2021
DOI: 10.1016/j.tust.2020.103752
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Temperature distribution in a blocked tunnel with one closed portal under natural ventilation

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Cited by 25 publications
(16 citation statements)
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“…In general, the plotted values show similar trends. The present measurements, in particular, are found to agree very well with the predictions proposed by Wang et al (2021) but slightly higher than the other models or data. This is mainly because the fire scenarios investigated in Wang et al (2021)'s research, i.e., fire burns between the closed end and blockage, are highly coincide with the fire scenarios explored herein while heat accumulation caused by these two factors are not addressed in the other plotted data.…”
Section: Computational Grid and Validationsupporting
confidence: 85%
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“…In general, the plotted values show similar trends. The present measurements, in particular, are found to agree very well with the predictions proposed by Wang et al (2021) but slightly higher than the other models or data. This is mainly because the fire scenarios investigated in Wang et al (2021)'s research, i.e., fire burns between the closed end and blockage, are highly coincide with the fire scenarios explored herein while heat accumulation caused by these two factors are not addressed in the other plotted data.…”
Section: Computational Grid and Validationsupporting
confidence: 85%
“…From the above analysis, it is reasonable to deduce that blockage certainly has impacts on the ceiling temperature profiles because the dominated factor, i.e., burning rate, increases as blockage occurs. Since the closed end and blockage effect are rarely simultaneously investigated in the previous researches, the published predictions and experimental measurements from similar fire scenarios, including the typical tunnel fire (Li et al, 2011), underground space with one closed end (Ji et al, 2011;Gao et al, 2021), tunnel with two closed ends (Yao et al, 2017), and tunnel with blockage (Tang et al, 2017;Wang et al, 2021), are plotted together with the present measurements in Figure 8. In general, the plotted values show similar trends.…”
Section: Computational Grid and Validationmentioning
confidence: 99%
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“…For example, Alpert [ 8 ] and Kurioka et al [ 9 ] developed maximum temperature prediction models for a tunnel fire. Moreover, researchers have carried out studies on the factors affecting the maximum temperature, such as the location and number of fire sources [ 10 12 ], the shape of tunnel cross-section [ 13 , 14 ], velocity of longitudinal ventilation [ 15 ], vehicle blockage in a tunnel [ 16 , 17 ], ambient pressure [ 18 , 19 ], and the slope of the vertical shaft [ 20 ]. In addition to the maximum temperature, researchers have also investigated temperature decay.…”
Section: Introductionmentioning
confidence: 99%