Enhancement of R600a vapour compression refrigeration system with MWCNT/TiO2 hybrid nano lubricants for net zero emissions building

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dc.authoridGeorge, Antony Casmir Jayaseelan/0000-0003-4591-9769en_US
dc.authoridAlagarsamy, Dr.Senthilkumar/0000-0001-9662-670Xen_US
dc.authoridSathish, T/0000-0003-4912-5579en_US
dc.authoridSaboor, Shaik/0000-0002-0490-4766en_US
dc.authoridSaleel, C Ahamed/0000-0003-3705-4371en_US
dc.authoridAgbulut, Umit/0000-0002-6635-6494en_US
dc.authoridL, Prabhu/0000-0001-9019-4555en_US
dc.authorwosidGeorge, Antony Casmir Jayaseelan/ISV-6234-2023en_US
dc.authorwosidAlagarsamy, Dr.Senthilkumar/AAP-7641-2021en_US
dc.authorwosidSaboor, Shaik/M-8170-2018en_US
dc.authorwosidSathish, T/T-1968-2019en_US
dc.authorwosidSaleel, C Ahamed/E-4217-2018en_US
dc.contributor.authorSenthilkumar, A.
dc.contributor.authorPrabhu, L.
dc.contributor.authorSathish, T.
dc.contributor.authorSaravanan, R.
dc.contributor.authorJeyaseelan, G. Antony Casmir
dc.contributor.authorAgbulutc, Umit
dc.contributor.authorMahmoud, Z.
dc.date.accessioned2024-08-23T16:04:33Z
dc.date.available2024-08-23T16:04:33Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractNet zero emissions building is widely investigated with great environmental care. In the case of refrigeration selection for net zero emissions building (NZEB), the ozone depletion potential is the primary criterion to choose the refrigerant. For achieving the NZEB, the R600a was preferred as it possesses the potential for global warming lower and zero potential for ozone depletion. This paper aims to amplify the coefficient of performance by utilizing MWCNT/TiO2 hybrid Nano lubricants in the R600a vapour compression refrigeration system. As numerous factors and equations are involved in the study and prediction of the Coefficient of Performance in vapour compression refrigeration systems which is comparatively complex and takes more time for promoting the development of precise prediction and results. Artificial neural networks (ANN) and adaptive neuro-fuzzy interface systems (ANFIS) are the two techniques mainly concentrated in this study which were not properly implemented previously. By using the ANFIS technique enhanced cooling effect of 200 W with a 50 % increment was obtained with 0.4 g/L of MWCNT/TiO2 hybrid nano lubricants which is better in comparison with ANN and experimental results. The minimum energy utilization of 90 W was obtained with the ANFIS technique. This method also predicted the enhanced COP of 3.7 with a 32 % increase in comparison to the ANN prediction method. When compared to the ANN prediction model, the ANFIS model's estimated least training error value. The results indicate that when compared to ANN prediction the ANFIS predicted values produced results that were more accurate and were the proper approach for predicting COP parameters and consumed 35 % less energy.en_US
dc.description.sponsorshipResearch Centre for Advanced Materials Science, King Khalid University, Ministry of Edu-cation, Kingdom of Saudi Arabia [RCAMS/KKU/015/22]en_US
dc.description.sponsorshipAcknowledgements This research work was supported by the Research Centre for Advanced Materials Science, King Khalid University, Ministry of Edu-cation, Kingdom of Saudi Arabia through grant number: RCAMS/KKU/015/22.en_US
dc.identifier.doi10.1016/j.seta.2023.103055
dc.identifier.issn2213-1388
dc.identifier.issn2213-1396
dc.identifier.urihttps://doi.org/10.1016/j.seta.2023.103055
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14263
dc.identifier.volume56en_US
dc.identifier.wosWOS:000950635800001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofSustainable Energy Technologies And Assessmentsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMWCNTen_US
dc.subjectTiO2 hybrid Nano lubricantsen_US
dc.subjectANFIS predictionen_US
dc.subjectANN modelen_US
dc.subjectNZEBen_US
dc.subjectCOPen_US
dc.subjectR600aen_US
dc.subjectEnergy conservationen_US
dc.subjectComputational Fluid-Dynamicsen_US
dc.subjectPerformance Analysisen_US
dc.subjectEnergy Performanceen_US
dc.subjectWorkingen_US
dc.subjectR134aen_US
dc.subjectSio2en_US
dc.subjectTio2en_US
dc.subjectLpgen_US
dc.titleEnhancement of R600a vapour compression refrigeration system with MWCNT/TiO2 hybrid nano lubricants for net zero emissions buildingen_US
dc.typeArticleen_US

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