Bridge Deterioration Prediction Model Based On Hybrid Markov-System Dynamic

Abstract

Abstract. 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.

OpenIPDM: A Probabilistic Framework for Estimating the Deterioration and Effect of Interventions on Bridges

“…Monitoring the deterioration state of bridges is a prerequisite for planning maintenance activities and many other decision-making processes [5,17,2]. Visual inspection is a common techniques for performing health monitoring tasks and providing data on a network-scale [12,15,13]. Nonetheless, interpreting information from visual inspection data is known to be challenging [14,4,8].…”

A literature review: model of disaster risk reduction for decision support system

“…The chain disaster scheme can be seen in Fig 2. This disaster chain modeling can use several model options, namely bayesian or dynamic bayesian [21], markov-chain [22], artificial intelligence [23], System Dynamic [24], [25] etc.…”

Dynamic bayesian updating approach for predicting bridge condition based on Indonesia-bridge management system (I-BMS)

“…The condition of each bridge component is obtained from the BMS value (0-5) which has been changed into probability rating and condition categories ("Good", "Moderate" and "Fail"). This method refers to the results of previous research (Markov-System Dynamic-MSD method) for prediction of conditions and relationships among bridge components [1].…”

“…The graphic is arranged in a DAG to connect a node (stochastic variable) with CPT others directly. To construct a DAG, please refer to the result of the MSD study [1]. To facilitate the making of a DAG structure, this study uses GeNIe 2.1 software (see Figure 2).…”

“…Research on the application of the BMS has been widely used, in which the BMS can be used as tool to predict the condition of bridges' reinforced concrete girders [1], to evaluate the performance and remaining life of bridges [2], [3], and to predict the residual life of bridges and its damages [4]. In 2016, Widodo, Adi and Anwar also proposed a bridge failure prediction model based on System Dynamic [5].…”