This paper numerically investigates the required superplasticizer (SP) demand for self-consolidating concrete (SCC) as a valuable information source to obtain a durable SCC. In this regard, an adaptive neuro-fuzzy inference system (ANFIS) is integrated with three metaheuristic algorithms to evaluate a dataset from non-destructive tests. Hence, five different non-destructive testing methods, including J-ring test, V-funnel test, U-box test, 3 min slump value and 50 min slump (T50) value were performed. Then, three metaheuristic algorithms, namely particle swarm optimization (PSO), ant colony optimization (ACO) and differential evolution optimization (DEO), were considered to predict the SP demand of SCC mixtures. To compare the optimization algorithms, ANFIS parameters were kept constant (clusters = 10, train samples = 70% and test samples = 30%). The metaheuristic parameters were adjusted, and each algorithm was tuned to attain the best performance. In general, it was found that the ANFIS method is a good base to be combined with other optimization algorithms. The results indicated that hybrid algorithms (ANFIS-PSO, ANFIS-DEO and ANFIS-ACO) can be used as reliable prediction methods and considered as an alternative for experimental techniques. In order to perform a reliable analogy of the developed algorithms, three evaluation criteria were employed, including root mean square error (RMSE), Pearson correlation coefficient (r) and determination regression coefficient (R²). As a result, the ANFIS-PSO algorithm represented the most accurate prediction of SP demand with RMSE = 0.0633, r = 0.9387 and R² = 0.9871 in the testing phase.

To compensate the incapability of traditional cable force adjustment methods to automatically optimize cable forces, this paper proposes Midas/Civil and MATLAB as a structure calculator and a cable force optimizer, and external memory as a data transfer. Initial solutions from conventional methods can be optimized by internalizing the influence matrix into the multiobjective particle swarm optimization algorithm with mutation operation and constructing the mathematical model of cable force optimization, and then, a series of Pareto frontier solution sets are obtained. For the first time, fuzzy set theory is introduced for selecting Pareto presolution set for the optimization of cable-stayed bridges, to solve the final reasonable dead load state of bridges. By using this method, the peak vertical displacement of a main girder of the optimized cable-stayed bridge decreased from −11 mm to −6 mm, with a reduction of 45%. Before and after optimization, the difference of peak negative bending moment at the top of the pier was 34.8%, indicating that the main beam was more evenly stressed and the alignment was more reasonable.

Purpose: As an important load-bearing component of cable-stayed bridge, the cable-stayed cable is an important load-bearing link for the bridge superstructure and the load transferred directly to the bridge tower. In order to better manage the risk of the cable system in the construction process, the purpose of this paper is to study a new method of dynamic risk analysis of the cable system of the suspended multi-tower cable-stayed bridge based on the Bayesian network.Design/methodology/approach: First of all, this paper focuses on the whole process of the construction of the cable system, analyzes the construction characteristics of each process, identifies the safety risk factors in the construction process of the cable system, and determines the causal relationship between the risk factors. Secondly, the prior probability distribution of risk factors is determined by the expert investigation method, and the risk matrix method is used to evaluate the safety risk of cable failure quantitatively. The function expression of risk matrix is established by combining the probability of risk event occurrence and loss level. After that, the topology structure of Bayesian network is established, risk factors and probability parameters are incorporated into the network and then the Bayesian principle is applied to update the posterior probability of risk events according to the new information in the construction process. Finally, the construction reliability evaluation of PAIRA bridge main bridge cable system in Bangladesh is taken as an example to verify the effectiveness and accuracy of the new method.Findings: The feasibility of using Bayesian network to dynamically assess the safety risk of PAIRA bridge in Bangladesh is verified by the construction reliability evaluation of the main bridge cable system. The research results show that the probability of the accident resulting from the insufficient safety of the cable components of the main bridge of PAIRA bridge is 0.02, which belongs to a very small range. According to the analysis of the risk grade matrix, the risk grade is Ⅱ, which belongs to the acceptable risk range. In addition, according to the reverse reasoning of the Bayesian model, when the serious failure of the cable system is certain to occur, the node with the greatest impact is B3 (cable break) and its probability of occurrence is 82%, that is, cable break is an important reason for the serious failure of the cable system. The factor that has the greatest influence on B3 node is C6 (cable quality), and its probability is 34%, that is, cable quality is not satisfied is the main reason for cable fracture. In the same way, it can be obtained that the D9 (steel wire fracture inside the cable) event of the next level is the biggest incentive of C6 event, its occurrence probability is 32% and E7 (steel strand strength is not up to standard) event is the biggest incentive of D9 event, its occurrence probability is 13%. At the same time, the sensitivity analysis also confirmed that B3, C6, D9 and E7 risk factors were the main causes of risk occurrence.Originality/value: This paper proposes a Bayesian network-based construction reliability assessment method for cable-stayed bridge cable system. The core purpose of this method is to achieve comprehensive and accurate management and control of the risks in the construction process of the cable system, so as to improve the service life of the cable while strengthening the overall reliability of the structure. Compared with the existing evaluation methods, the proposed method has higher reliability and accuracy. This method can effectively assess the risk of the cable system in the construction process, and is innovative in the field of risk assessment of the cable system of cable-stayed bridge construction, enriching the scientific research achievements in this field, and providing strong support for the construction risk control of the cable system of cable-stayed bridge.

