NEESR Payload: Fiber Optic Method for Buried Pipelines Health Assessment after Earthquake-Induced Ground Movement

NEESR 有效负载:地震引起的地面运动后埋地管道健康评估的光纤方法

基本信息

  • 批准号:
    0936493
  • 负责人:
  • 金额:
    $ 10万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-02-01 至 2012-01-31
  • 项目状态:
    已结题

项目摘要

This award (NEESR Payload) is an outcome of the NSF 09-524 program solicitation ''George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) Research (NEESR)'' competition and includes the Princeton University (lead institution of this NEESR Payload project) and University of Michigan at Ann Arbor (lead institution of NEESR Award CMMI-0724022 that will accommodate this NEESR Payload). This project will utilize the NEES equipment site at the Cornell University. Close collaboration will be realized with other partners of the NEESR Award CMMI-0724022, Merrimack College and Purdue University.Natural disasters, in particular earthquakes, can cause damage to pipelines which transport life- and society-sustaining supplies, such as water or hydrocarbons. Earthquake damage to pipelines can have disastrous humanitarian, social, economic, and ecologic consequences. Consequently, real-time, and automatic or on-demand assessment of damage to pipelines after the earthquake is essential for early emergency response, efficient preparation of rescue plans, and mitigation of the disastrous consequences. Assessment is particularly challenging for buried pipelines. A method for real-time, automatic or on-demand, assessment of health condition of buried pipelines after the earthquake will be developed in this Payload project. The focus will be on damage detection and localization generated by earthquake induced ground displacement. The method will be based on the use of distributed fiber-optic sensing technology and will be applicable to both concrete and steel pipelines. A distributed fiber-optic sensor can be represented by a single several-kilometer long cable that is sensitive at every point along its length. Hence, one distributed sensor can replace thousands of traditional point sensors, and is less difficult and more economical to install and operate. Both, strain (deformation) and temperature will be monitored: strain (deformation) because the earthquake induced ground displacement actually strains (deforms) the pipe, while temperature sensing is proposed since the damage of a pipeline is often correlated with leakage of transported material that can be indirectly detected as a change of thermal parameters in the surrounding soil. Besides the assessment of damage, the method can be used for long-term structural health monitoring and operational monitoring, which will serve as an important input for lifetime maintenance activities.The proposed method will help mitigate disastrous consequences of the earthquake-induced damage to pipelines, but it will also help lifetime maintenance activities of pipelines through structural health monitoring and operational monitoring. This will have a direct broad impact on society through an increase in safety for the human population and goods, the containment of economical losses for industry and users, and the preservation of the environment. Broadened participation will be achieved through teamwork with other NEESR award partners, and in particular with Merrimack College, MA, which is a non-PhD-granting institution. The outcomes of the project will be included in Princeton University courses at both the undergraduate level (structural analysis course) and graduate level (structural health monitoring course). Results of the project will be disseminated by the Principal Investigator at Princeton University and jointly with partners of NEESR Award CMMI-0724022 to relevant industries, practitioners, and the broader public in the form of newsletters, website pages, papers published in scientific journals and professional magazines, documents, posters, and presentations via web-seminars (webinars). The project necessitates research in several disciplines and consequently, a multi-disciplinary collaboration will be established and the project will be presented in multi-disciplinary workshops and conferences at the national and international level. Data from this project will be archived and made available to the public through the NEES data repository.
该奖项(NEESR有效载荷)是NSF 09-524计划征集“乔治E.小布朗地震工程模拟(NEES)研究网络(NEESR)竞赛,包括普林斯顿大学(该NEESR有效载荷项目的牵头机构)和密歇根大学安阿伯分校(将容纳该NEESR有效载荷的NEESR奖CMMI-0724022的牵头机构)。该项目将利用康奈尔大学的NEES设备场地。 将与NEESR奖CMMI-0724022的其他合作伙伴、梅里马克学院和普渡大学密切合作。自然灾害,特别是地震,可能会对输送水或碳氢化合物等维持生命和社会的供应品的管道造成破坏。地震对管道的破坏会造成灾难性的人道主义、社会、经济和生态后果。 因此,实时、自动或按需评估地震后管道的损坏情况对于早期应急响应、有效制定救援计划和减轻灾难性后果至关重要。 对埋地管道的评估尤其具有挑战性。本Payload项目将开发一种地震后埋地管道健康状况的实时、自动或按需评估方法。 重点将放在由地震引起的地面位移产生的损伤检测和定位。 该方法将基于分布式光纤传感技术的使用,并将适用于混凝土和钢管。 分布式光纤传感器可以用一根几公里长的电缆来表示,它在沿其长度的沿着每一点都是敏感的。 因此,一个分布式传感器可以取代数千个传统的点传感器,并且安装和操作起来不那么困难,也更经济。 应变(变形)和温度都将被监测:应变(变形)是因为地震引起的地面位移实际上使管道应变(变形),而温度传感是因为管道的损坏通常与运输材料的泄漏相关,可以间接检测到周围土壤中的热参数变化。 该方法不仅可用于管道的损伤评估,还可用于管道的长期结构健康监测和运行监测,为管道的终身维护提供重要的信息,不仅有助于减轻地震对管道造成的灾难性后果,而且还有助于管道的结构健康监测和运行监测,为管道的终身维护提供帮助。 这将通过提高人口和货物的安全性、遏制工业和用户的经济损失以及保护环境,对社会产生直接的广泛影响。扩大参与将通过与其他NEESR奖合作伙伴,特别是与梅里马克学院,马,这是一个非博士授予机构的团队合作。 该项目的成果将被纳入普林斯顿大学的本科课程(结构分析课程)和研究生课程(结构健康监测课程)。该项目的结果将由普林斯顿大学的首席研究员与NEESR奖CMMI-0724022的合作伙伴共同传播给相关行业,从业者和更广泛的公众,形式包括通讯,网站页面,在科学期刊和专业杂志上发表的论文,文件,海报和通过网络研讨会(网络研讨会)进行的演示。 该项目需要在多个学科进行研究,因此,将建立多学科合作,并将在国家和国际一级的多学科讲习班和会议上介绍该项目。该项目的数据将通过NEES数据库存档并向公众提供。

