Sustainable Design: Minimizing Discomfort Glare Through Data-Driven Methods for Responsive Facades

Negar Heidari Matin (), Ali Eydgahi and Amin Gharipour
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Negar Heidari Matin: Gibbs College of Architecture, University of Oklahoma, Norman, OK 73019, USA
Ali Eydgahi: School of Engineering, Eastern Michigan University, Ypsilanti, MI 48197, USA
Amin Gharipour: School of ICT, Griffith University, Brisbane, QLD 4111, Australia

Sustainability, 2025, vol. 17, issue 2, 1-34

Abstract: Ensuring visual comfort for occupants in sustainable buildings involves addressing discomfort glare and its associated risks. Responsive facades, designed based on pre-set algorithms, enhance visual performance and reduce discomfort glare by continuously adapting to changes in daylight intensity, reflection, or color. In this study, computational models were developed by incorporating hourly daylight glare probability (DGP) with occupants’ spatial data and facade active variables to minimize discomfort glare for responsive facades. To evaluate these models, a room with an office setting was parametrically simulated with a responsive facade, generating hourly DGP data for an entire year across different facade configurations, building orientations, and climate zones. The Exhaustive Search Algorithm was then used to calculate the optimal hourly angles for the facade configurations. The results indicate that the proposed models can significantly maintain DGPs within an imperceptible range (<0.35) in all scenarios compared to a no-louver scenario. These models offer valuable insights for architects, facade designers, and researchers aiming to enhance occupant visual comfort and productivity through innovative responsive facade strategies. Aligning visual comfort, well-being, and productivity with sustainability ensures that buildings operate efficiently while providing a healthy and comfortable environment for users.

Keywords: Responsive facades; facade optimization; visual comfort; glare; data-driven design (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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