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Research Article

Daylighting and visual comfort of oriental sun responsive skins: A parametric analysis

Amir Tabadkani1( )Saeed Banihashemi2M. Reza Hosseini3
Department of Building and Architectural Engineering, Politecnico di Milano, Milano, Italy
School of Built Environment and Design, University of Canberra, Australia
School of Architecture and Built Environment, Deakin University, Australia
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Abstract

This study reports on developing an innovative approach for the parametric analysis of daylighting and visual comfort, through a sun responsive shading system. The objective is estimating the annual daylight metrics and indoor glare discomfort. To this end, a review of the literature was carried out on three key concepts: smart facades, visual comfort, and parametric design, in order to develop a dynamic pattern of an oriental system for enhancing the daylight and visual performance. Afterwards, two geometrical components (Rosette modules and louvers) were applied, using Grasshopper plug-in for Rhino and daylighting plug-in DIVA, to investigate the indoor daylight quality through different geometrical and physical properties. This resulted in generating 6480 design variants, when several variables (rotation, distance to facade, time hours, transmittance properties and colors) that affect incoming daylight as well as visual comfort performance in a single office space in the hot-arid climate of Tehran were taken into account. Interactive correlations between the overall performance of kinetic patterns and visual performance were investigated through an optimization process. Analyses showed that the proposed approach is capable of significantly improving the shading flexibility to control daylight metrics and glare, via a full potential adaptive pattern to achieve the maximum visual comfort level based on LEEDv4 certificate.

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Building Simulation
Pages 663-676
Cite this article:
Tabadkani A, Banihashemi S, Hosseini MR. Daylighting and visual comfort of oriental sun responsive skins: A parametric analysis. Building Simulation, 2018, 11(4): 663-676. https://doi.org/10.1007/s12273-018-0433-0

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Received: 30 August 2017
Revised: 08 January 2018
Accepted: 17 January 2018
Published: 01 February 2018
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018
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