Iranian Journal of Science and Technology, Transactions of Civil Engineering最新文献

In order to investigate the fire resisting performance of straight tenon joints with dowel, the numerical model of wood joint about the temperature field was established by adopting the finite element method to achieve the temperature distribution at each component and essential section of this joint, which was verified to have the satisfactory agreement with the experimental results. The sequential coupling method was utilized to simulate the thermal–mechanical coupling field and the residual bearing capacity of straight tenon joints with dowel under high temperature was further analyzed. The stress nephogram used for determining the failure modes of joints under different high-temperature conditions was obtained from above numerical analysis, and the corresponding mechanical performance indexes of joints including the bending moment-rotation angle curve, rotational stiffness, yield and maximum bending moments under different temperatures were perfectly achieved. The analytical results show that the mechanical performance of joints is dramatically influenced by the incurred heating temperature, and the percentage of residual bearing capacity about the rotational stiffness, yield and maximum bending moments of joints decreases gradually with the increase of the maximum temperature.

This study was aimed at assessing the utility of the subsidiary weir in the post-rehabilitation scenario of Taunsa Barrage Pakistan wherein a 7 ft. high subsidiary weir was constructed at a distance of 920 ft. downstream of the main weir. In addition to the construction of the Subsidiary weir, auxiliary devices were also provided in the stilling basin downstream of the main weir. These devices include chute blocks and dented end sill. CFD (Computation Fluid Dynamics) based software Flow-3D was employed in the current study to numerically model the Taunsa Barrage, Pakistan and simulate the flow scenario. Based on the simulations of these flow scenarios, flow parameters were recorded for each scenario and comparative analysis was carried out to assess the effectiveness of the subsidiary weir. The study concluded that the addition of a subsidiary weir affected the flow parameters (Flow depth, depth-averaged velocity, and Froude number) and the location of the hydraulic jump. Furthermore, the study concluded that the addition of a subsidiary weir resulted in lesser energy dissipation as compared to the energy dissipation observed in the absence of a subsidiary weir.

Nowadays, reinforced concrete (RC) flat slabs frequently known as a gravity-load resisting system are being used in almost every building structure due to a number of distinct advantages. On the minus side, the greatest drawback of the RC flat slabs is punching shear failure still hotly debated by researchers. Nevertheless, there is not a source of information to accurately predict the governing failure mechanism of the slabs concerning the severe shortage of a certain hypothetical method. This study was targeted at investigating the governing failure mode of the slabs monotonically subjected to vertical load by reviewing the recommendations of the current codes, i.e., ACI 318-19, EC 2, MC2010, also by using the yield line theory (YLT), as was foremost amongst the literature. For this purpose, the results numerically assessed by the punching shear equations of the codes were compared to those of experimental tests categorized in a database with 88 RC flat slabs. To predict the failure mode of the slabs, the punching shear strength obtained by the codes was compared to the flexural capacity calculated by the YLT. Finally, two case studies on RC flat slabs were proposed to elucidate the changes of shear load-carrying capacity and flexural strength while the flexural reinforcement ratio differed, as were to predict the governing failure mechanism. The slabs’ geometry was identical; one slab was served as the control specimen while the other had four openings located adjacent and parallel to the column. Shear reinforcement was, moreover, employed as a key parameter for improving the punching shear strength of the slabs at the rate of 50%. It was proved that the presented failure-mode prediction methodology is applicable to the design purposes of the slabs by comparing the predicted failure modes with the experimental counterparts. According to the case studies, the governing failure mode of 50%-shear-reinforced slab was punching shear as the flexural reinforcement ratio was more than 0.7% while the failure mode was flexural for lower flexural reinforcement ratios.

Harsh loading conditions, such as ground vibrations from earthquakes, can reduce the ductility of large structures due to their weight and cause damage and early destruction. The research explores the use of Triangular added-damping-and-stiffness (TADAS) dampers in concrete moment frame structures to assess their impact on reducing floor displacement. The study examines the impact of two different alloys, ST52 and H13, used in the TADAS damper pins. It analyzes how the TADAS structural geometry and the mechanical behavior of its ductile alloys affect the stability of concrete structures under various cyclic and monotonic loading conditions. The finite element method implemented in ABAQUS is utilized to simulate the TADAS damper under both monotonic and cyclic loading conditions. The research findings include a novel modification of alloy materials, such as H13 steel, to enhance damper flexibility, optimization of damper geometry to increase seismic energy dissipation, and improvement in structural integrity to reduce stress concentration. Comparing two ST 52 alloys to H13 steel, the maximum bearable force has increased from 300 kN to 600 kN, which is about double the resistance increase. Practical applications of integrating TADAS dampers and Chevron braces in tall and low-rise concrete buildings show significant improvements in structural stability and displacement reduction. The results indicate that the base shear, the maximum relative displacement of the floors in height, and the increase of the internal force generated in the beam and column have decreased in the structure with yielding damper compared to the structure without damper. The research results for the 15-story structure show that without using a damper, the maximum relative displacement of the floor is 150 mm. However, when a damper is used, the maximum relative displacement is reduced to about 60 mm. This study highlights the practical implications of using TADAS dampers in structural engineering and offers a promising solution to minimize the destructive effects of seismic events on large-scale concrete structures.

