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A Novel Framework for Optimizing Indoor Illuminance and Discovering Association of Involved Variables
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The associations between various design variables affecting the visual performance of responsive facade systems are investigated in this study. First, we propose a data-driven approach to study practical aspects of illuminance optimization for responsive facades. In this approach, the hourly indoor illuminance data are combined with the location information to generate an objective function. This function is then utilized to evaluate the visual performance of responsive facade systems by matching a variety of facade angle movements to hourly sunshine patterns. Next, statistical tests were deployed to evaluate the role of design variables in different scenarios. The results provide detailed information about the design variables and their effects on visual comfort at 0.05 significant levels. On average, facade angles, facade configurations, facade orientations, and facade locations were significant in 100%, 41%, 87%, and 45% of different possible combinations of scenarios/variables, respectively.
Title: A Novel Framework for Optimizing Indoor Illuminance and Discovering Association of Involved Variables
Description:
The associations between various design variables affecting the visual performance of responsive facade systems are investigated in this study.
First, we propose a data-driven approach to study practical aspects of illuminance optimization for responsive facades.
In this approach, the hourly indoor illuminance data are combined with the location information to generate an objective function.
This function is then utilized to evaluate the visual performance of responsive facade systems by matching a variety of facade angle movements to hourly sunshine patterns.
Next, statistical tests were deployed to evaluate the role of design variables in different scenarios.
The results provide detailed information about the design variables and their effects on visual comfort at 0.
05 significant levels.
On average, facade angles, facade configurations, facade orientations, and facade locations were significant in 100%, 41%, 87%, and 45% of different possible combinations of scenarios/variables, respectively.
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