Condition evaluations of old bridges are necessary for determining their health states and providing priority levels of maintenance. In this paper, a novel condition evaluation approach for reinforced concrete (RC) bridge superstructure is presented based on fuzzy c-mean clustering optimised by particle swarm optimisation (FCM-PSO) algorithm. It is equipped with the advantages of PSO algorithm in global optimisation and FCM algorithm in convergence acceleration, which greatly improves the effectiveness of clustering. Using this methodology, a reliable evaluation index system and a number of training samples from field-measured data of existing old bridges are prerequisites. In addition, the optimal cluster number for training samples can be determined by Xie–Beni validity evaluation index. Subsequently, condition grades and corresponding cluster centres can be determined based on the calculation of cluster centres and membership matrix for training samples. On the above basis, bridge conditions of testing samples can be evaluated based on the fuzzy membership to the cluster centres of condition grades. A case study was carried out to verify the feasibility and effectiveness of the proposed FCM-PSO method. Evaluation results reveal that the proposed method can effectively reduce the influence of subjective factors and will be favourable for condition evaluation of existing RC bridges.

Hinge joint damage is a typical form of damage occurring in simply supported slab bridges, which can present adverse effects on the overall force distribution of the structure. However, damage identification methods of hinge joint damage are still limited. In this study, a damage identification algorithm for simply supported hinged-slab bridges based on the modified hinge plate method (MHPM) and artificial bee colony (ABC) algorithms was proposed by considering the effect of hinge damage conditions on the lateral load distribution (LLD) of structures. Firstly, MHPM was proposed and demonstrated, which is based on a traditional hinge plate method by introducing relative displacement as a damage factor to simulate hinge joint damage. The effectiveness of MHPM was verified through comparison with the finite element method (FEM). Secondly, damage identification was treated as the inverse problem of calculating the LLD in damage conditions of simply supported slab bridges. Four ABC algorithms were chosen to solve the problem due to its simple structure, ease of implementation, and robustness. Comparisons of convergence speed and identification accuracy with genetic algorithm and particle swarm optimization were also conducted. Finally, hinged bridges composed of four and seven slabs were studied as numerical examples to account for the feasibility and correctness of the proposed method. The simulation results revealed that the proposed algorithm could identify the location and degree of damaged joints efficiently and precisely.

The prefabricated reinforced concrete (RC) hollow slab bridges, with the advantages of high quality, lower cost and shorter construction period, have been widely used for small-to-medium-span highway bridges in China. Because of environmental deterioration and traffic volume increases, the performance of the bridge system deteriorates gradually. Accurate bridge system evaluation can provide a reliable basis for maintenance and management. A bridge system is composed of multiple interrelated components, which makes the system reliability evaluation become a computationally intractable work. In this paper, an effective method was proposed to evaluate the system reliability of the prefabricated RC hollow slab bridge considering hinge joint damage based on the modified analytic hierarchy process (AHP). Considering the subjectivity of the traditional AHP method in constructing the judgment matrix, this paper proposed an objective construction method of the judgment matrix to modify the traditional AHP. The modified hinge plate method (MHPM) proposed by the previous research was utilized to analyze the effect of hinge joint damage on system reliability. In order to verify the applicability of the proposed system reliability evaluation method, a simply supported RC hollow slab bridge was selected as the case study and the system reliability indexes were compared with the traditional series and parallel methods. The results indicated that the traditional methods were either too conservative or too radical to objectively evaluate the actual system reliability level of the structure. In contrast, the proposed method in this paper was more suitable for evaluating the system reliability of such bridges, and more accurate in providing maintenance decision makers with a relatively reasonable bridge condition information.

The system reliability evaluation of a bridge structure is a complicated problem. Previous studies have commonly used approximate estimation methods, such as the wide bounds method and the narrow bounds method, but neither could obtain an accurate result. In recent years, the copula theory has been introduced into the system reliability evaluation, which can obtain more accurate results than the approximate methods. However, most studies simply construct binary copula functions to consider the joint failure of two failure modes. For a complex bridge structure composed of multiple components and failure modes, the joint failure of multiple failure modes needs to be considered. Before evaluating the system reliability, it is necessary to determine the failure criteria of the system. Different failure criteria for simply supported beam bridges have been proposed. However, there is no standard available to determine which failure criterion to choose, and the selection of failure criteria is ambiguous. In this paper, a novel method is proposed to evaluate the system reliability of a simply supported beam bridge by considering multiple failure criteria based on multivariate copulas and the analytic hierarchy process entropy weight (AHP–EW) method. The method first considers multiple failure criteria comprehensively and constructs multivariate copulas for the joint failure of multiple components in a bridge system reliability evaluation. The AHP–EW method is a comprehensive weighting method combining the analytic hierarchy process and entropy weight methods, which is used to establish the hierarchical analysis model between system reliability and multiple failure criteria. By considering the joint failure of multiple failure modes in the system reliability evaluation under a single failure criterion, multivariate copula functions were constructed. In order to verify the applicability of the proposed bridge system reliability method, a simply supported reinforced concrete (RC) hollow slab bridge composed of nine slab segments was selected as the numerical example. The results indicate that the method proposed in this paper could evaluate the bridge system reliability more comprehensively and reasonably.

Structural health monitoring (SHM) has been widely used in all kinds of bridges. It is significant to accurately assess the serviceability and reliability of bridge subjected to severe conditions by SHM technique. Bridge deflection as an essential evaluation index can reflect structural condition perfectly. In this study, an approach for deflection calculation and reliability assessment of simply supported bridge is presented. Firstly, a bridge deflection calculation method is proposed based on modal flexibility and Kriging method improved by artificial bee colony algorithm. Secondly, a dynamic Bayesian network is employed to evaluate the deflection reliability combined with monitoring results which include modal frequency, mode shape, environmental temperature, and humidity. A linear regression model is established to analyze the relationship between modal parameters and environmental factors. Thirdly, a simply supported bridge is constructed and monitored to verify the effectiveness of the proposed method. The results reveal that the proposed method can precisely calculate the bridge deflection. Finally, the time-dependent reliabilities of two cases are computed and the effects of monitoring factors on bridge deflection reliability are analyzed by sensitivity parameter. It indicates that the reliability is negatively correlated with temperature and more sensitive to mode shape than other three factors.