Thermal performance analysis of a parabolic trough solar water collector using fuzzy model
The main aim of this experimental work is enhancing the thermal performance of a modified PTSC system by using a corrugated absorber tube with a Fuzzy model system to predict the thermal efficiency (ηth) and Nusselt number (Nu). The experimental work is carried out at mass flow rates (m˚) of 0.02 Kg...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | The main aim of this experimental work is enhancing the thermal performance of a modified PTSC system by using a corrugated absorber tube with a Fuzzy model system to predict the thermal efficiency (ηth) and Nusselt number (Nu). The experimental work is carried out at mass flow rates (m˚) of 0.02 Kg/s, 0.025 Kg/s, 0.03 Kg/s, 0.035 Kg/s, and 0.04 Kg/s. The Reynolds number (Re) were determined in the ranges of 2000 to 4000. According to the data are obtained in the experimental work, the fuzzy model of the PTSC system has been created considering five inputs and two outputs data. The input parameters include the inlet water temperature (Tin), the outlet water temperature (Tout), receiver temperature (Tr), mass flow rate (m˚), and solar intensity (I). While the output parameters include the thermal efficiency (ηth) and Nusselt number (Nu) of the PTSC system. The triangular MFs and the Mamdani-style of model systems are used in this modeling. The final results show that the inner geometry modified technique enhanced the heat transfer coefficient and the thermal efficiency of the PTSC system to generated vortex in the flow. More specifically, the use of a using a corrugated absorber tube enhanced the collector efficiency by 5.1% to 5.5% compared with a smooth absorber tube. Also, the predict value are founding to been in near settlement with the investigational counterparts with accuracy of ∼92 %. Therefore, the proposed Fuzzy model system has high validity and accuracy for predicting a PTSC system's performance relative to that of the conventional model. The benefits of this approach are speed, flexibility, and the using of specialist information for predict as compared to that of the conventional model. |
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ISSN: | 0094-243X 1551-7616 |
DOI: | 10.1063/5.0112884 |