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dc.creatorKerčov, Anton
dc.creatorBajc, Tamara
dc.creatorGojak, Milan
dc.creatorTodorović, Maja
dc.creatorPivac, Nikolina
dc.creatorNižetić, Sandro
dc.date.accessioned2023-02-23T17:21:41Z
dc.date.available2023-02-23T17:21:41Z
dc.date.issued2022
dc.identifier.isbn978-1-6654-8828-0
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/4536
dc.description.abstractThe paper deals with an analysis of existing thermal comfort models based on exergy approach and the impact of models’ input parameters to the calculation results. The aim of this paper is to present the results of the application of five different thermal comfort models based on the exergy analysis, to compare them, and to determine if they coincide with the results obtained by using Fanger’s model. While models that are the most commonly used to evaluate and predict thermal comfort conditions are based on the first law of thermodynamics, a handful of authors used both the first and the second law of thermodynamics in order to develop new thermal comfort models. Even though the optimal comfort conditions according to these models may not differ by large margin from the optimal thermal comfort conditions according to Fanger’s model, it is concluded that justification of using models based on the exergy analysis to evaluate thermal comfort is very dependent on the input parameters, which should all be taken into consideration separately.sr
dc.language.isoensr
dc.publisherIEEEsr
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/33047/RS//
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/33048/RS//
dc.rightsclosedAccesssr
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceProceedings of 7th International Conference on Smart and Sustainable Technologies SpliTech2022sr
dc.subjectthermal comfort modelsr
dc.subjectexergy analysissr
dc.subjectFanger’s modelsr
dc.titleComparison between different thermal comfort models based on the exergy analysissr
dc.typeconferenceObjectsr
dc.rights.licenseBYsr
dc.rights.holderIEEEsr
dc.citation.rankM33
dc.identifier.doi10.23919/SpliTech55088.2022.9854270
dc.type.versionpublishedVersionsr


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