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  5. Theoretical models for predicting ventilation performance of vertical solar chimneys in tunnels

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Article
English
2024

Theoretical models for predicting ventilation performance of vertical solar chimneys in tunnels

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0 Files

English
2024
Renewable Energy
Vol 232
DOI: 10.1016/j.renene.2024.121023

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Long Shi
Long Shi

University Of Science And Technology Of China

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Youbo Huang
Bing Wang
Chengjia Luo
+4 more

Abstract

Solar chimney as a reliable renewable energy system has been primarily utilized for building ventilation, but its application in the tunnel is rarely explored. This study develops theoretical models to predict the ventilation performance of vertical solar chimney in urban tunnel. Five temperature distribution types within the chimney cavity are analyzed, including uniform, vertically linear, horizontally semi-parabolic, two piecewise semi-parabolic in the depth direction, and three-dimensional parabolic profiles. The theoretical models consider the effect of chimney configuration, tunnel geometry, glazing materials, and solar radiation intensity on airflow rate through solar chimney. Validation against experimental data and numerical simulation shows that considering three-dimensional temperature distributions results in an average 11 % deviation from validation data, outperforming assumptions of uniform (29.3 % deviation) or lower-dimensional profiles. The volumetric flow rate through solar chimney exponentially decreased with h/w and h/d that the optimum ratio of h/d is 10. The airflow rate linearly increased with 0.14 power of glazing absorptivity. This analysis provides technical guidance for optimizing solar chimney design in tunnels, enhancing natural ventilation, and reducing energy consumption for mechanical ventilation systems.

How to cite this publication

Youbo Huang, Bing Wang, Chengjia Luo, Long Shi, Ning Lü, Bingyan Dong, Hua Zhong (2024). Theoretical models for predicting ventilation performance of vertical solar chimneys in tunnels. Renewable Energy, 232, pp. 121023-121023, DOI: 10.1016/j.renene.2024.121023.

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Publication Details

Type

Article

Year

2024

Authors

7

Datasets

0

Total Files

0

Language

English

Journal

Renewable Energy

DOI

10.1016/j.renene.2024.121023

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