Bearing capacity of transversely isotropic soils have been studied by implementing the microstructure tensor in the previous works. This paper is a counterpart of the previous theoretical one which mainly focused on the verification and physical interpretation of the results. While the previous work mainly explained the theoretical framework with some numerical verifications, this paper contains a verification made by applying the results to a number of collected database of footing load tests both in the field and in the lab. The main idea is that the natural sedimentation process makes most soils some degree of anisotropy. This anisotropy is often neglected while geotechnical studies are conducted and when the bearing capacity is calculated. In this study, a comparison with theory and experimental results tries to explore the true degree of anisotropy in natural granular soil deposits, at least for practical purposes. Results indicate that if the anisotropy is ignored, the theoretical estimate of the bearing capacity is nearly 20% to 30% higher than the actual values measured in practice. Of course the nature of the test and the interpretation of the test data are influential on this general conclusion.

The present study develops a shear deformable finite element (FE) formulation for the analysis of the elastic lateral torsional buckling (LTB) of steel beams. Four governing displacement fields are proposed to describe the LTB deformation. The buckling strains/stresses and the total buckling potential energy of the system are subsequently expressed in terms of the governing displacements. The theory considers the contributions of local and global warping deformations and shear deformations. A FE formulation is then developed by using linear and cubic shape functions. Based on the validations conducted in four examples, the buckling loads/modes of single and continuous span steel beams predicted by the present solutions are observed to excellently agree with those predicted by other analytical, experimental, numerical solutions. The buckling loads evaluated by using standard moment modification factors are also discussed to clarify the restrictions of the evaluation method. The effects of shear deformations, different loading conditions, and span ratios on the buckling responses of various steel beams are also investigated in the present study.

There are two main methods for reducing the number of road accident fatalities and damages: proactive statistics and reactive statistics. The segments under consideration do not necessarily have the same level of safety risk and should be prioritized based on safety and budget expertise. Using six proactive and reactive criteria, this study presents a new index for ranking segments of a suburban road in terms of safety, namely accidents, roadside conditions, vertical signs, road markings, pavement conditions, and access density. In this study, a hierarchical analysis, a hybrid indicator of combinative distance-based assessment/evaluation based on distance from average solution, and simple weighted models were applied in addition to safety audit and accident index. The Sanandaj-Kermanshah road was selected as a case study for implementing the model. The road was chosen because of its high traffic, importance, and accident rate. In determining the safety risk of segments, accident severity index and access density were the most important factors. Due to the consideration of two steps to verify the prioritization, the CODAS model received the highest weight in the composite indicator. In suburban roads, the proposed index could be used to prioritize budget allocations for road safety. The innovation of this study is the use of a hierarchical and hybrid indicator for proactive data (obtained from safety audits) and reactive data (obtained from accidents). Also, in past studies, they have not examined the combination of proactive and reactive data.

In this paper, the mechanical properties and microstructure of hybrid basalt-brucite fibers reinforced low heat cement concrete were investigated, including compressive strength, splitting tensile strength, hydration products, microstructure, and pore. The results showed that the composite effect of hybrid fibers could effectively affect the failure mode of specimens, and improve the mechanical properties of low heat cement concrete that under optimal dosage conditions, it reached the maximum value, which were 40.2% for compressive strength and 70.6% for splitting tensile strength higher than the benchmark group. Based on microscopic techniques, hybrid fibers was found that it had a good bonding effect with the mortar. The failure modes of hybrid fibers in mortar included pull-out, tensile failure, and torsional failure. Meanwhile, mineral fibers could effectively promote hydration reaction, enhance the interface transition zone between fibers and concrete, and improve the compactness of concrete by compensating for small pores in concrete. Based on the theory of composite materials, the reinforcement mechanism of hybrid fibers on low heat cement concrete was elucidated.

One of the most significant factors affecting the durability of concrete is sulfate attack. In this paper, to predict the compressive strength (CS) of concrete under sulfate attack, three coupled machine learning methods (SSA-BP, PSO-BP and NGO-BP) were developed by coupling BP neural networks (BPNN) with three swarm intelligence algorithms, which are sparrow search algorithm (SSA), particle swarm optimization algorithm (PSO) and northern goshawk optimization algorithm (NGO), respectively. Twelve influencing factors related to material composition, erosion medium and exposure conditions are chosen as inputs, and the CS of concrete subject to sulfate attack is selected as the output. The database of 591 samples collected from published literatures is divided into three parts. Performance indexes are used to evaluate the three coupled models and BP independent model. Finally, the influence of each input on the CS of concrete under sulfate attack is examined using the Grey relational analysis approach. The following findings are reached: (1) all coupled models can predict the CS of concrete under sulfate attack with higher accuracy and achieve better performance than BP independent model, and the best one is SSA-BP model. Benefitted both from the strong nonlinear mapping ability of BPNN and from the global search and fast convergence ability of SSA, SSA-BP model has strong potential in predicting the CS of sulfate attack concrete. (2) Grey relational analysis shows that, among the twelve inputs considered, the initial compressive strength of concrete has the highest correlation (almost one) with the CS of concrete under sulfate attack. The robustness of the suggested model is confirmed by the relational analysis of all input parameters. (3) In addition, this model can provide an innovative way to assess the durability of concrete under complex or harsh environmental conditions.

Multiple treatment phases are involved in a water treatment plant (WTP), but coagulation and disinfection are the most crucial for producing safe and clear water. Determining the optimal coagulant and chlorine doses in the laboratory is time-consuming and poses a significant challenge in water treatment. To streamline this process, artificial neural network (ANN) models have been developed to predict the chlorine dose based on the coagulant dose. Studies comparing various ANN models indicate that the radial basis function neural network (RBFNN) model provides excellent predictions (R = 0.999). In modeling with radial basis function neural networks (RBFNN) and generalized regression neural networks (GRNN), the spread factor was varied from 0.1 to 15 to achieve a stable and accurate model with high predictive accuracy. Employing soft computing models to define the coagulant and chlorine doses has proven highly beneficial for the management of WTPs, significantly enhancing the efficiency and accuracy of dosing predictions.