Show simple item record

dc.contributor.authorHeidari Matin, Negar
dc.contributor.authorEydgahi, Ali
dc.contributor.authorGharipour, Amin
dc.contributor.authorMatin, Payam
dc.date.accessioned2022-10-17T11:58:01Z
dc.date.available2022-10-17T11:58:01Z
dc.date.issued2022-06-22
dc.identifier.citationMatin, N.H.; Eydgahi, A.; Gharipour, A.; Matin, P. A Novel Framework for Optimizing Indoor Illuminance and Discovering Association of Involved Variables. Buildings 2022, 12, 878. https://doi.org/10.3390/buildings12070878en_US
dc.identifier.urihttps://hdl.handle.net/11244/336540
dc.description.abstractThe associations between various design variables affecting the visual performance of responsive facade systems are investigated in this study. First, we propose a data-driven approach to study practical aspects of illuminance optimization for responsive facades. In this approach, the hourly indoor illuminance data are combined with the location information to generate an objective function. This function is then utilized to evaluate the visual performance of responsive facade systems by matching a variety of facade angle movements to hourly sunshine patterns. Next, statistical tests were deployed to evaluate the role of design variables in different scenarios. The results provide detailed information about the design variables and their effects on visual comfort at 0.05 significant levels. On average, facade angles, facade configurations, facade orientations, and facade locations were significant in 100%, 41%, 87%, and 45% of different possible combinations of scenarios/variables, respectively.en_US
dc.description.sponsorshipThis project was funded by the Faculty Investment Program (FIP) Provided by the Vice Pres- ident for Research and Partnership at the University of Oklahoma. Financial support was provided by the University of Oklahoma Libraries’ Open Access Fund.en_US
dc.languageen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectresponsive facadesen_US
dc.subjectfacade optimizationen_US
dc.subjectvisual comforten_US
dc.subjectdata-driven designen_US
dc.subjectstatistical testsen_US
dc.titleA Novel Framework for Optimizing Indoor Illuminance and Discovering Association of Involved Variablesen_US
dc.typeArticleen_US
dc.description.peerreviewYesen_US
dc.identifier.doi10.3390/buildings12070878en_US
ou.groupChristopher C. Gibbs College of Architectureen_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record


Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International