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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Hui Ren,Shoulong Wang.GPPre: A Python-Based Tool in Grasshopper for Office Building Performance Optimization[J].Journal of Harbin Institute Of Technology(New Series),2021,28(5):47-60.DOI:10.11916/j.issn.1005-9113.2019069.
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GPPre: A Python-Based Tool in Grasshopper for Office Building Performance Optimization
Author NameAffiliation
Hui Ren Heilongjiang Cold Region Architectural Science Key Laboratory, School of Architecture, Harbin Institute of Technology, Harbin 150001, China 
Shoulong Wang Department of Chemical Engineering and Safety, Binzhou University, Binzhou 256600, Shandong, China 
Abstract:
With the development of the economic and low-carbon society, high-performance building (HPB) design plays an increasingly 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. Building performance simulation (BPS) and multiple objective optimizations (MOO) are becoming the main methods for obtaining a high performance building in the design process. 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 high-performance building more conveniently. This paper proposes a toolkit “GPPre” developed based on the Grasshopper platform and Python language. At the end of this paper, a case study was conducted to verify the function of GPPre, which shows that the combination of the sensitivity analysis (SA) and MOO module in the GPPre could aid architects to design the buildings with better performance.
Key words:  GPPre  building performance simulation  multiple objective optimizations  high-performance building  Python language
DOI:10.11916/j.issn.1005-9113.2019069
Clc Number:TU243
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