Abstract

Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is mostly by intuition and experience rather than by systematic design. To develop a sensor system design methodology, the proper selection of an indoor airflow model is needed. Various indoor airflow models exist in the literature, from complex computational fluid dynamics (CFD) to simpler approaches such as multizone and zonal models. Airflow models provide the contaminant concentration data, to which an optimization method can be applied to design sensor systems. The authors utilized a subzonal modeling approach when using a multizone model and were the first to utilize a zonal model for systematic sensor system design. The objective of the study was to examine whether or not data from a simpler airflow model could be used to design sensor systems capable of performing just as well as those designed using data from more complex CFD models. Three test environments, a small office, a large hall, and an office suite were examined. Results showed that when a unique sensor system design was not needed, sensor systems designed using data from simpler airflow models could perform just as well as those designed using CFD data. Further, only for the small office did the common engineering sensor system design practice of placing a sensor at the exhaust result in sensor system performance that was equivalent to one designed using CFD data.

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