Exploring Integrating Designers with Daylight Parametric Algorithms Results to find Optimum Window-to-Wall Ratio, Shading Depth, and spacing: Establishing opportunities for future Studies

Abstract

Architectural decision-making is a complex process. It is important for architects to create a link between their knowledge and quantitative methods. In this paper, the performance-based design process is being explored by sharing the results of the parametric simulation tools with the design team through an interactive data visualization tool. The goal is to identify a more effective process for the design team to design spaces with optimum daylight. A K–12 school with parametric window and shading was modeled in Rhino. One of the classrooms was selected for this study to find the optimum window/wall and shading design. It was simulated with Honeybee and Ladybug for analyzing illuminance level on the working area (3 ft above the floor). The variables include window-to-wall ratio, shading depth, shading spacing, and month and hour of the year. The design objectives are having the high percentage area of the space with illuminance level between 300–500 lux, and low percentage area of the space with illuminance level lower than 300 lux and higher than 500 lux. Colibri plug-in in Grasshopper is used to automatically iterate the process and save the results for the data visualization step. Design Explorer was used for interactive data visualization. The conversation between analyst and designer during the meeting helped to have a better understanding about different methods to achieve the optimal design. The methods include variable, output, and timeof-year oriented methods. This is the first step in a series of studies integrating designers with parametric simulation.