This study analyzed the data on diagnosis for the last 12 years in Korea by applying the Bayesian Markov Hazard Model. The deterioration model subdivided pavement materials into asphalt, conventional concrete, and latex-modified concrete.
Thus, this study developed deterioration models for bridge pavements as the first step to secure the power of execution of the Infrastructure Management Act. However, road agencies are experiencing problems due to a lack of deterioration models which are essential to conducting a life cycle cost analysis. The study also developed cost models for each of the pavement and bridge treatments and used these results to assess the long-term cost-effectiveness of the treatments.Īs the Framework Act on Sustainable Infrastructure Management has recently been enacted in Korea, it has become mandatory to establish a medium-and long-term plan for managing social infrastructure and evaluating the feasibility of maintenance projects. The third is a set of charts that describe the sensitivity of the treatment impact to factors related to the asset or the treatment. The second is the overall statistical description of the impact, namely, the minimum and maximum impact, and range and standard deviation of impact a statistical model that predicts the impact as a function of asset and treatment attributes. The first deliverable from this project is the average (mean) impact for each treatment type under investigation. The performance jump models showed that the asset’s functional class and pre-treatment condition, and the treatment type were major significant predictors of the performance jump and post-treatment performance loss. The performance impacts are expressed in terms of the requisite performance indicators.
age relationship, and cost) of each treatment type typically applied to INDOT’s assets. The research product from this project is a set of averages or models that represent the impacts (performance jump, post-treatment performance vs. The third specific objective is to use this information to assess the cost-effectiveness of the treatments. The second is to measure the longer-term effectiveness of specific maintenance treatments in terms of the extension to asset life. Of the specific objectives, the first is to generate requisite reset values that INDOT’s asset manager can use in the agency’s PMS and BMS software packages. This study provides and demonstrates a methodology to quantify the impact of INDOT’s standard maintenance treatments on state highway pavements and bridge deck surfaces, in terms of their condition ratings.
0 kommentar(er)
