期刊
ENERGY
卷 210, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.118601
关键词
Trombe wall; Natural ventilation; Renewable energy; Tunnel; CFD modelling; Fire safety
资金
- Australian Government through the Australian Research Council [DE200100892, DE190100217]
- National Natural Science Foundation of China [51776192]
- State Key Laboratory of Fire Science (SKLFS) at University of Science and Technology of China (USTC) [HZ2019-KF15]
- Australian Research Council [DE190100217] Funding Source: Australian Research Council
Although solar chimney as a reliable passive renewable energy system has been widely adopted in buildings, its application in the tunnel is so far limited. By developing a validated numerical model, this study systematically investigated four critical factors that govern the effectiveness of solar chimney in tunnel applications, such as cavity height (h(c)), cavity gap (L), solar radiation, and fire size. It was known that the chimney height in tunnel shows a relatively higher impact on the natural ventilation when comparing to the applications in building, but in an opposite position for the solar radiation. The natural ventilation rate is proportional to h(c)(0.69) in the tunnel, but the power is between 0.5 and 2/3 for building applications. The power for solar radiation in tunnel is 0.34, where it is 0.572 for building. It was obtained from an orthogonal analysis that chimney height presents a relatively higher impact on the natural ventilation performance of a solar chimney in the tunnel, but it shows an opposite phenomenon under the smoke exhaustion model. Under both natural ventilation and smoke exhaustion modes, chimney height and cavity gap show relatively stronger influence on the performance than that from the solar radiation. A theoretical model was also developed that considers both the vertically linear and horizontally parabolic temperature distributions inside the chimney cavity. The predictions when considering both distributions agree reasonably well with those numerical results, which drops about 20.6% when comparing to the predictions of those traditional models without the considerations. (C) 2020 Elsevier Ltd. All rights reserved.
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