2019
DOI: 10.1007/s12273-019-0508-6
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On the impact of local microclimate on building performance simulation. Part II: Effect of external conditions on the dynamic thermal behavior of buildings

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Cited by 9 publications
(3 citation statements)
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“…Architectural diversity comes from various spatial characteristics identified in urban space, such as geometry, orientation, urban structure, and materials [17]. Spatial diversity is also accompanied by thermal diversity, defined in terms of various microclimatic conditions related to temperature and air circulation in hot environments [18,19].…”
Section: Thermal Comfortmentioning
confidence: 99%
“…Architectural diversity comes from various spatial characteristics identified in urban space, such as geometry, orientation, urban structure, and materials [17]. Spatial diversity is also accompanied by thermal diversity, defined in terms of various microclimatic conditions related to temperature and air circulation in hot environments [18,19].…”
Section: Thermal Comfortmentioning
confidence: 99%
“…Another essential aspect responsible for increasing building energy consumption is climate change, which occurs naturally or by human interventions [6]. These changes are attributed to change in meteorological variables (such as solar radiation, longwave radiation, air temperature, air humidity, air wind speed and direction, and their interactions [7][8][9]) prevailing over a large area (spatial), usually spanning over several years (temporal). The built environment alters the local meteorological variables and creates its unique local microclimate, which is significantly different from surrounding neighbourhoods [10,11].…”
Section: Introductionmentioning
confidence: 99%
“…Urban microclimate CFD software varies substantially depending on its physical basis, spatial-temporal resolution, and output variables (Allegrini, et al, 2015). The most widely used both nationally and internationally are Envi-MET met (Crank et al, 2018;Maggiotto, 2021), Energy-Plus (Kuo-Tsang & Yi-Jhen, 2017;Yang et al, 2012), SOLENE-Microclimate (Merlier et al, 2019;Morille et al, 2015), TRNSYS (Palme & Salvati, 2018;Perini et al, 2017), and SIMEDIF (Boutet et al, 2016;Ruiz & Correa, 2015), among others.…”
Section: Introductionmentioning
confidence: 99%