Numerical simulation of 222Rn profiling in an experimental chamber using CFD technique. (September 2020) - Agarwal, Tarun K.
Abstract: Measurement of indoor 222 Rn concentration and interpretation of distribution patterns are important for inhalation dosimetry in occupational and residential areas. Experimental determination of 222 Rn concentration distribution and estimation of inhalation doses depend on the underlying aspects such as calibration of the detectors, accuracy of the techniques etc. Therefore, 222 Rn concentration distribution needs to be very well understood in a closed domain for the controlled studies. In the recent times, Computational fluid dynamics (CFD) technique has gained a lot of attention for the prediction and visualization of indoor 222 Rn concentration profiles and their mixing ability in the domain. The present study aims to simulate the effect of forced mixing on the 222 Rn concentration profile in a 22 m 3 experimental chamber. This chamber is designed for carrying out the controlled experiments, calibration and inter-comparison studies of various types of 222 Rn detectors. Effect of different parameters such as time, flow rates, fan-off and fan-on conditions have been studied on the transient response, extent of the air mixing patterns and subsequently on 222 Rn concentration profile in the chamber. Further, Non uniformity index (NUI) is introduced as a measure of the uniformity of the distribution in the closed domain. NUI is estimated for different cases in order to efficiently interpret the effect of above mentioned parameters on 222 Rn profile in the chamber. This study will be useful to represent the turbulent conditions in real indoor domains and occupational facilities as U-mines during calibration and inter-comparison exercises of different 222 Rn detectors. Highlights: 222 Rn profiling in a 22 m 3 experimental chamber. Effect of time, flow rates, fan induced turbulence on mixing patterns of 222 Rn concentration profile. Non uniformity index (NUI) introduced as a measure of the uniformity of the distribution in the closed domain. Estimation of NUI for different cases in order to efficiently interpret parameters on 222 Rn profile.