It is necessary to understand the features of air pressure in a drainage stack of a high-rise building for properly designing and operating a drainage system. This paper presents a mathematical model for predicting th...It is necessary to understand the features of air pressure in a drainage stack of a high-rise building for properly designing and operating a drainage system. This paper presents a mathematical model for predicting the stack performance. A step function is used to describe the effect of the air entrainment caused by the water discharged from branch pipes. An additional source term is introduced to reflect the gas-liquid interphase interaction （GLII） and stack base effect. The drainage stack is divided into upper and base parts. The air pressure in the upper part is predicted by a total variation diminishing （TVD） scheme, while in the base part, it is predicted by a characteristic line method （CLM）. The predicted results are compared with the data measured in a real-scale high- rise test building. It is found that the additional source term in the present model is effective. It intensively influences the air pressure distribution in the stack. The air pressure is also sensitive to the velocity-adjusting parameter （VAP）, the branch pipe air entrainment, and the conditions on the stack bottom.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 10972212)
文摘It is necessary to understand the features of air pressure in a drainage stack of a high-rise building for properly designing and operating a drainage system. This paper presents a mathematical model for predicting the stack performance. A step function is used to describe the effect of the air entrainment caused by the water discharged from branch pipes. An additional source term is introduced to reflect the gas-liquid interphase interaction （GLII） and stack base effect. The drainage stack is divided into upper and base parts. The air pressure in the upper part is predicted by a total variation diminishing （TVD） scheme, while in the base part, it is predicted by a characteristic line method （CLM）. The predicted results are compared with the data measured in a real-scale high- rise test building. It is found that the additional source term in the present model is effective. It intensively influences the air pressure distribution in the stack. The air pressure is also sensitive to the velocity-adjusting parameter （VAP）, the branch pipe air entrainment, and the conditions on the stack bottom.
