This research is devoted to study the strengthening technique for the existing reinforced concrete beams using external post-tensioning. An analytical methodology is proposed to predict the value of the effective prestress force for the external tendons required to close cracks in existing beams. The external prestressing force required to close cracks in existing members is only a part from the total strengthening force.
A computer program created by Oukaili (1997) and developed by Alhawwassi (2008) to evaluate curvature and deflection for reinforced concrete beams or internally prestressed concrete beams is modified to evaluate the deflection and the stress of the external tendons for the externally strengthened beams using Matlab

In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate k_p (10^-12g².cm^-4.s^-1) in Incoloy 800H at 900^oC . ANN was used for estimating the predicted values of hot corrosion rate k_p (10^-12g².cm^-4.s^-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg

This paper presents the application of nonlinear finite element models in the analysis of dappedends pre-stressed reinforced concrete girders under static loading by using ANSYS software. The girder dimensions are (4.90 m span, 0.40 m depth, 0.20 m width, 0.20 m nib depth, and 0.10 m nib length) and the parameters considered in this research are the pre-stress effect, and strand profile (straight and draped). The numerical results are compared with the experimental results of the same girders. The comparisons are carried out in terms of initial prestress effect, load- deflection curve, and failure load. Good agreement was obtained between the analytical and experimental results. Even that, the numerical model was stiffer than the experiment

This paper presents the application of nonlinear finite element models in the analysis of dapped-ends pre-stressed reinforced concrete girders under static loading by using ANSYS software. The girder dimensions are (4.90 m span, 0.40 m depth, 0.20 m width, 0.20 m nib depth, and 0.10 m nib length) and the parameters considered in this research are the pre-stress effect, and strand profile (straight and draped).

    The numerical results are compared with the experimental results of the same girders. The comparisons are carried out in terms of initial prestress effect, load- deflection curve, and failure load. Good agreement was obtained between the analytical and experimental results. Even that, the

Six proposed simply supported high strength-steel fiber reinforced concrete (HS-SFRC) beams reinforced with FRP (fiber reinforced polymer) rebars were numerically tested by finite element method using ABAQUS software to investigate their behavior under the flexural failure. The beams were divided into two groups depending on their cross sectional shape. Group A consisted of four trapezoidal beams with dimensions of (height 200 mm, top width 250 mm, and bottom width 125 mm), while group B consisted of two rectangular beams with dimensions of (125 ×200) mm. All specimens have same total length of 1500 mm, and they were also considered to be made of same high strength concrete designed material with 1% volume fraction of steel fiber.

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur