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Integral analysis and optimization of monitoring and inspection in aging structures: a Bayesian network approach

Integral analysis and optimization of monitoring and inspection in aging structures: a Bayesian network approach
老化结构监测和检查的整体分析和优化:贝叶斯网络方法
批准号:
229790985
负责人:
Professor Dr. Daniel Straub
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2012
资助国家:
德国
项目状态:
已结题
起止时间:
2011-12-31 至 2017-12-31

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中文摘要
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英文摘要
Significant research resources have been invested into the development of monitoring systems for aging engineering systems. At the same time, only limited efforts have been directed towards developing models and methods to quantitatively assess the information gained with these systems and to quantify the benefit of these monitoring systems. Quantitative models for understanding and assessing the effect of monitoring systems are lacking, in particular when considering combinations of several monitoring systems and inspection techniques. To develop and investigate such models is the goal of this project. These shall enable a better understanding of the impact of monitoring systems on the reliability and shall allow to quantify the Value of Information obtained from these systems. The research will employ physically-based probabilistic models of the deteriorating engineering structures and the monitoring and inspection systems. With few exceptions, this approach to assess the effect of monitoring has not been pursued; a main reason being the difficulties in the modeling and the associated large computational efforts. The recently introduced Bayesian network approach to stochastic modeling of deterioration offers unique possibilities to address these challenges. Initial results for individual structural components are promising. Therefore, this research project aims at developing methods to assess the effect of monitoring combined with inspection on the reliability of deteriorating structures, using physically-based models implemented in a Bayesian network model framework. To ensure the feasibility of the project, it will focus on offshore steel structures subject to fatigue, for which structural and deterioration models are readily available. However, the results of the project will be transferable to other types of structures and deterioration mechanisms. In addition, a major expected outcome of the project is didactic: The models needed for quantitatively assessing the impact of monitoring and inspection in an integral way will not least facilitate a better understanding and communication of which information monitoring systems must provide to be effective. Given the economic importance of deterioration in infrastructure and engineering systems and given the significant amount of resources spent on developing and implementing monitoring systems, the potential impact of this research is considerable.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.strusafe.2019.101877
发表时间: 2020
期刊: Structural Safety
影响因子: 5.8
作者: [D. Štraub;R. Schneider;E. Bismut;Hyun-joong Kim]
通讯作者: D. Štraub;R. Schneider;E. Bismut;Hyun-joong Kim
DOI: 10.1016/j.strusafe.2018.08.002
发表时间: 2019
期刊: Structural Safety
影响因子: 5.8
作者: [J. Luque;D. Štraub]
通讯作者: J. Luque;D. Štraub
Spatial Probabilistic Modeling of Corrosion in Ship Structures
船舶结构腐蚀的空间概率建模
DOI: 10.1115/1.4035399
发表时间: 2016
期刊: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
影响因子: --
作者: [Luque J, Hamann R, Straub D.]
通讯作者: Straub D.
Probabilistic modeling of system deterioration with inspection and monitoring data using Bayesian networks
使用贝叶斯网络通过检查和监测数据对系统恶化进行概率建模
DOI: 10.14288/1.0076249
发表时间: 2015
期刊:
影响因子: --
作者: [Luque J, Straub D]
通讯作者: Straub D
6
    Integration of reliability and sensitivity assessment with data assimilation for improved decision support
    Reliability analysis and updating of complex infrastructure systems by Bayesian network
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