Application of fuzzy optimum system hierarchy analysis selection method to determining repair order for existing reinforced concrete bridges

Abstract

In this paper, the D. (Degree) E. (Extent) R. (Relevancy) evaluation criterion, in combination with the fuzzy optimum system hierarchy analysis selection method, is established as a newly proposed method. The evaluation factors for the entire bridge system are partitioned and combined by weighting values. Based on the proposed method, the best decision making repair order for bridge damages can be made according to the membership grade. The evaluated results using the D.E.R. evaluation criterion in combination with the multiple factors and layers fuzzy synthesis evaluation (MFLFSE) method were employed to compare the evaluation results obtained from both the proposed and D.E.R. evaluation methods. To verify the feasibility and reliability of the proposed method, ten existing RC bridges in Keelung, Taiwan were used for determining the repair order. The predicted results obtained from among the proposed and MFLFSE and the condition index (CI) of the D.E.R. evaluation methods have the same repair order and are shown as follows: Fun‐min, Guan‐in, Wuu‐der, Dong‐shyh, Jong‐jeng, Jong‐san, Guang‐hwa, Long‐men, Shang‐ren and Jong‐her bridges. However, the predicted repair order results using the priority index (PI) of the D.E.R. evaluation method were: Fun‐min, Guan‐in, Wuu‐der, Dong‐shyh, Guanghwa, Jong‐jeng, Long‐men, Jong‐her, Jong‐san, and Shang‐ren bridges. The prediction difference between the proposed method and the PI of the D.E.R. evaluation method is because the PI of the D.E.R. evaluation method considers only the detailed assessment items while the general assessment items are neglected. The MFLFSE method has the difficulty of distributed weight due to too many factors. The predicted results obtained using the proposed method clearly show the repair and reinforcement order for each bridge is better than the D.E.R. evaluation method and the MFLFSE method. The results presented in this study can be used to repair, reinforce or demolish existing RC bridges.