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Artificial Neural Networks Modeling of Heat Transfer Characteris-tics in a Parabolic Trough Solar Collector using Nano-Fluids

    T. A. Salih H. K. Dawood S. A. Mutlag

Anbar Journal of Engineering Sciences, 2021, Volume 12, Issue 2, Pages 245-255
10.37649/aengs.2021.171192

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Abstract

In the current article, an experimental investigation has been implemented of flow and heat transfer characteristics in a parabolic trough solar collector (PTSC) using both nano-fluids and artificial neural networks modeling. Water was used as a standard working fluid in order to compare with two different types of nano-fluid namely, nano-CuO /H2O and nano-TiO2/ H2O, both with a volume concentration of 0.02. The performance of the PTSC system was eval-uated using three main indicators: outlet water temperature, useful energy and thermal efficiency under the influence of mass flowrate ranging from 30 to 80 Lt/hr. In parallel, an artificial neural network (ANN) has been proposed to predict the thermal efficiency of PTSC depending on the experimental re-sults. An Artificial Neural Network (ANN) model consists of four inputs, one output parameter and two hidden layers, two neural network models (4-2-2-1) and (4-9-9-1) were built. The experimental results show that CuO/ H2O and TiO2/H2O have higher thermal performance than water. Overall, it was veri-fied that the maximum increase in thermal efficiency of TiO2/H2O and CuO/H2O compared to water was 7.12% and 19.2%, respectively. On the oth-er hand, the results of the model 4-9-9-1 of ANN provide a higher reliability and accuracy for predicting the Thermal efficiency than the model 4-2-2-1. The results revealed that the agreement in the thermal efficiency between the ANN analysis and the experimental results about of 91% and RMSE 3.951 for 4-9-9-1 and 86% and RMSE 5.278 for 4-2-21.
Keywords:
    Solar thermal perfor-mance Parabolic trough solar collector artificial neural network CuO/H2O nano fluids TiO2/ H2O nano fluids
Main Subjects:
  • Mechanical Engineering
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(2021). Artificial Neural Networks Modeling of Heat Transfer Characteris-tics in a Parabolic Trough Solar Collector using Nano-Fluids. Anbar Journal of Engineering Sciences, 12(2), 245-255. doi: 10.37649/aengs.2021.171192
T. A. Salih; H. K. Dawood; S. A. Mutlag. "Artificial Neural Networks Modeling of Heat Transfer Characteris-tics in a Parabolic Trough Solar Collector using Nano-Fluids". Anbar Journal of Engineering Sciences, 12, 2, 2021, 245-255. doi: 10.37649/aengs.2021.171192
(2021). 'Artificial Neural Networks Modeling of Heat Transfer Characteris-tics in a Parabolic Trough Solar Collector using Nano-Fluids', Anbar Journal of Engineering Sciences, 12(2), pp. 245-255. doi: 10.37649/aengs.2021.171192
Artificial Neural Networks Modeling of Heat Transfer Characteris-tics in a Parabolic Trough Solar Collector using Nano-Fluids. Anbar Journal of Engineering Sciences, 2021; 12(2): 245-255. doi: 10.37649/aengs.2021.171192
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This journal is licensed under a Creative Commons Attribution 4.0 International (CC-BY 4.0)

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