Bridge Monitoring and Prognostication Workshop; Minneapolis, MN; September 2008

随着国家基础设施的老化和对基础设施的需求日益增加，越来越明显的是，迫切需要能够准确评估桥梁系统的健康和安全，以确保生命安全，并优先分配有限的资源来改造和更换系统。人们越来越关注将智能桥梁技术纳入桥梁系统，以标记需要立即关注的异常情况。目前的系统存在严重的局限性，这些局限性与从离散传感器获得的有限知识、大量信息的传输和存储、数据的解释以及根据结果做出决策的优先级有关。本次研讨会将汇集来自广泛学科的20名参与者和最多20名观察员，他们具有以下一个或多个领域的个人专业知识：传感器，网络/通信，数据解释/决策，目的是确定有关这些领域的集成问题的技术挑战和研究需求，以及单个主题领域的研究需求。研讨会将产生一份文件，该文件将提供一份明确的优先事项清单，该文件可作为一种资源，告知NSF的相关项目和更广泛的研究界，有关桥梁传感和预测的短期和长期研究需求以及需要解决的重大挑战，这可能会指导支持这项工作所需的跨学科资源。特别强调的是与跨主要主题领域的整合相关的研究需求。

ABSTRACT (250 words):NSF Long-Term Bridge Monitoring and Prognostication Workshop As the nation's infrastructure ages and as demands on the infrastructure intensify, it has become increasingly evident that there is an urgent need to be able to accurately assess the health and safety of bridge systems to ensure life safety and to prioritize the allocation of limited resources to retrofit and replace systems. There is increasing interest in incorporation of smart bridge technology within bridge systems to flag abnormalities that require immediate attention. Current systems have severe limitations associated with limited knowledge obtained from discrete sensors, transmission and storage of large amounts of information, interpretation of the data, and prioritization of decisions to be made based on the results. This workshop will bring together 20 participants and up to 20 observers from a broad range of disciplines with individual expertise in one or more of the following areas: sensors, networking/communication, data interpretation/decision making, with the purpose of identifying technical challenges and research needs regarding integration issues across these fields as well as research needs within the individual topic areas. The workshop will result in a document which will provide a clear list of priorities which can be used as a resource to inform the associated programs at NSF and broader research community of the short and long-term research needs and grand challenges to be addressed associated with bridge sensing and prognostication which might guide the cross-disciplinary resources required to support the effort. Particular emphasis will be placed on the research needs associated with the integration across the major topic areas.