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Go to Editorial ManagerMathematical programming techniques have been used to minimize the cost of reinforced concrete T-beam floor. The floor system consists of one way continuous slab and simply supported T-beams. The study presents a formulation based on elastic analysis followed by the ultimate strength method of design with the consideration of serviceability constraints as per ACI Code. The formulation of optimization problem has been made by utilizing the interior penalty function method as an optimization method with the purpose of minimizing the objective function representing the cost of one-meter length of the floor system. The cost includes cost of concrete, reinforcement, and formwork. The design variables considered in this study are the dimensions and the amounts of reinforcement for the slab and beams, in addition to the spacing of the beams. Many examples are solved to show the effect of these design variables on the optimum solution of the floor system. The effect on the optimum design of the compressive strength of concrete, yield strength of steel, concrete cost ratios, and formwork cost ratios has also been studied.
A computer program has been generated to calculate the optimum dimensions and the amount of reinforcements for open reinforced concrete circular cylindrical tanks rest on ground. The design is based on limit state method for both ultimate and serviceability limit states in accordance with the British Standards B.S. 8110 and B.S. 5337. The cost of concrete, steel, and formwork are considered. The procedure is based on the interior penalty method to find the optimum solution for the non-linear programming problem. The tank consists of cylindrical wall and circular base and the joint between them was considered as partially fixed. The design variables consist of tank geometric variables in addition to steel content in seven positions. The effect of the design capacity of the tank, bearing capacity of the soil, unit price of steel and concrete, and finally unit cost of formwork was studied. It is found that the reduction of the bearing capacity of the soil linearly increases the cost of the tank. The increase of concrete and steel unit costs leads to increasing the tank height while the increase of formwork unit cost enhances the tank diameter, to reach the optimal design.
This numerical study was conducted to simulate and analyze the pushout test for the new shear connector in a new steel-concrete composite system. In this system, the shear stirrups of the reinforced concrete beam are used as shear connectors when passed through holes drilled in the web of inverted steel T-section. The numerical analysis was performed by creating a three-dimensional finite element model using the finite element program ANSYS 21 student version to simulate the behavior of the new innovative shear connectors. The pushout specimens analyzed in this study have been tested experimentally by the same researchers earlier. A total of fifty-six push-out specimens were modeled and analyzed to investigate the effect of many parameters on the shear strength and slip capacity of the shear connector. The parameters studied in this investigation were the specimen dimensions (length and width), the diameter of stirrups (shear connector), the number of connectors per specimen, concrete strength, size of T-section, and shape of the specimen. The finite element analysis using ANSYS gave a good prediction of the effect of studied parameters on connector strength, the failure modes, the form and intensity of deformations in the model, and the load-slip response. The maximum difference in connector strength which was observed between the numerical and experimental results was 15 %.
Mathematical programming techniques have been used to minimize the cost of reinforced concrete counterfort retaining wall.The study presents a formulation based on elastic analysis and the ultimate strength method of design as per ACI-M318code. A computer program is generated to handle the considered problem. The formulation of optimization problem has been made by utilizing the interior penalty function method as an optimization method with the purpose of minimizing the objective function representing the cost of one-meter length of the counterfort retaining wall. This includes cost of concrete, reinforcement, and formwork. The design variables considered in this study are the dimensions and the amounts of reinforcement. It is found that the optimal spacing of counterforts equals about (0.214 to 0.366) of total height of wall. The optimum width of the base is found in the range (0.50 to 0.78) of the total height of the wall. Also the thickness of the stem is in the range(0.0284 to 0.0377) of the total height and it is less than half thickness of the base.
New composite reinforced concrete beams, in which reinforced concrete component is connected to steel T-section, are proposed. The stirrups of the beam were utilized as shear connectors by passing them through drilled holes in the web of the steel T-section. Experimental test and numerical analysis were conducted to determine the behaviour of such beams when subjected to combined shear, torsion, and bending stresses. Full scale one conventional reinforced concrete curved in plan beam C1, and four composite reinforced concrete ones, C2 to C5, were tested. The degree of shear connection between the two components of beams C2 to C5 was changed by varying the number of stirrups which are used as shear connectors. The increase in load carrying capacity of the composite reinforced concrete beams reached 55 % for beam C4 as compared to that of ordinary reinforced concrete beam. The experimental results demonstrated that the stirrups are very effective in providing the interaction between the two components of the beams. The degree of shear connection emerged not to have effect on the behaviour of tested beams. Three-dimensional finite element analysis was conducted using commercial software ABAQUS. To model the shear connection in composite reinforced concrete beam, the stirrups were connected to the web of the steel T-section by springs at the location of the stirrups. Good agreement is obtained between the results of the experimental tests and the finite element analysis.
Artificial Neural Networks (ANN) have been applied to structural engineering in recent years. Most of the researches are based on backpropagation neural networks due to its well-studied theory. A backpropagation neural network has been used to predict the ultimate torsional strength of reinforced concrete rectangular beams. The effects of the parameters, such as the number of nodes in the input, output and hidden layers and the pre-process of the training patterns, on the behaviour of the neural network have been investigated. The algorithm called 'resilient propagation algorithm' has been used to the performance of the neural network. After training, the generalization of the neural network was tested by the patterns not included in the training patterns. Once the neural network has been trained, the ultimate torsional strength of reinforced concrete is obtained very easily and efficiently. Based on the ANN results, a parametric analysis was carried out to study the influence of parameters affecting the ultimate torsional strength of reinforced concrete beams and these results are compared with the equations of ACI-code.
