The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute parameters of electrical energy consumption. The method considers the timeseries homes of the information and offers parallelization of large-scale facts processing with magnificent operational efficiency, considering the timeseries aspects of the information and the problematic inherent correlations between variables. The exams have been done using the UCI public dataset, and the experimental findings validate the method's efficacy, which has clear, sensible implications for setting up intelligent strength grid dispatching.
Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi
... Show MoreIn this paper the effect of engagement length, number of teeth, amount of applied load, wave propagation time, number of cycles, and initial crack length on the principal stress distribution, velocity of crack propagation, and cyclic crack growth rate in a spline coupling subjected to cyclic torsional impact have been investigated analytically and experimentally. It was found that the stresses induced due to cyclic impact loading are higher than the stresses induced due to impact loading with high percentage depends on the number of cycles and total loading time. Also increasing the engagement length and the number of teeth reduces the principal stresses (40%) and
(25%) respectively for increasing the engagement length from (0.15 to 0
Evaluating the behavior of a ring foundation resting on multi-layered soil is one of the important issues facing civil engineers. Many researchers have studied the behavior of ring foundation rests on multi-layered soil with vertical loads acting on the foundation. In real life ring foundation can be subjected to both vertical and horizontal loads at the same time due to wind or the presence of soil. In this research, the behavior of ring footing subjected to inclined load has been studied using PLAXIS software. Furthermore, the effect of multi-layered soil has been simulated in the model. The results showed that both vertical and horizontal stresses are mainly affected when the inclination angle of the load exceeded 45 degrees with a reduc
... Show MoreThe influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa).
To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the seco
... Show MoreCarbon Fiber-Reinforced Polymer (CFRP) bars have several advantages over traditional steel reinforcement, including low density, erosion resistance, and higher tensile strength. The ACI 440.11-22 code permits CFRP as reinforcement; however, there are limited experimental studies on its application in Reinforced Concrete (RC) columns under combined loads. This study utilized theoretical analysis and Finite Element Analysis (FEA) to investigate 25 square slender concrete columns (kL/r = 17) affected by concentric and eccentric loads, examining variables, like CFRP bar contribution, eccentricity-to-depth ratio, and reinforcement arrangement. The results demonstrated CFRP's effectiveness in these columns, with failure modes varying from
... Show MoreRutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur
... Show MoreThe idea of using slender Reinforced Concrete (RC) columns with cross-shaped (+-shaped) instead of columns with square-shaped was discussed in this paper. The use of +-shaped columns provides many architectural and structural advantages, such as avoiding prominent columns edges and improved the structural response of member. Therefore, this study explores the structural response of slender +-shaped columns experimentally and numerically by nonlinear finite element analysis using Abaqus simulation tools. The results showed an excellent convergence in strength between numerical and test results with an average standard deviation of 0.05 and 0.07. Besides that, the use of +-shaped column
The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l
... Show MoreThe effect of ozone gas with temperatures 35. 40 and 45 Celsius to control on larval and adult stages of Tribolium castaneum was tested and at time of exposure 1.0, 3.0, 7.0, 9.0, 11.0, 13.0 hours and the level of relative humidity prevailing during the test 45 ± 1%. Results showed significant differences between the exposure times, when the percentage of mortality 100% between larvae (primary, intermediate and advanced) in the treatment effect at a temperature of 35 Celsius with ozone gas at exposure time to 9.0, 11.0, 11.0 hours for the three ages respectively, and adult (male and female) in the same treatment when the three heat degrees had given ratios the total mortality reached 100% of both males at exposure time to 7.0 ,3
... Show MoreIn recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication
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