Automatic relative humidity optimization in underground heritage sites through ventilation system based on digital twins

通风(建筑) 航程(航空) 相对湿度 工程类 建筑工程 土木工程 采矿工程 海洋工程 气象学 机械工程 航空航天工程 地理
作者
Jiaying Zhang,Helen H.L. Kwok,Han Luo,Jimmy C.K. Tong,Jackie Cheng
出处
期刊:Building and Environment [Elsevier]
卷期号:216: 108999-108999 被引量:18
标识
DOI:10.1016/j.buildenv.2022.108999
摘要

Underground heritage sites generally experience significant humidity, which results in the destruction of the surfaces and structures. This study establishes an underground heritage site preservation mechanism through a dynamic ventilation system based on digital twin technology. The aim is to control the relative humidity (RH) gradually on the air region near the walls of sites within the standard range and reduce adverse physical equipment effects and energy consumption of the system. Underground heritage site projects have more complex shapes with irregular and nonlinear arcs and height difference distributions. It is challenging to regenerate them. To achieve this objective, a model simplification rule for irregular heritage building information modeling (HBIM) technology was first established via computational fluid dynamics (CFD) simulation. Second, a methodology was developed to design a reliable and effective ventilation equipment and its layout based on CFD for irregular heritage sites. Compared with the scheme based on the optimal geometric rule arrangement, the number of pipes can be reduced by up to 25%. Third, a web-based digital twin platform combined with Internet of Things (IoTs) technology was established for achieving real-time control of the overall RH level of underground heritage sites within the standard range. The results present new solutions to control the RH of underground heritage sites for preservation. The proposed methodology can be used in typical underground heritage sites and illustrated by a real case. The validation encompassed development of digital environment for the real case and development of the ventilation system for its RH optimization.
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