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Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system
Recirculating ventilation systems may act as carriers of hazardous substances. The long-term prediction of the dynamic distribution of contaminants in this type of system is crucial for the evaluation of pollution and further design of more efficient ventilation systems. However, few convenient meth...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126526/ https://www.ncbi.nlm.nih.gov/pubmed/32287971 http://dx.doi.org/10.1016/j.buildenv.2017.05.012 |
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author | Shao, Xiaoliang Li, Xianting Ma, Xiaojun Zhu, Fenfei |
author_facet | Shao, Xiaoliang Li, Xianting Ma, Xiaojun Zhu, Fenfei |
author_sort | Shao, Xiaoliang |
collection | PubMed |
description | Recirculating ventilation systems may act as carriers of hazardous substances. The long-term prediction of the dynamic distribution of contaminants in this type of system is crucial for the evaluation of pollution and further design of more efficient ventilation systems. However, few convenient methods can predict the dynamic distribution of contaminants, because the dynamic supply air concentrations resulting from air recirculation are unknown, especially over long time periods, such as months or years. In this study, a novel method is proposed to predict the dynamic distribution of contaminants over a long time period in a complex recirculating ventilation system, where an algebraic expression based on the indices of the response coefficient is applied to account for the relationship between the contaminant distribution inside the room and various boundary conditions. The method is established by obtaining comprehensive mathematical descriptions of the relationships between concentrations of contaminants in the air handling units, supply air inlets, return air outlets, and fresh air. Hourly supply air concentrations can be easily obtained by solving a matrix, and the dynamic distribution of contaminants is then calculated using an expression based on the response coefficient. The reliability of the proposed method is analyzed by both experimental and numerical methods. A simplified method is suggested to accelerate the time-consuming calculation of the response coefficient. The proposed method is beneficial for predicting three-dimensional dynamic distribution of contaminants in complex ventilation systems with an acceptable accuracy and time cost. |
format | Online Article Text |
id | pubmed-7126526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71265262020-04-08 Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system Shao, Xiaoliang Li, Xianting Ma, Xiaojun Zhu, Fenfei Build Environ Article Recirculating ventilation systems may act as carriers of hazardous substances. The long-term prediction of the dynamic distribution of contaminants in this type of system is crucial for the evaluation of pollution and further design of more efficient ventilation systems. However, few convenient methods can predict the dynamic distribution of contaminants, because the dynamic supply air concentrations resulting from air recirculation are unknown, especially over long time periods, such as months or years. In this study, a novel method is proposed to predict the dynamic distribution of contaminants over a long time period in a complex recirculating ventilation system, where an algebraic expression based on the indices of the response coefficient is applied to account for the relationship between the contaminant distribution inside the room and various boundary conditions. The method is established by obtaining comprehensive mathematical descriptions of the relationships between concentrations of contaminants in the air handling units, supply air inlets, return air outlets, and fresh air. Hourly supply air concentrations can be easily obtained by solving a matrix, and the dynamic distribution of contaminants is then calculated using an expression based on the response coefficient. The reliability of the proposed method is analyzed by both experimental and numerical methods. A simplified method is suggested to accelerate the time-consuming calculation of the response coefficient. The proposed method is beneficial for predicting three-dimensional dynamic distribution of contaminants in complex ventilation systems with an acceptable accuracy and time cost. Elsevier Ltd. 2017-08-15 2017-05-10 /pmc/articles/PMC7126526/ /pubmed/32287971 http://dx.doi.org/10.1016/j.buildenv.2017.05.012 Text en © 2017 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Shao, Xiaoliang Li, Xianting Ma, Xiaojun Zhu, Fenfei Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
title | Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
title_full | Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
title_fullStr | Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
title_full_unstemmed | Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
title_short | Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
title_sort | long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126526/ https://www.ncbi.nlm.nih.gov/pubmed/32287971 http://dx.doi.org/10.1016/j.buildenv.2017.05.012 |
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