Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Life-Cycle Maintenance Cost Model for Concrete Bridges Using Markovian Deterioration Curves
Long-term deterioration of concrete bridges is a natural process that requires prudent maintenance actions throughout the bridge’s life-cycle. Nowadays, there is an ongoing effort to simulate such processes into practical models. One primary element for the model’s accuracy is the datasets used for its development. The gap between underestimated or overestimated and actual values could be narrowed by utilizing real-world datasets on bridge deterioration and rehabilitation obtained from systematic inspections over time in similar environments. Therefore, the present study aims to develop an empirical probabilistic model for precisely predicting the bridge’s future performance and suitably implementing maintenance strategies that facilitate sustainable management during bridge service life based on real data. Actual records of 72 concrete bridges from motorways in Northern Greece were collected, documenting different detected defect types, condition states, and associated maintenance costs over time. Two discrete-time Markov-chain models for the bridge’s superstructure and substructure were produced, allowing for the prediction of maintenance costs that align with the given structural condition throughout its operational life. A Chi-square test demonstrated the model’s applicability to similar datasets. This enables bridge managers to obtain a comprehensive overview of the bridge’s longitudinal performance and maintenance expenditures and adopt economically sustainable solutions for the bridge’s management.
Life-Cycle Maintenance Cost Model for Concrete Bridges Using Markovian Deterioration Curves
Long-term deterioration of concrete bridges is a natural process that requires prudent maintenance actions throughout the bridge’s life-cycle. Nowadays, there is an ongoing effort to simulate such processes into practical models. One primary element for the model’s accuracy is the datasets used for its development. The gap between underestimated or overestimated and actual values could be narrowed by utilizing real-world datasets on bridge deterioration and rehabilitation obtained from systematic inspections over time in similar environments. Therefore, the present study aims to develop an empirical probabilistic model for precisely predicting the bridge’s future performance and suitably implementing maintenance strategies that facilitate sustainable management during bridge service life based on real data. Actual records of 72 concrete bridges from motorways in Northern Greece were collected, documenting different detected defect types, condition states, and associated maintenance costs over time. Two discrete-time Markov-chain models for the bridge’s superstructure and substructure were produced, allowing for the prediction of maintenance costs that align with the given structural condition throughout its operational life. A Chi-square test demonstrated the model’s applicability to similar datasets. This enables bridge managers to obtain a comprehensive overview of the bridge’s longitudinal performance and maintenance expenditures and adopt economically sustainable solutions for the bridge’s management.
Life-Cycle Maintenance Cost Model for Concrete Bridges Using Markovian Deterioration Curves
Kleopatra Petroutsatou (Autor:in) / Theodora Vagdatli (Autor:in) / Nikolaos Louloudakis (Autor:in) / Panagiotis Panetsos (Autor:in)
2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
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