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. Temperature exerted the most significant influence at 100%, while sample dimensions had a minimal impact at 17.9%. In addition, the mathematical model closest to the proposed was the Bazli model, because the latter depends on two variables (thickness and temperature). The ANN accurately predicted the residual tensile strength of GFRP at elevated temperatures, achieving a correlation coefficient of 97.3% and a determination coefficient of 94.3%.
This study aims to investigate the effect of changing skins material on the strength of sandwich plates with circular hole when subjected to mechanical loads. Theoretical, numerical and experimental analyses are done for sandwich plates with hole and with two face sheet materials. Theoretical analysis is performed by using sandwich plate theory which depends on the first order shear deformation theory for plates subjected to tension and bending separately. Finite element method was used to analyse numerically all cases by ANSYS program.
The sandwich plates were investigated experimentally under bending and buckling load separately. The relationship between stresses and the ratio of hole diameter to plate width (d/b) are built, by
... Show MoreBackground: Reduction in bond strength when bonding was done immediately after intracoronal bleaching procedure has been recognized. The purpose of this study is to assess the effect of antioxidants (10% sodium ascorbate (SA), 0.1M thiourea and7% sodium bicarbonate (SB)) on reversing bonding strength of composite resin to bleached dentin. Materials and method: Sixty upper 1st premolar teeth, were selected, the crowns of the teeth were embedded in acrylic resin blocks exposing a flat dentin from the buccal surface, then divided into 6 groups (10 samples each). Bleaching for the experimental groups was performed using 35% hydrogen peroxide bleaching gel (pola–office).Group A (Negative
... Show Moreloaded reinforced concrete circular short columns. An experimental investigation into the behavior
of 24 short reinforced concrete columns with and without steel fibers was carried out. The columns
had a circular section (200 mm diameter and 900 mm long). Test variables include concrete
strength, spacing of spiral reinforcement, and inclusion of steel fibers. The axial stress and axial
strains were obtained and used to evaluate the effects of the presence of steel fibers. It was found
that the addition of steel fibers slightly improves the load carrying capacity of the tested columns
whereas it significantly enhances the ductility of these specimens. Test results also indicated that for
the same confinement parameter
In this work a hybrid composite materials were prepared containing matrix of polymer (polyethylene PE) reinforced by different reinforcing materials (Alumina powder + Carbon black powder CB + Silica powder). The hybrid composite materials prepared are: • H1 = PE + Al2O3 + CB • H2 = PE + CB + SiO2 • H3 = PE + Al2O3 + CB + SiO2 All samples related to electrical tests were prepared by injection molding process. Mechanical tests include compression with different temperatures and different chemical solutions at different immersion times The mechanical experimentations results were in favour of the samples (H3) with an obvious weakness of the samples (H1) and a decrease of these properties with a rise in temperature and the increasing
... Show MoreTechnological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video strea
... Show MoreArtificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex
In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
... Show MoreIn this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented
The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).