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Architecture & Urban Research Institute

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³í¹®¸í õ°ø ¸ðµ¨¸µÁ¶°Ç º¯È­¿¡ ´ëÇÑ ¼Ò±Ô¸ð »ç¹«½ÇÀÇ ÁÖ±¤Á¶µµ ¿¹Ãø / The Prediction Indoor Daylight Illuminance in a Small Office for the Modelings of Sky Conditions
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¼ö·Ï»çÇ× Çѱ¹¹®È­°ø°£°ÇÃàÇÐȸ ³í¹®Áý, Åë±Ç Á¦67È£ (2019-08)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(277) ÃÑÆäÀÌÁö(10)
ISSN 1738-818X
ÁÖÁ¦ºÐ·ù °èȹ¹×¼³°è / µµ½Ã
ÁÖÁ¦¾î ÁÖ±¤Á¶µµ; °è»ê¾Ë°í¸®Áò; ·¹À̵ð¾ð½º; žç¸ÅĪ; ÁÖ±¤°è¼ö¹æ¹ý; ȸ±ÍºÐ¼® ; Daylight illuminance; Computation algorithm; Radiance; Sun-matching; Daylight Coefficient approach; Regression
¿ä¾à2 This study investigates the accuracy of simulation methods for the predictions of daylight illuminance in a small office space. Theoretical computation algorithms for the prediction were developed and verified against the Radiance under various daylight conditions. For the sun, the prediction results by the sun-matching method were close to those by the Radiance. The daylight coefficient approach based on 4 sky patches provided more reliable prediction results compared to those based on the method for one sky patch. For the sky, the daylight illuminance levels predicted by the daylight coefficient approach were closer to those by the Radiance compared to the sky matching-method. The illuminance levels from the various methods developed in this study strongly correlated to those from the Radiance. The linear regression models between them were acceptable under a significance level of 0.01.
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