Performance optimization of pulsating heat pipe integrated compound parabolic solar collector using hybrid Red Fox optimizer based DNN (DNN-Rdfx)
•Dual doping of nano particles improved thermal performance of working fluids.•Performance of PHP integrated CPSC was studied at various filling ratios.•The experiment was optimized using hybrid DNN-RdFx method successfully.•Optimum doping fraction for deionized water is obtained based on results. N...
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Veröffentlicht in: | Solar energy 2024-11, Vol.283, p.113038, Article 113038 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Dual doping of nano particles improved thermal performance of working fluids.•Performance of PHP integrated CPSC was studied at various filling ratios.•The experiment was optimized using hybrid DNN-RdFx method successfully.•Optimum doping fraction for deionized water is obtained based on results.
Non-renewable energy usage has gradually increased over the past few decades, polluting the atmosphere. In the investigation, increasing the thermal performance of pulsating heat pipe-integrated compound parabolic solar collectors using hybrid Red Fox optimizer-based DNN. The heat transfer fluid varies the filling ratio, and nanoparticles add to the concentration level. The working fluids are titanium dioxide (TiO2) and single-wall carbon nanotubes (SWCNT), and the base fluid is deionized water. The filling ratio varies between 40, 50, and 60 % in pulsating heat pipe (PHP) system validation. Thermal resistance, thermal efficiency, and temperature are the experimental validation criteria for evaluating thermal performance. The Nano fluid combination of DIW + 100 ppm SWCNT + 100 ppm TiO2 significantly outperforms other working fluid combinations. Temperature and thermal efficiency increase by adding nanoparticles to the heat transfer fluid and reducing the thermal resistance. During experimentation with a 60 % filling ratio, the maximum respective temperature, thermal efficiency, and thermal resistivity of 68.167 °C, 58.7 %, and 0.627 °C/W are observed at around 01:00p.m. The predicted and optimized filling ratio from DNN-RdFx is also nearly 60 %. For this optimum filling ratio, the algorithm predicted optimum thermal resistance, thermal efficiency, and temperature are 0.588 °C/W, 62.48 %, and 69.35 °C, respectively, which is predicted to be achieved around 01.18p.m. The confirmatory test readings around this time period got closer to the optimum results with less than 4 % error. The test result indicates the nanoparticles are increasing the thermal performance of the PHP. |
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ISSN: | 0038-092X |
DOI: | 10.1016/j.solener.2024.113038 |