Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling

Indoor Air
X Liu, Z Zhai

Abstract

Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in f...Continue Reading

References

Jun 16, 2004·Current Opinion in Cell Biology·Lijun Sun, Zhijian J Chen

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Citations

Nov 3, 2010·Risk Analysis : an Official Publication of the Society for Risk Analysis·Gin Nam Sze-To, Christopher Y H Chao
May 19, 2011·Indoor Air·Y Li, P V Nielsen
Nov 21, 2020·Annals of Work Exposures and Health·Henk GoedeAnjoeka Pronk

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