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The use of Monte Carlo method to assess the uncertainty of thermal comfort indices PMV and PPD: Benefits of using a measuring set with an operative temperature probe

2021-03Journal article Restricted access
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dc.contributor.authorBroday, Evandro Eduardo
dc.contributor.authorRuivo, Celestino
dc.contributor.authorSilva, Manuel Gameiro da
dc.date.accessioned2021-09-08T10:58:04Z
dc.date.available2021-09-08T10:58:04Z
dc.date.issued2021-03
dc.description.abstractThe Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) are the most used indices for the assessment of thermal conditions in indoor environments. However, many times, the uncertainties associated with the calculation of both indices are not reported, may be because direct methods are not easily applicable to calculate it. The present study applies Monte Carlo method to assess the uncertainties on the calculation of PMV and PPD, as a function of values and the uncertainties of four environmental (air temperature, mean radiant temperature, air velocity, and partial vapour pressure) and two individual related input parameters (metabolic rate and clothing insulation), used in Fanger's model, to calculate it. The metrological quality of the measuring probes was assumed through the scenarios established by ISO 7726 (1998) (required and desirable conditions). The use of uncertainties values for metabolic rate, clothing insulation and operative temperature were also considered. The main findings of this research are: (i) condition defined as required is not suitable for implementation of the classification scheme of thermal environments proposed by ISO 7730 (2005); (ii) in desirable condition, it is unrealistic obtaining an uncertainty of 0.2 degrees C for mean radiant temperature, if a 0.2 degrees C uncertainty temperature probe is used; (iii) the use of an operative temperature probe is a good strategy to decrease the overall level of uncertainty in the indices.
dc.description.sponsorshipCENTRO-01-0145-FEDER-032503
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1016/j.jobe.2020.101961
dc.identifier.issn2352-7102
dc.identifier.urihttp://hdl.handle.net/10400.1/17020
dc.language.isoeng
dc.peerreviewedyes
dc.publisherELSEVIER
dc.relationAssociate Laboratory of Energy, Transports and Aeronautics
dc.relationAssociate Laboratory of Energy, Transports and Aeronautics
dc.subjectThermal comfort
dc.subjectPredicted mean vote
dc.subjectUncertainty
dc.subjectMonte Carlo method
dc.subjectCombined errors
dc.subjectOperative temperature
dc.subject.otherConstruction & Building Technology; Engineering
dc.titleThe use of Monte Carlo method to assess the uncertainty of thermal comfort indices PMV and PPD: Benefits of using a measuring set with an operative temperature probe
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aeronautics
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aeronautics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50022%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50022%2F2020/PT
oaire.citation.startPage101961
oaire.citation.titleJournal of Building Engineering
oaire.citation.volume35
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameRuivo
person.givenNameCelestino
person.identifier.ciencia-id9A17-9D4B-A0A9
person.identifier.orcid0000-0002-3915-0554
person.identifier.ridI-7712-2015
person.identifier.scopus-author-id14020628300
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccess
rcaap.typearticle
relation.isAuthorOfPublicationc0c1a39a-793a-4569-a026-b08f0bc7dde4
relation.isAuthorOfPublication.latestForDiscoveryc0c1a39a-793a-4569-a026-b08f0bc7dde4
relation.isProjectOfPublication9df77b70-8231-47e7-9b34-c702e9c6021c
relation.isProjectOfPublicationc455c151-2f71-4492-b5ed-9231048a9dca
relation.isProjectOfPublication.latestForDiscovery9df77b70-8231-47e7-9b34-c702e9c6021c

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