will be used to refine an infrastructure data integration strategy that can be applied across multiple jurisdictions across the U.S. to help assess threats and vulnerabilities of vital infrastructure systems and to identify single points of failure and triggers to cascading effects. The project will provide effective models for multi-stakeholder engagement and a detailed roadmap for the implementation of a subsurface data model.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.
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