A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis

The service performance of reinforced concrete bridges degrades overtime under environmental and vehicle loads. Accurate bridge deterioration analysis can provide a more scientific suggestion for the formulation of road bridge maintenance, strengthening, and reconstruction plans to ensure the operat...

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Main Authors: Liang Huang, Jixin Duan, Shizhan Xu, Jiapeng Zhu, Jun Liu, Danjie Niu, Li Xu, Jiangtao You, Pengtao Xue
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/2022/4667231
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author Liang Huang
Jixin Duan
Shizhan Xu
Jiapeng Zhu
Jun Liu
Danjie Niu
Li Xu
Jiangtao You
Pengtao Xue
author_facet Liang Huang
Jixin Duan
Shizhan Xu
Jiapeng Zhu
Jun Liu
Danjie Niu
Li Xu
Jiangtao You
Pengtao Xue
author_sort Liang Huang
collection DOAJ
description The service performance of reinforced concrete bridges degrades overtime under environmental and vehicle loads. Accurate bridge deterioration analysis can provide a more scientific suggestion for the formulation of road bridge maintenance, strengthening, and reconstruction plans to ensure the operational safety of road bridges. Combined with bridge inspection data from the bridge database in Henan Province, we propose a prognostic model which is based on the Cox regression model for the service performance of newly operated highway girder bridges based on survival analysis theory. The Cox regression model can not only simultaneously analyze the effects of numerous factors on bridge survival, but also handle the presence of censored data in bridge survival data, which does not require the data to meet a specific distribution type. It shows that the decay rate of the deck system, superstructure, and substructure decreases with time in service, which is consistent with the actual decay pattern of the bridge structure. To further verify the accuracy of the model, the authors built a multilayer perceptron neural network with one hidden layer and used the cross-entropy error as the loss function. It showed that the importance of the deck system, superstructure, and substructure to the decay of the bridge structure gradually decreased. The model proposed in this paper is highly applicable and reliable. Theoretically, bridge decay prediction at regional and network-wide levels can be achieved if sufficient comprehensive bridge inspection data can be collected.
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publishDate 2022-01-01
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spelling doaj-art-d0dd0d0cf3ff4cde8ca6faa1a13b786b2025-08-20T02:20:03ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/4667231A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival AnalysisLiang Huang0Jixin Duan1Shizhan Xu2Jiapeng Zhu3Jun Liu4Danjie Niu5Li Xu6Jiangtao You7Pengtao Xue8School of Civil EngineeringSchool of Civil EngineeringSchool of Civil EngineeringHenan Transport Investment Zhongyuan Expressway Zhengluo Construction Co., Ltd.Henan Transport Investment Zhongyuan Expressway Zhengluo Construction Co., Ltd.Xuchang Highway Development CenterXuchang Highway Development CenterHenan College of TransportationHenan Transportation Development CenterThe service performance of reinforced concrete bridges degrades overtime under environmental and vehicle loads. Accurate bridge deterioration analysis can provide a more scientific suggestion for the formulation of road bridge maintenance, strengthening, and reconstruction plans to ensure the operational safety of road bridges. Combined with bridge inspection data from the bridge database in Henan Province, we propose a prognostic model which is based on the Cox regression model for the service performance of newly operated highway girder bridges based on survival analysis theory. The Cox regression model can not only simultaneously analyze the effects of numerous factors on bridge survival, but also handle the presence of censored data in bridge survival data, which does not require the data to meet a specific distribution type. It shows that the decay rate of the deck system, superstructure, and substructure decreases with time in service, which is consistent with the actual decay pattern of the bridge structure. To further verify the accuracy of the model, the authors built a multilayer perceptron neural network with one hidden layer and used the cross-entropy error as the loss function. It showed that the importance of the deck system, superstructure, and substructure to the decay of the bridge structure gradually decreased. The model proposed in this paper is highly applicable and reliable. Theoretically, bridge decay prediction at regional and network-wide levels can be achieved if sufficient comprehensive bridge inspection data can be collected.http://dx.doi.org/10.1155/2022/4667231
spellingShingle Liang Huang
Jixin Duan
Shizhan Xu
Jiapeng Zhu
Jun Liu
Danjie Niu
Li Xu
Jiangtao You
Pengtao Xue
A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis
Advances in Civil Engineering
title A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis
title_full A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis
title_fullStr A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis
title_full_unstemmed A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis
title_short A Prognostic Model for Newly Operated Highway Bridges Based on Censored Data and Survival Analysis
title_sort prognostic model for newly operated highway bridges based on censored data and survival analysis
url http://dx.doi.org/10.1155/2022/4667231
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