Abstract
The purpose of this research is to investigate general workflow of parametric architecture design basing on building physical performance. Earlier study on parametric design have shown that this method can effectively improve quality and diversity in terms of architecture appearance. In addition, design time could also be saved in this way. Nevertheless, research about parametric design on building configuration basing on building physical performance is still insufficient. Hence, this study investigates the specific workflow of parametric design in the basis of building performance. The result show that whole workflow can be divided into three steps:1) variables input 2) objective function determination 3) optimization operation. Combination of different component conducts in every step and realize final optimal scheme.
Highlights
This study focuses on two research areas: parametric design and building thermal environment performance
Caldas and Norford combined DOE2.1E with genetic algorithm (GA) to optimize the geometrical variables of the office buildings façades with the annual total energy consumption as the objective function
Parametric design workflow can be built basing on building performances
Summary
This study focuses on two research areas: parametric design and building thermal environment performance. The purpose is to construct a parametric design process based on the building thermal physical environment combining above two areas. Caldas and Norford combined DOE2.1E with GA to optimize the geometrical variables of the office buildings façades with the annual total energy consumption as the objective function. Coley and Schuka considered GA as the optimization algorithm and took the lowest building energy consumption as the objective function.[1,2,3] In addition, the parametric model was used to study the influence of thermal conductivity and heat capacity on the target function value. The architecture subjective judgment was regarded as an optimal solution and the factors of manual intervention were added on the basis of algorithm calculation simultaneously.[4,5] In this case, Trubiano et al integrated software Radiance, Energy Plus and MATLAB with GA to optimize the shape of an office building with an atrium in terms of total energy consumption and indoor illumination.[6]
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