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

Background: Coated archwires have been introduced to improve esthetics during orthodontic treatment. Theaim of the present study was to evaluate and compare the load–deflection characteristics and force levels of six brands of coated nickel titanium orthodontic archwires using palatal and gingival deflection. Materials and methods: Ten round wires (0.016 inch) and ten rectangular wires (0.019x0.025 inch) were obtained from each of six brands (G&H, Opal, Ortho Technology, Dany, Hubit and Astar Companies). The load-deflection properties of these archwires were evaluated by the modified bending test usinga readymade dental arch model in both palatal and gingival directions at 37°C temperature using a universal material testing machi

Coated sand (CS) filter media was investigated to remove phenol and 4-nitrophenol from aqueous solutions in batch experiments. Local sand was subjected to surface modification as impregnated with iron. The influence of process variables represented by solution pH value, contact time, initial concentration and adsorbent dosage on removal efficiency of phenol and 4-nitrophenol onto CS was studied. Batch studies were performed to evaluate the adsorption process, and it was found that the Langmuir isotherm effectively fits the experimental data for the adsorbates better than the Freundlich model with the CS highest adsorption capacity of 0.45 mg/g for 4-nitrophenol and 0.25 mg/g for phenol. The CS was found to adsorb 85% of 4-nitrophenol and

Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

Abstract

This paper concerned with study the effect of a graphite micro powder mixed in the kerosene dielectric fluid during powder mixing electric discharge machining (PMEDM) of high carbon high chromium AISI D2 steel. The type of electrode (copper and graphite), the pulse current and the pulse-on time and mixing powder in kerosene dielectric fluid are taken as the process main input parameters. The material removal rate MRR, the tool wear ratio TWR and the work piece surface roughness (SR) are taken as output parameters to measure the process performance. The experiments are planned using response surface methodology (RSM) design procedure. Empirical models are developed for MRR, TWR and SR, using the analysis

   Phenol is one of the worst-damaging organic pollutants, and it produces a variety of very poisonous organic intermediates, thus it is important to find efficient ways to eliminate it. One of the promising techniques is sonoelectrochemical processing. However, the type of electrodes, removal efficiency, and process cost are the biggest challenges. The main goal of the present study is to investigate the removal of phenol by a sonoelectrochemical process with different anodes, such as graphite, stainless steel, and titanium. The best anode performance was optimized by using the Taguchi approach with an L16 orthogonal array. the degradation of phenol sonoelectrochemically was investigated with three process parameters: current de