This study investigates the impact of varying glass fiber-reinforced polymer (GFRP) stirrup spacing on the performance of doubly GFRP-reinforced concrete beams. The research focuses on assessing the behavior of GFRP-reinforced concrete beams, including load-carrying capacity, cracking, and deformability. It explores the feasibility and effectiveness of GFRP bars as an alternative to traditional steel reinforcement in concrete structures. Six concrete beams with a cross-section of 300 mm (wide) × 250 mm (deep), simply supported on a 2100 mm span, were tested. The beams underwent four-point bending with two concentrated loads applied symmetrically at one-third of the span length, resulting in a shear span (a)-to-depth (h) ratio of 2.

Concrete structures are exposed to aggressive environmental conditions that lead to corrosion of the embedded reinforcement and pre-stressing steel. Consequently, the safety of concrete structures may be compromised, and this requires a significant budgets to repair and maintain critical infrastructure. Prediction of structural safety can lead to significant reductions in maintenance costs by maximizing the impact of investments. The aim of this paper is to establish a framework to assess the reliability of existing post-tensioned concrete bridges. A time-dependent reliability analysis of an existing post-tensioned involving the assessment of Ynys-y-Gwas bridge has been presented in this study. The main cause of failure of this bridge was c

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

This project sought to fabricate a flexible gas sensor based on a short functionalized multi-walled carbon nanotubes (f-MWCNTs) network for nitrogen dioxide gas detection. The network was prepared by filtration from the suspension (FFS) method and modified by coating with a layer of polypyrrole conductive polymer (PPy) prepared by the oxidative chemical polymerization to improve the properties of the network. The structural, optical, and morphological properties of the f-MWCNTs and f-MWCNTs/PPy network were studied using X-ray diffraction (XRD), Fourie-transform infrared (FTIR), with an AFM (atomic force microscopy). XRD proved that the structure of f-MWCNTs is unaffected by the synthesis procedure. The FTIR spectra verified the existence o

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

The current research aims to reveal the level of satisfaction of the mentors with the evaluation of their performance according to gender (male - female) and to formulate the predictive equation for the level of performance (dependent variable) from knowing the level of satisfaction with the evaluation (independent variable). (16 paragraphs) contains alternatives to the answer that measures the level of satisfaction (weak, medium, and high) (1,2,3), that is, with a hypothetical average of (32). It consisted of 100 educational counselors consisting of 45 males and 55 females, the results of the research concluded that the level of satisfaction with performance is below the mean when compared with the hypothetical average of the scale of s