Issue |
MATEC Web Conf.
Volume 138, 2017
The 6th International Conference of Euro Asia Civil Engineering Forum (EACEF 2017)
|
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Article Number | 05001 | |
Number of page(s) | 10 | |
Section | 5-Construction and Safety Management | |
DOI | https://doi.org/10.1051/matecconf/201713805001 | |
Published online | 30 December 2017 |
Bridge Deterioration Prediction Model Based On Hybrid Markov-System Dynamic
1 Department of Civil Engineering, Institut Teknologi Sepuluh Nopember, 60111 Surabaya, Indonesia
2 Department of Civil Engineering, The University of Jember, 68111 Jember, Indonesia
* Corresponding author: jojok.teknik@unej.ac.id
Instantaneous bridge failure tends to increase in Indonesia. To mitigate this condition, Indonesia’s Bridge Management System (I-BMS) has been applied to continuously monitor the condition of bridges. However, I-BMS only implements visual inspection for maintenance priority of the bridge structure component instead of bridge structure system. This paper proposes a new bridge failure prediction model based on hybrid Markov-System Dynamic (MSD). System dynamic is used to represent the correlation among bridge structure components while Markov chain is used to calculate temporal probability of the bridge failure. Around 235 data of bridges in Indonesia were collected from Directorate of Bridge the Ministry of Public Works and Housing for calculating transition probability of the model. To validate the model, a medium span concrete bridge was used as a case study. The result shows that the proposed model can accurately predict the bridge condition. Besides predicting the probability of the bridge failure, this model can also be used as an early warning system for bridge monitoring activity.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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