Information about the factors that lead to the deterioration of bridges is essential for bridge maintenance. Pinpointing what these factors are will certainly enhance the effectiveness of bridge management. However, a review of the literature reveals that such factors are mainly determined based on experts' opinions rather than a systematic approach. In this study the factors leading to deterioration of RC bridge decks are grouped into six common types. Twenty-nine candidate factors are selected from an extensive review of past work as well as from the inventory of the Taiwan Bridge Management System. A data mining technique, the Rough Set Theory (RST), is employed to find the factors that have the most significant impact on deterioration. It is found that weather-related factors are rather significant for almost all types of deterioration. Finally, the factors mined by RST are compared to those obtained by Mann-Whitney U (MWU). The results of comparison appear fairly consistent, which validates the proposed approach.

Abstract-This study proposes a systematic approach to estimate the MR&R cost of bridges using a reliability-based model. The approach first identifies a group of similar bridge samples to describe how the target bridge deteriorates in terms of reliability indices. The cost is then accumulated while each MR&R action is assumed to be taken over its lifespan. Afterwards, Monte Carlo Simulation is applied to generate the probability distribution as a stochastic result. Bridge expansion joint is employed as an example to demonstrate and to validate the developed approach. Results show the estimation of maintenance cost for the expansion joint of the bridge example forms a lognormal distribution with a mean of 120,768 TWD.

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Bridge life cycle maintenance costs can be estimated more accurately if the deteriorating and maintaining process can be simulated objectively. This paper first proposed a reliabilitybased model for prediction of deterioration. The performance of bridge elements was quantified by the reliability index. A stochastic approach was then introduced and the probabilities for what action should be taken at any time point can be determined. Afterwards, the costs associated with different maintaining actions were summarized from historical records. Thus, the maintaining cost for a bridge element can be taken as the sum of costs for all actions incurred over its lifespan. Monte Carlo Simulation (MCS) was finally applied to generate the probability distribution of cost estimation. Expansion joint was taken as an example to demonstrate the framework of the model. Likewise, the proposed model can be applied to all bridge elements and in turn, evaluate the maintenance cost for a whole bridge.

Information about the factors that lead to the deterioration of bridges is essential for bridge maintenance. Pinpointing what these factors are will certainly enhance the effectiveness of bridge management. However, a review of the literature reveals that such deterioration factors are usually determined from expert opinion. In other words, there is no systematic way to identify the factors and the effect they have on different types of bridge members. This study identifies six common types of deterioration that affect RC bridge decks. Twenty-nine factors are extracted from a review of past related work as well as from the inventory of Taiwan Bridge Management System. After this, a data mining technique, Rough Set Theory (RST), is employed to find the factors that have the greatest impact on deterioration from thousands of visual inspection, traffic and environmental data. It is found that weather-related factors are rather significant for almost all types of deterioration. In addition to these, some functional and structural factors are major factors for cracking and traffic volume is a major factor in rebar corrosion and breakage.