Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 7Citation - Scopus: 8A Review on Adaptive and Non-Adaptive Shading Devices for Sustainable Buildings(Elsevier, 2025) Avci, Pelin; Ekici, Berk; Kazanasmaz, Zehra TugceAdaptive and non-adaptive shading devices are noteworthy fa & ccedil;ade components in designing sustainable buildings. As the comparisons of their characteristics are limited, it becomes challenging to understand their efficiency, including their impacts on occupant behavior and comfort metrics. This comprehensive review covers (a) identifying the relationship between architectural parameters and performance targets, (b) exploring model development techniques due to performance targets, and (c) declaring both energy and visual comfort metrics. The paper covers 103 papers under architectural parameters and their corresponding performance targets, namely, daylight and visual comfort metrics with lighting energy. The aim is to identify existing research trends, methodological gaps, and potential for future study by examining how performance targets affect model development approaches. The categorizations include design parameters (shading elements and fa & ccedil;ade organization), control systems (shading device control, artificial lighting control, integrated systems), performance targets (daylight metrics, visual comfort metrics, lighting energy metrics), and modeling methods (simulation, experimental, optimization). Results showed that few studies combined daylight, visual comfort, and lighting energy due to complex modeling approaches, whereas most studies dealt only with daylight. With the increase in simulation software used to conduct research results on various focuses, an increasing trend in published papers is available in this field. Studies mostly observed changes in shading device typologies, slat angles, and numbers. The most dominant climate types were humid subtropical (Cfa) and Mediterranean (Csa). Future studies can be directed to integrated performance targets and combine suitable modeling approaches with AI technologies to produce more validated and accurate results.