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Article
Affiliation(s)

1. School of Architecture, Harbin Institute of Technology, Harbin 150001, China
2. Hei Long Jiang Cold Region Architectural Science Key Laboratory, Harbin 150001, China
3. Department of Chemical Engineering and Safety, Binzhou University, Binzhou256600, China
4. Faculty of Built Environment, University of New South Wales, 2052 Sydney, Australia

ABSTRACT

With the development of the economic and low-carbon society, high-performance building (EPB) design plays a more and more important role in the architectural area. The performance of buildings usually includes the building energy consumption, building interior natural daylighting, building surface solar radiation and so on. To obtain a high-performance building in the design process, building performance simulation (BPS) and multiple objective optimizations (MOO) are becoming the main methods. Correspondingly, the BPS and MOO are based on the parametric tools like Grasshopper and Dynamo. However, these tools are lacking the data analysis module for designers to select the EPB more conveniently. This paper proposes a toolkit “transDATA2” developed based on the Grasshopper platform and Python language. At the end of this paper, four experiments were operated to verify the function of transDATA2 which showed that it could aid architects to design the high-performance buildings more efficiently and conveniently.

KEYWORDS

TransDATA2, BPS, MOO, EPB, Python language.

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