کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6479285 | 1428374 | 2017 | 10 صفحه PDF | دانلود رایگان |
- Automated CFD analysis has been used to study the transport of a pollutant which entered a room via the ventilation system.
- The speed of transport across different rooms was shown to be strongly dependent on the inverse of the air change rate.
- The equation describing this relationship could be used to rapidly predict pollutant transit times in real rooms.
- These times could be used in safety planning to reduce the effects of accidental releases of toxic airborne material.
- Automation of the CFD process coupled with high performance computing has been demonstrated to be a powerful tool.
Understanding mixing times for transient pollutants in mechanically ventilated rooms is important for resilience and safety planning for accidental releases of toxic material. There is a lack of information on the ability of simple models available to predict these times for ventilated spaces with different geometries and ventilation configurations. Three analytical mixing time models, including a novel jet transit based approach, have been selected for comparison with computational fluid dynamics (CFD) predictions for a wide range of cuboidal rooms with ceiling ventilation. A modelling tool has been developed, using open source and open source based software, to automatically build and run a large number of Reynolds averaged Navier-Stokes CFD models. The tool has been used to study the dependence of the chosen mixing metrics on room geometry and ventilation parameters, such as the air change rate, for a transient pollutant entering the room via the ventilation system. The room volume, shape, air change rate and vent layout were varied for each room using a Sobol sequence experimental design. The CFD tool has been used to assess the validity of the analytical mixing time models and to derive parameters for the scenarios of interest.
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Journal: Building and Environment - Volume 118, June 2017, Pages 313-322