Accurate calculation of transient overvoltages and dielectric stresses from fast-front excitations is required to obtain an optimal dielectric design of power components subjected to these conditions, which are commonly due to switching and lightning, as well as utilization of power-electronic devices. Toroidal transformers are generally used at the low voltage level. However, recent investigations and developments have explored their use at the medium voltage level. This paper analyzes the model-based improvement of the insulation design of medium voltage toroidal transformers. Lumped and distributed parameter models are used and compared to predict the transient response and dielectric stress along the transformer winding. The parameters of the toroidal transformer are computed using the finite element method considering a three-dimensional geometry. Different strategies for insulation design are proposed by means of optimal insulation thickness and electrostatic shield to reduce transient overvoltage and dielectric stress. The results show that the proposed optimal insulation design based on particle swarm optimization with electrostatic shield can substantially reduce the dielectric stress and dielectric distances. Comparison between simulations and experimental results demonstrates that the frequency domain modeling approach results in accurate calculation of transient overvoltages produced by fast front excitation and can be used effectively for insulation design.
Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
... Show MoreEnsuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages. So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capac
... Show MoreAir pollution refers to the release of pollutants into the air that are detrimental to human health and the planet as a whole.In this research, the air pollutants concentration measurements such as Total Suspended Particles(TSP), Carbon Monoxides(CO),Carbon Dioxide (CO2) and meteorological parameters including temperature (T), relative humidity (RH) and wind speed & direction were conducted in Baghdad city by several stations measuring numbered (22) stations located in different regions, and were classified into (industrial, commercial and residential) stations. Using Arc-GIS program ( spatial Analyses), different maps have been prepared for the distribution of different pollutant
The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads
... Show MoreSpecies of genus Chrotogonus (surface grasshoppers) are phytophagous and damaging to various economical important plants in their seedling stages. In order to know the biodiversity of surface grasshoppers, the detailed study has been conducted from four provinces of Pakistan. During this study, biodiversity, taxonomy, diagnosis, morphometric analysis, habitat, global distribution, and remarks of each species have been described. Total of 826 specimens were collected and sorted out into three species and three subspecies: C. (Chrotogonus) homalodemus homalodemus (Blanchard, 1836), C. (Chrotogonus) homalodemus (Blanchard, 1836), C. (Chrotogonus) trachypter
... Show More
Abstract
The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.
the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac
... Show MoreSurvival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
... Show MoreThis search includes the preparation of Schiff base ligand (SB) from condensation primary amine with vanillin. The new ligand was diagnosed by spectroscopic methods as Mass, NMR, CHN and FTIR. Ligand complexes were mixed from new (SB) and Anthranillic acid (A) with five metal (II) chlorides. The preparation and diagnosis were conducted by FTIR, CHN, UV-visible, molar conductivity, atomic absorption and magnetic moment. The octahedral geometrical shape of the complexes was proposed. The ligands and their new complexes were screened with two different types of bacteria.