This research concerns with the fracture behavior of reinforced concrete beams without shear reinforcement numerically. The software ABAQUS is adapted to simulate the crack propagation using the eXtended Finite Element Method (XFEM), taking into account materials nonlinearities using concrete damage plasticity CDP criteria. XFEM is used to solve the discontinuity problems in the simulation. The maximum principal stress failure criterion is selected for damage initiation, and an energy-based damage evolution law based on a model- independent fracture criterion is selected for damage propagation. The traditional nonlinear finite element analysis is used to specify the crack initiation position, which is required to specify the crack location in the analysis of beams using XFEM. Three-dimensional reinforced concrete beam models are investigated subjected to three and four-point loading tests. Simply supported beams under the effect of applied static load are investigated. An elastic perfectly plastic model is used for modeling the longitudinal steel bars. The main variables considered in the study are beam depth and the shear span with beam length. The numerical results are compared with the available experimental results to demonstrate the applicability of the model. The XFEM provides the capability to predict the concrete member fracture behavior.
A spandrel beam is a structural member lies at the edge of a frame and is connected by a joint to the floor beam extending into the slab. The spandrel beams are primarily responsible for transferring forces from a slab to the supporting edge columns. This work investigates the possibility of using the artificial neural networks to model the complicated nonlinear relationship between the various input parameters associated with reinforced concrete spandrel beams and the actual ultimate strength of them. The descent gradient backpropagation algorithm was employed for predicting the ultimate strength of the reinforced concrete spandrel beams. The optimum topology (which gives least mean square error for both training and testing with fewer number of epochs) is presented. Effects of parameters such as, number of hidden layer(s), number of nodes in the input layer, output layer and hidden layer(s), initialization weight factors and selection of the learning rate and momentum coefficient on the behaviour of the neural network have been investigated. Because of the slow convergence of results when using descent gradient backpropagation, another algorithm which is faster called "resilient backpropagation algorithm" has been used. The neural network trained with the resilient backpropagation RPROP algorithm gives better results than that trained with the steepest descent algorithm with momentum GDM algorithm.
This paper deals with the behavior of reinforced concrete anchor blocks for underground steel pipelines.~ under the effect of loads caused by internal pressure and temperature variation due to the transportation of hydrocarbon products. The finite element method is used to carry out the analysis using the ANSYS 5.4 program. To study the effect of oil, it is represented by springs with different values for the modulus of subgrade reaction in normal and tangential reactions. It is concluded that increasing the values of the modulus of subgrade reactions, kn and ks of the soil surrounding the reinforced concrete anchor block causes an increase in the failure loads of the block. But at high values of these modules, the rate of this increase in the failure load will decrease. The area of the passive face of the concrete anchor block is found to have the main effect on the failure load as compared to the length of that block. The failure load of the concrete anchor blocks that have square cross sections is 1.33 times larger compared to that of rectangular sections. It is also concluded that locating the steel flange at the middle of the block leads to a larger resistance of anchor blocks as compared to any other position.
The effect of pore fluid chemistry on the engineering properties of soil in Garmatt-Ali zone of Basrah was investigated. The tested soil is described as silty clay of low plasticity. The pore fluid was altered to include distilled water, raw sewage, and solutions of various salts such calcium carbonate, magnesium sulphate, and calcium chloride. Also, the solutions of salts were used with different concentration (0.25, 0.5, 0.75, 1.0 normality). The prepared samples of soil were tested after different exposure periods. The test program included determination of shear strength characteristics, consolidation characteristics, and Atterberg limits. The changes in shear strength, coefficient of permeability, void ratio – effective stress relationship, and Atterberg limits were recorded with the change in exposure period or the concentration of pore fluid solution. Generally, it was found that there are reductions in the shear strength of soil when the pore fluid is changed from distilled water to solutions of salts or raw sewage. Also it was found that there is a change in the calculated values of permeability, upon changing the type of pore fluid. The coefficient of consolidation for polluted soil was found to be less than that for the reference samples with distilled water.
The present study deals with the analysis of short reinforced concrete columns subjected to axial load. One of the efficient techniques is applied, known as artificial neural networks. The descent gradient backpropagation algorithm is employed for analysis. The optimum topology (which gives the least mean square error for both training and testing with a fewer number of epochs) is presented. The effects of the number of nodes in input and hidden layer(s), and selecting of leaming rate and momentum coefficient, on the behavior of the neural network, have been investigated. Due to the slow convergence of results when using descent gradient backpropagation, the faster algorithm called "resilient backpropagation algorithm" has been used to improve the performance of the neural network and the results have been compared with those obtained using the descent gradient backpropagation algorithm.
The paper deals with neural networks identification of ultimate moment capacity of steel-concrete composite beams on base of experimental results. Basic information on artificial neural networks and its parameters suitable for analysis of experimental results are given. Two types of neural network algorithms are used. Results of identification are reported. The results show that artificial neural networks are highly suitable for assessing the ultimate moment capacity of composite section. The proposed neural network was also used to explore the effect of the various parameters on the behaviour of composite beams.