This study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment t

This study offers the elastic response of the variable thickness functionally graded (FG) by single walled carbon nanotubes reinforced composite (CNTRC) moderately thick cylindrical panels under rotating and transverse mechanical loadings. It’s considered that, three kinds of distributions of carbon nanotubes which are uniaxial aligned in the longitudinal direction and two functionally graded in the transverse direction of the cylindrical panels. Depending on first order shear deformation theory (FSDT), the governing equations can be derived. The partial differential equations are solved by utilizing the technique of finite element method (FEM) with a program has been built by using FORTRAN 95. The results are calculat

In this study the effect of fiber volume fraction of the glass fiber on the thermal conductivity of the polymer composite material was studied. Different fiber volume fraction of glass fibers were used (3%, 6%, 9%, 12%, and 15%). Specimens were made from polyester which reinforced with glass fibers .The fibers had two arrangements according to the direction of the thermal flow. In the first arrangement the fibers were parallel to the direction of the thermal flow, while the second arrangement was perpendicular; Lee's disk method was used for testing the specimens. The experimental results proved that the values of the thermal conductivity of the specimens was higher when the fibers arranged in parallel direction than that when the fibers

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal

Recently, there has been an increasing advancement in the communications technology, and due to the increment in using the cellphone applications in the diverse aspects of life, it became possible to automate home appliances, which is the desired goal from residences worldwide, since that provides lots of comfort by knowing that their appliances are working in their highest effi ciency whenever it is required without their knowledge, and it also allows them to control the devices when they are away from home, including turning them on or off whenever required. The design and implementation of this system is carried out by using the Global System of Mobile communications (GSM) technique to control the home appliances – In this work, an ele

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de