项目成果

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Branko Glisic其他文献

Special issue on Distributed and quasi-distributed monitoring of civil infrastructure systems
Long-term monitoring of high-rise buildings connected by link bridges
  • DOI:
    10.1007/s13349-013-0045-4
  • 发表时间:
    2013-04-28
  • 期刊:
  • 影响因子:
    4.300
  • 作者:
    Michael Roussel;Branko Glisic;Joo Ming Lau;Chor Cheong Fong
  • 通讯作者:
    Chor Cheong Fong
Reconstruction of the appearance and structural system of Trajan's Bridge
  • DOI:
    10.1016/j.culher.2014.01.005
  • 发表时间:
    2015-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Anjali Mehrotra;Branko Glisic
  • 通讯作者:
    Branko Glisic
Minimizing the adverse effects of bias and low repeatability precision in photogrammetry software through statistical analysis
  • DOI:
    10.1016/j.culher.2017.11.005
  • 发表时间:
    2018-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Rebecca K. Napolitano;Branko Glisic
  • 通讯作者:
    Branko Glisic
Tool development for digital reconstruction: A framework for a database of historic Roman construction materials
  • DOI:
    10.1016/j.culher.2019.05.007
  • 发表时间:
    2019-11-01
  • 期刊:
  • 影响因子:
  • 作者:
    Rebecca Napolitano;Catherine Jennings;Sophia Feist;Abigail Rettew;Grace Sommers;Hannah Smagh;Benjamin Hicks;Branko Glisic
  • 通讯作者:
    Branko Glisic

Branko Glisic的其他文献

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{{ truncateString('Branko Glisic', 18)}}的其他基金

Collaborative Research: EAGER: Reliable Monitoring and Predictive Modeling for Safer Future Smart Transportation Structures
合作研究:EAGER:可靠的监控和预测建模,打造更安全的未来智能交通结构
  • 批准号:
    2329801
  • 财政年份:
    2023
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CPS: Medium: Collaborative Research: Scalable Intelligent Backscatter-Based RF Sensor Network for Self-Diagnosis of Structures
CPS:中:协作研究:用于结构自诊断的可扩展智能反向散射射频传感器网络
  • 批准号:
    2038761
  • 财政年份:
    2021
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
Collaborative Research: Structural Identification & Health Monitoring using Temperature-Driven Data
合作研究:结构识别
  • 批准号:
    1434455
  • 财政年份:
    2014
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Fiber Optic Method for Bridge Health Assessment Based on Long-Gauge Sensors
基于长规格传感器的桥梁健康评估光纤方法
  • 批准号:
    1362723
  • 财政年份:
    2014
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant

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