Investigating the thermal and electrical gains and efficiencies influence the designed photovoltaic thermal hybrid collector (PVT) under different weather conditions. The designed system was manufactured by attaching a fabricated cooling system made of serpentine tubes to a single PV panel and connecting it to an automatic controlling system for measuring, monitoring, and simultaneously collecting the required data. A removable glass cover had been used to study the effects of glazed and unglazed PVT panel situations. The research was conducted in February (winter) and July (summer), and March for daily solar radiation effects on efficiencies. The results indicated that electrical and thermal gains increased by the increase in solar radiation. The average rise in PVT water collectors' thermal energy efficiency with a glass cover for three cases was 5% compared with the unglazed PVT water collector. While the maximum total efficiencies of 79 % and 69.5 % for glazed and unglazed collectors were recorded under maximum solar radiation of 1100 W/m2 and maximum water flow rate in the tubes system for July. The recorded result seemed promising and significant, indicating that the manufactured system is useful for adjusting PVT thermal and electrical efficiencies for cold and hot weather conditions.
With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw
... Show MoreIn this paper the effect of nonthermal atmospheric argon plasma on the optical properties of the cadmium oxide CdO thin films prepared by chemical spray pyrolysis was studied. The prepared films were exposed to different time intervals (0, 5, 10, 15, 20) min. For every sample, the transmittance, Absorbance, absorption coefficient, energy gap, extinction coefficient and dielectric constant were studied. It is found that the transmittance and the energy gap increased with exposure time, and absorption. Absorption coefficient, extinction coefficient, dielectric constant decreased with time of exposure to the argon plasma
The electrical characteristics of polyvinyl alcohol PVA doped with different concentrations (0, 1, 2, 3 and 4wt%) of sodium iodide NaI powder were studied. The films are prepared using solution casting technique, in order to investigate the effect of sodium iodide NaI additions on the electrical properties of PVA host. The D.C conductivity measured by measuring the D.C electrical resistance using the Keithly Electrometer type 616C, and for different temperatures ranging from 30 – 70oC.
The dielectric properties measured by measuring the capacitor and the loss
... Show MoreFirstly, in this study, a brief updated description and applications of different solar collectors used in renewable energy systems for supplying electric and thermal energy was presented. Secondly, an attempt was made to utilize tilting orientation of solar collector for maximizing collector energy with time in respect to horizontal orientation. For energy calculation, global solar radiation was used since they are directly related. For that purpose, field measurements of half-hourly radiation on two flat panels of tilting and horizontal orientations were carried out throughout 8-month period under local climate of Baghdad. Then, energy gain and radiation level averages were calculated based on the field radiation
... Show MoreA substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co
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