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BIM-based automated design for HVAC system of office buildings—An experimental study

Hongxin Wang1Peng Xu1( )Huajing Sha1Jiefan Gu1Tong Xiao1Yikun Yang1Dingyi Zhang2
School of Mechanical Engineering, Tongji University, 1239 Siping Road, Shanghai, China
College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China
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Abstract

Although computer technologies have greatly advanced in recent years and help engineers improve work efficiency, the heating, ventilation, and air conditioning (HVAC) design process is still very time-consuming. In this paper, we propose a conceptual framework for automating the entire design process to replace current human-based HVAC design procedures. This framework includes the following automated processes: building information modeling (BIM) simplification, building energy modeling (BEM) generation & load calculation, HVAC system topology generation & equipment sizing, and system diagram generation. In this study, we analyze the importance of each process and possible ways to implement them using software. Then, we use a case study to test the automated design procedure and illustrate the feasibility of the new automated design approach. The purpose of this study is to simplify the steps in the traditional rule-based HVAC system design process by introducing artificial intelligence (AI) technology based on the traditional computer-aided design (CAD) process. Experimental results show that the automatic processes are feasible, compared with the traditional design process can effectively shorten the design time from 23.37 working hours to nearly 1 hour, and improve the efficiency.

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Building Simulation
Pages 1177-1192

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Cite this article:
Wang H, Xu P, Sha H, et al. BIM-based automated design for HVAC system of office buildings—An experimental study. Building Simulation, 2022, 15(7): 1177-1192. https://doi.org/10.1007/s12273-021-0883-7

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Received: 26 June 2021
Revised: 14 December 2021
Accepted: 23 December 2021
Published: 01 February 2022
© Tsinghua University Press 2022