globalchange  > 气候变化事实与影响
DOI: 10.1016/j.watres.2018.11.066
Scopus记录号: 2-s2.0-85057609051
论文题名:
A two-time-scale point process model of water main breaks for infrastructure asset management
作者: Lin P.; Yuan X.-X.
刊名: Water Research
ISSN: 431354
出版年: 2019
起始页码: 296
结束页码: 309
语种: 英语
英文关键词: Bathtub curve ; Data augmentation ; Infrastructure asset management ; Markov chain Monte Carlo ; Missing event history ; Poisson processes ; Renewal processes ; Water main breaks
Scopus关键词: Asset management ; Clocks ; Deterioration ; Markov processes ; Monte Carlo methods ; Poisson distribution ; Repair ; Risk assessment ; Bathtub curve ; Data augmentation ; Event history ; Infrastructure asset management ; Markov Chain Monte-Carlo ; Poisson process ; Renewal process ; Water mains ; Water distribution systems ; water ; data assimilation ; distribution system ; estimation method ; holistic approach ; infrastructural development ; Markov chain ; Monte Carlo analysis ; numerical model ; parameter estimation ; pipe ; Poisson ratio ; prediction ; risk assessment ; two-dimensional modeling ; Article ; Markov chain ; Monte Carlo method ; Poisson distribution ; priority journal ; probability ; process model ; water supply ; Canada
英文摘要: Deterioration modelling has been a bottlenecking step towards risk-informed asset management of municipal water distribution networks. To close the gap, we proposed a two-time-scale (TTS) point process model on a pipe level for modelling and prediction of water main breaks. This paper presents the characterization, statistical parameter estimation, probabilistic features, and application of the model. Combining Poisson and renewal models into one, the proposed TTS process is characterized by a conditional intensity function of two time variables—one in a pipe clock for overall pipe aging and the other in a repair clock for local renewal. As a result, different aging patterns including the complicated bathtub-type behaviour can be modelled. A novel statistical method that combines data augmentation and Markov Chain Monte Carlo was developed for model estimation to deal with partially missing event histories. A case study using real-life data collected from a regional municipality in Canada was presented to illustrate the application of the proposed model. The modelling process ranging from model estimation, verification, validation, and updating to application in asset management was thoroughly demonstrated. This study also demonstrated that one must use the full distributions of the parameters to obtain an unbiased prediction of mean number of water main breaks. The proposed model was also compared with the Poisson process model in terms of break intensity, survival probability, mean cumulative number of breaks, and mean annual number of breaks. The implications of the different results to asset management were carefully discussed as well. Last, the ability of the proposed model to capture the maintenance effectiveness of pipe repair was proven. This work represents a solid advancement towards holistic assessment of the aging risk of a municipal water distribution network. © 2018 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/122094
Appears in Collections:气候变化事实与影响

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作者单位: Department of Civil Engineering & Ryerson Institute for Infrastructure Innovation, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada

Recommended Citation:
Lin P.,Yuan X.-X.. A two-time-scale point process model of water main breaks for infrastructure asset management[J]. Water Research,2019-01-01
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