Archive of

Advanced Engineering Science

Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-21-10-2022-364

Abstract : Iraq is one of the countries that suffer from a shortage of electricity production. One of the ways to produce electrical energy is by using photovoltaic cells. Although the cost of producing electrical energy using photovoltaic panel is low compared to using fossil fuels. However, the efficiency of photovoltaic panels is relatively low. The use of reflectors is one of the methods used to improve the efficiency of photovoltaic panels, but at the same time it causes the solar panels to heat up and over time causes damage to the photovoltaic panels. In this research, a numerical as well as experimental study was carried out to study the improvement of the performance of the photovoltaic cell. for the numerical study, it was carried out using the ANSYS 2022 program, where the analysis was done in a three-dimensional geometrical and four models were analysed which are concentration photovoltaic without adding PCM (case 1), concentration photovoltaic cell with a mixture of paraffin and petroleum jelly at 50%(case 2), concentration photoelectric cell with PCM and fins (CPV/FPCM) (case 3), concentration photoelectric cell with PCM, fins and external aluminum matrix (case 4). Experimental and numerical results showed convergence in the results and that the use of the mixture of phase-changing materials leads to a decrease in temperature (CPV/PCM2), (CPV/FPCM2) and (CPV/FPCM2P) are (7.97C°) (8.7331C°) ( 11.455 C°) respectively, and also leads to an increase in efficiency by rate (5.561%) (6.68%) in cases (CPV/FPCM2) and (CPV/FPCM2P) respectively..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-20-10-2022-362

Abstract : Recently, graphene nanoribbon field effect transistors (GNRFETs) are considered as promising contender in nano-electronic industry because of its extraordinary properties such as large mobility, high strength, and optical properties. In this paper, Schottky barrier GNRFET (SB-GNRFET) and doped GNRFET (D-GNRFET) are proposed to investigate their performance in terms of ON and OFF state currents, voltage-current (I-V) curves and transconductance. The presented devices are designed and implemented using the Synopsis based Quantumwise ATK tool to obtain the simulation results. It is observed that the D-GNRFET show high performance over the SB-GNRFET because of the doping concentrations. The simulation results of the proposed devices are obtained by the non-equilibrium Green’s function and the Poisson’s condition solver is utilized to evaluate the electrostatic potential..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-20-10-2022-361

Abstract : Precision agriculture analysis is a development fact in big data mining for predicting weather data for future recommendation agricluture. Especially in agricultural development, the spatial data is more difficult to predict right information because of more dimension due to non-relation feature analysis leads classification prediction problems. To resolve this, we propose a Forecasting weather prediction model based On Mutual Invariance Feature Selection Model (MIFSM) with intent of Successive Weather Influence Rate (WSIR) depended feature prediction and classified with Subset Spread Spectral Deep Neural Network (S3-DNN). Further predicting right features based on relevant features estimation using successive weather influence rate (SWIF) is estimated. Initially the proposed system collects the geo spatial weather data and process into feature selection using Mutual In variance Feature selection model. The features gets estimated using Successive Weather Influence Rate (SWIF) to make mean weightage along with marginal values observed from dataset rainfall, temperature, humidity etc. the estimated weight is patterned using Spatial Harvest Successive Rate (SHSR) to make ordered ranking. Further the selected features is trained into Soft Max Logical Activation Function (SMLAF) to get tuned neural network Using Convolution Neural Network (CCN). The classifier get trained with SMLAF to process input features make categorize the data into recommend and non-recommend fields based on this weather which is for recommendation for agricultural resources. The proposed system produce best recommendation performance as well than previous system..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-18-10-2022-360

Abstract : Improving the operational performance of wastewater treatment plants can be effectively approached by means of model simulation. GPS-X model was used in this study. Calibration and validation of the model were carried out, with various sensitive parameters subject to modification, with results found within the prescribed parameters for R and RMSE. Sensitivity analysis then indicated that the most important factor for reducing nitrogen and phosphorous concentrations was the readily biodegradable fraction; thus, the IR, RAS ratio, DO, and WAS flows were reduced from 3% to 1%, from 100 to 20%, from 3.5 to 2 mg/L, and from 3,500 to 1,000 m3/d, respectively, producing an optimization that saved 688.4 Kw.h in energy and gave a sludge reduction of 32%. These results showed that an IR percentage of 3% is not appropriate. Decreased rbCOD thus necessitates a chemical upgrade, which was implemented in this case by means of adding an external carbon source, represented by acetic acid, propionic acid, methanol, and glycerol, with good results. These additions led to improvements in terms of reduced TN and TP by suitable ratios. The best external carbon source was thus determined to be methanol, while glycerol was less effective than the others. The process of pre-denitrification was compared with the post-denitrification process by means of the addition of methanol as an external carbon source, which gave good results for the reduction of TN in the post-denitrification process, by up to 80%; however, the effect on other pollutants was to increase concentrations..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-17-10-2022-359

Abstract : We introduce the new class quasi -(ζ,η)- normal operators. Composition operators, Weighted composition operators, Composite multiplication operators of Quasi –(ζ,η)- normal and their adjoints on L^2 (ℷ) are described..
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