Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.enbuild.2012.10.056
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dc.titleAssessment of approaches for modeling louver shading devices in building energy simulation programs
dc.contributor.authorSaelens, D.
dc.contributor.authorParys, W.
dc.contributor.authorRoofthooft, J.
dc.contributor.authorDe La Torre, A.T.
dc.date.accessioned2016-06-02T09:25:10Z
dc.date.available2016-06-02T09:25:10Z
dc.date.issued2013
dc.identifier.citationSaelens, D., Parys, W., Roofthooft, J., De La Torre, A.T. (2013). Assessment of approaches for modeling louver shading devices in building energy simulation programs. Energy and Buildings 60 : 286-297. ScholarBank@NUS Repository. https://doi.org/10.1016/j.enbuild.2012.10.056
dc.identifier.issn03787788
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/124967
dc.description.abstractIn this paper a ray-tracing method is developed to describe the global solar transmittance of louver shading devices. The method is integrated in the dynamic building energy simulation program TRNSYS to assess the cooling demand and required peak cooling power in a south oriented office room. The proposed integrated approach allows calculating the solar transmittance for each time step. As the method is quite complex and requires an important computational effort, this research contrasts the results against the performance of simplified modeling and implementation approaches to assess the performance of louver shading devices. The use of view factor models not accounting for reflections in the shading device underestimates the cooling demand and the peak cooling power. It is shown that representing the shading device as a fixed reduction factor, independent of orientation and shading typology is an unacceptable simplification. However, the use of a simplified implementation of shading factors based on ray-tracing calculations is possible within acceptable margins of error. Best results are achieved by implementing solar radiation weighted monthly averages allowing to estimate the cooling demand and peak cooling power within 3%. © 2013 Elsevier B.V.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.enbuild.2012.10.056
dc.sourceScopus
dc.subjectAngular dependent properties
dc.subjectBuilding energy simulation
dc.subjectg-Value
dc.subjectLouvers
dc.subjectRay-tracing
dc.subjectShading device
dc.subjectSolar energy
dc.subjectSolar radiation
dc.typeArticle
dc.contributor.departmentARCHITECTURE
dc.description.doi10.1016/j.enbuild.2012.10.056
dc.description.sourcetitleEnergy and Buildings
dc.description.volume60
dc.description.page286-297
dc.description.codenENEBD
dc.identifier.isiut000317539800030
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