<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jong-Jin Kim</style></author><author><style face="normal" font="default" size="100%">Konstantinos M. Papamichael</style></author><author><style face="normal" font="default" size="100%">Stephen E. Selkowitz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of Regression Equations for a Daylighting Coefficient-of-Utilization Model</style></title><secondary-title><style face="normal" font="default" size="100%">International Daylighting Conference Proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1986</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/1986</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">http://eetd.lbl.gov/sites/all/files/publications/20539.pdf</style></url></related-urls></urls><pub-location><style face="normal" font="default" size="100%">Long Beach, CA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;When hourly energy simulation models are used to predict the performance of multi-zone buildings, theysmay be required to perform more than 2,000 daylight analyses in a single simulation. The traditionalsapproach is to use a very fast computational model, which of necessity must be a very simple model.sCoefficient of utilization models have been widely used as simple design tools but have been severely limitedsin their applicability to complex and realistic fenestration systems and building designs. This paperspresent a new coefficient of utilization (CU) model for daylighting that combines the ease of use of CUsmodels with the ability to predict illuminance under a wide range of conditions. The model consists ofsseven regression equations normalized to exterior vertical surface illuminance. These equations describesdaylight illuminance as a function of position in a room and are sensitive to all of the significant designsvariables. The equations are derived from parametric analysis using a mainframe daylighting computersmodel (SUPERLITE). We describe how these equations were developed and their physical and theoreticalsbackground. Comparisons between direct calculation and CU results for sample rooms are demonstrated.&lt;/p&gt;</style></abstract><call-num><style face="normal" font="default" size="100%">LBL-20539</style></call-num><custom1><style face="normal" font="default" size="100%">&lt;p&gt;Windows and Daylighting Group&lt;/p&gt;</style></custom1><custom2><style face="normal" font="default" size="100%">LBL-20539</style></custom2></record></records></xml>