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• W4285151770 abstract "The operation of a low-temperature solar thermal system using artificial neural networks (ANNs) models of its components (flat-plate solar collector, internal heat exchanger, and stratified tank), and its working with dynamic and static modes, has been simulated. The ANNs models of these components, used as blocks, have been previously formulated using the experimental data of solar irradiance, ambient temperature, flow and temperature of the working fluid and water supplied to the tank, and stratification temperatures in eight levels of the tank, measured under the continental Mediterranean climate conditions of the center of the Iberian Peninsula. The simulation, executed in intervals of 1 min, was run for two individual days and each month of 1 year. The f-Chart method was used to validate the neural simulation under the same conditions (without stratification) for 10 years, resulting in an average deviation of the performance of 1.85%. The results for 1 day at stratification temperatures show a root-mean-square error (RMSE) value of 0.77°C in dynamic operation mode and 0.13°C in static operation mode." @default.
• W4285151770 created "2022-07-14" @default.
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• W4285151770 date "2022-01-01" @default.
• W4285151770 modified "2023-09-26" @default.
• W4285151770 title "DRAM circuit and process technology" @default.
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• W4285151770 doi "https://doi.org/10.1016/b978-0-12-820758-1.00015-7" @default.
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