Purpose: Reinforcement of reinforced concrete (RC) beams in-service have always been an important research field, anchoring steel plate in the bottom of the beams is a kind of common reinforcement methods. In actual engineering, the contribution of pavement layer to the bearing capacity of RC beams is often ignored, which underestimates the bearing capacity and stiffness of RC beams to a certain extent. The purpose of this paper is to study the effect of pavement layer on the RC beams before and after reinforcement. Design/methodology/approach: First, static load experiments are carried out on three in-service RC hollow slab beams, meanwhile, nonlinear finite element models are built to study the bearing capacity of them. The nonlinear material and shear slip effect of studs are considered in the models. Second, the finite element models are verified, and the numerical simulation results are in good agreement with the experimental results. Last, the finite element models are adopted to carry out the research on the influence of different steel plate thicknesses on the flexural bearing capacity and ductility. Findings: The experimental results showed that pavement layers increase the flexural capacity of hollow slab beams by 16.7%, and contribute to increasing stiffness. Ductility ratio of SPRCB3 and PRCB2 was 30% and 24% lower than that of RCB1, respectively. The results showed that when the steel plate thickness was 1 mm–6 mm, the bearing capacity of the hollow slab beam increased gradually from 2158.0 kN.m to 2656.6 kN.m. As the steel plate thickness continuously increased to 8 mm, the ultimate bearing capacity increased to 2681.0 kN.m. The increased thickness did not cause difference to the bearing capacity, because of concrete crushing at the upper edge. Originality/value: In this paper, based on the experimental study, the bearing capacity of hollow beam strengthened by steel plate with different thickness is extrapolated by finite element simulation, and its influence on ductility is discussed. This method not only guarantees the accuracy of the bearing capacity evaluation, but also does not require a large number of samples, and has certain economy. The research results provide a basis for the reinforcement design of similar bridges.

Purpose: The flexural reinforcement of bridges in-service has been an important research field for a long time. Anchoring steel plate at the bottom of beam is a simple and effective method to improve its bearing capacity. The purpose of this paper is to explore the influence of anchoring steel plates of different thicknesses on the bearing capacity of hollow slab beam and to judge its working status.Design/methodology/approach: First, static load experiments are carried out on two in-service RC hollow slab beams; meanwhile, nonlinear finite element models are built to study the bearing capacity of them. The nonlinear material and shear slip effect of studs are considered in the models. Second, the finite element models are verified, and the numerical simulation results are in good agreement with the experimental results. Finally, the finite element models are adopted to carry out the research on the influence of different steel plate thicknesses on the flexural bearing capacity and ductility.Findings: When steel plates of different thicknesses are adopted to reinforce RC hollow slab beams, the bearing capacity increases with the increase of the steel plate thickness in a certain range. But when the steel plate thickness reaches a certain level, bearing capacity is no longer influenced. The displacement ductility coefficient decreases with the increase of steel plate thickness.Originality/value: Based on experimental study, this paper makes an extrapolation analysis of the bearing capacity of hollow slab beams reinforced with steel plates of different thicknesses through finite element simulation and discusses the influence on ductility. This method not only ensures the accuracy of bearing capacity evaluation but also does not need many samples, which is economical to a certain extent. The research results provide a basis for the reinforcement design of similar bridges.