Performance Prediction of Concrete Elements in Bridge Substructures using Integrated Deterioration Method
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Author(s)
Bu, Guoping
Lee, Jaeho
Guan, Hong
Blumenstein, Michael
Loo, Yew-Chaye
Griffith University Author(s)
Year published
2012
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Show full item recordAbstract
The typical probabilistic deterioration model cannot guarantee a reliable long-term prediction for various situations of available condition data. To minimise this limitation, this paper presents an advanced integrated method using state-/time-based model to build a reliable transition probability for prediction long-term performance of bridge elements. A selection process is developed in this method to automatically select a suitable prediction approach for a given situations of condition data. Furthermore, a Backward Prediction Model (BPM) is employed to effectively prediction the bridge performance when the inspection ...
View more >The typical probabilistic deterioration model cannot guarantee a reliable long-term prediction for various situations of available condition data. To minimise this limitation, this paper presents an advanced integrated method using state-/time-based model to build a reliable transition probability for prediction long-term performance of bridge elements. A selection process is developed in this method to automatically select a suitable prediction approach for a given situations of condition data. Furthermore, a Backward Prediction Model (BPM) is employed to effectively prediction the bridge performance when the inspection data are insufficient. In this study, a benchmark example-concrete element in bridge substructures is selected to demonstrate that the BPM in conjunction with time-based model can improve the reliability of long-term prediction.
View less >
View more >The typical probabilistic deterioration model cannot guarantee a reliable long-term prediction for various situations of available condition data. To minimise this limitation, this paper presents an advanced integrated method using state-/time-based model to build a reliable transition probability for prediction long-term performance of bridge elements. A selection process is developed in this method to automatically select a suitable prediction approach for a given situations of condition data. Furthermore, a Backward Prediction Model (BPM) is employed to effectively prediction the bridge performance when the inspection data are insufficient. In this study, a benchmark example-concrete element in bridge substructures is selected to demonstrate that the BPM in conjunction with time-based model can improve the reliability of long-term prediction.
View less >
Conference Title
18th IABSE Congress on Innovative Infrastructures - Toward Human Urbanism
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Copyright Statement
© 2012 IASBE. The attached file is posted here in accordance with the copyright policy of the publisher, for your personal use only. No further distribution permitted. Use hypertext link for access to conference website.
Subject
Infrastructure Engineering and Asset Management