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MODERN TUNNELLING TECHNOLOGY 2016, Vol. 53 Issue (6) :115-122    DOI:
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Model Optimization and Computational Analysis of a Ventilation Network for Large Underground Petroleum Storage Caverns
(Key Laboratory of Transportation Tunnel Engineering, Ministry of Education, Southwest Jiaotong University, Chengdu 610031)
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Abstract Usually it is necessary to use forced ventilation or a large number of ventilation shafts to solve construc? tion phase ventilation problems in large scale underground caverns. Since ventilation shafts are mostly set up in accordance with experience or site conditions, they are generally located at a relatively shallow depth in an oil storage cavern, resulting in a“disordered”ventilation network, leading to poor local ventilation. Shaft depth and the temperature difference between inside and outside have a great effect on the natural ventilation of the shaft. Taking the construction ventilation of the Jinzhou underground petroleum storage cavern as an example, this paper introduces a calculation method for gallery ventilation based on ventilation network theory in order to study the ventilation calculation and equipment configuration for three ventilation configurations in a cavern group. The results show that using the entrance of the construction adits (construction transport channels from the ground into the cavern) as a viable air outlet and forcing in fresh air with an axial flow fan at the shaft mouth results in an orderly circulation in the ventilation network. Using a shaft to exhaust air requires more than one fan operating at the same time, which means higher costs and, additionally, the natural ventilation effect of shafts is not sufficient in winter. When the shaft is connected to the cavern (i.e., the upper layer of the petroleum storage cavern is completed), it is possible to adopt forced ventilation supplemented by jet flow, or it may be necessary to use full jet flow if the ventilation distance is long.
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ZHANG Heng- Lin- Fang- Sun-Jian-Chun
KeywordsCavern group   Construction ventilation   Ventilation network   Computational analysis   Ventilation moni? toring     
Abstract: Usually it is necessary to use forced ventilation or a large number of ventilation shafts to solve construc? tion phase ventilation problems in large scale underground caverns. Since ventilation shafts are mostly set up in accordance with experience or site conditions, they are generally located at a relatively shallow depth in an oil storage cavern, resulting in a“disordered”ventilation network, leading to poor local ventilation. Shaft depth and the temperature difference between inside and outside have a great effect on the natural ventilation of the shaft. Taking the construction ventilation of the Jinzhou underground petroleum storage cavern as an example, this paper introduces a calculation method for gallery ventilation based on ventilation network theory in order to study the ventilation calculation and equipment configuration for three ventilation configurations in a cavern group. The results show that using the entrance of the construction adits (construction transport channels from the ground into the cavern) as a viable air outlet and forcing in fresh air with an axial flow fan at the shaft mouth results in an orderly circulation in the ventilation network. Using a shaft to exhaust air requires more than one fan operating at the same time, which means higher costs and, additionally, the natural ventilation effect of shafts is not sufficient in winter. When the shaft is connected to the cavern (i.e., the upper layer of the petroleum storage cavern is completed), it is possible to adopt forced ventilation supplemented by jet flow, or it may be necessary to use full jet flow if the ventilation distance is long.
KeywordsCavern group,   Construction ventilation,   Ventilation network,   Computational analysis,   Ventilation moni? toring     
Cite this article:   
ZHANG Heng- Lin- Fang- Sun-Jian-Chun .Model Optimization and Computational Analysis of a Ventilation Network for Large Underground Petroleum Storage Caverns[J]  MODERN TUNNELLING TECHNOLOGY, 2016,V53(6): 115-122
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