The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

In order to improve the effectiveness, increase the life cycle, and avoid the blade structural failure of wind turbines, the blades need to be perfectly designed. Knowing the flow angle and the geometric characteristics of the blade is necessary to calculate the values of the induction factors (axial and tangential), which are the basis of the Blade Element Momentum theory (BEM). The aforementioned equations form an implicit and nonlinear system. Consequently, a straightforward iterative solution process can be used to solve this problem. A theoretical study of the aerodynamic performance of a horizontal-axis wind turbine blade was introduced using the BEM. The main objective of the current work is to examine the wind turbine blade’s perf

The present work aims to fabricate n-i-p forward perovskite solar cell (PSC) withئ structure (FTO/ compact TiO₂/ compact TiO₂/ MAPbI₃ Perovskite/ hole transport layer/ Au). P3HT, CuI and Spiro-OMeTAD were used as hole transport layers. A nano film of 25 nm gold layer was deposited once between the electron transport layer and the perovskite layer, then between the hole transport layer and the perovskite layer. The performance of the forward-perovskite solar cell was studied. Also, the role of each electron transport layer and the hole transport layer in the perovskite solar cell was presented. The structural, morphological and electrical properties were studied with X-ray diffractometer, field emission s

During the last two decades, nanomaterial application has gained a significant attraction into asphalt technology due to their effect in enhancing asphalt binder improving the asphaltic mixture. This study will modify the asphalt binder with two different nano types, nano SiO2 and CaCO3, at levels ranging from 1% to 7%. The resulting optimum nano-modified Asphalt will be subject to a series of rheological tests, including dynamic shear rheometer (DSR), Viscosity, and bending beam rheometer (BBR) to determine asphalt binder sensitivity towards low-medium-high temperature range. Results indicate that both nano types improved the physical characteristics of Asphalt, and 5% by weight of Asphalt was suggested as a reasonable dosage of nano-SiO2

There is an interesting potential for the use of GFRP-pultruded profiles in hybrid GFRP-concrete structural elements, either for new constructions or for the rehabilitation of existing structures. This paper provides experimental and numerical investigations on the flexural performance of reinforced concrete (RC) specimens composite with encased pultruded GFRP I-sections. Five simply supported composite beams were tested in this experimental program to investigate the static flexural behavior of encased GFRP beams with high-strength concrete. Besides, the effect of using shear studs to improve the composite interaction between the GFRP beam and concrete as well as the effect of web stiffeners of GFRP were explored. Encasing the GFRP

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

This article deals with the impact of including transverse ribs within the absorber tube of the concentrated linear Fresnel collector (CLFRC) system with a secondary compound parabolic collector (CPC) on thermal and flow performance coefficients. The enhancement rates of heat transfer due to varying governing parameters were compared and analyzed parametrically at Reynolds numbers in the range 5,000–13,000, employing water as the heat transfer fluid. Simulations were performed to solve the governing equations using the finite volume method (FVM) under various boundary conditions. For all Reynolds numbers, the average Nusselt number in the circular tube in the CLFRC system with ribs was found to be larger than that of the plain abs

Abstract:

              The hotel sector is one of the most vital sectors exposed to risks, and the authorities concerned with control must take their active and influential role in putting the hotel sector on the right track and compatible with the internationally approved approaches, and the importance of auditing the performance of the hotel sector in light of the (Covid-19) pandemic is embodied in the fact that it gives a clear and realistic picture to the management and regulatory bodies about the performance and activities of this sector and the shortcomings and deviations that must be addressed, and also helps government decision makers to ob