MODELING OF AIRFLOW AND CONTAMINANT DISTRIBUTION

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21. DESCRIPTION The broad, long-term objective of this research is to validate computational fluid dynamics (CFD) modeling technique for use in predicting workplace exposure to hazardous substances and in evaluation of control or intervention alternatives. The specific aims of the project are to answer the following questions: a) Can CFD codes be written to stimulate complex workspaces? and b) Can these codes be applied to three specific applications (open tank processes, TB isolation rooms, hospital waiting rooms)? CFD modeling and simulation may be very useful tools in design and troubleshooting of ventilation systems used to control release of hazardous substances in workplaces. However, before these methods are widely accepted, they need to be validated. Models to describe air flow and concentration distributions in and around open tank type processes and to describe airflow and temperature distribution in large spaces have been developed. These models are largely two-dimensional and have been validated in the laboratory with controlled local exhaust ventilation (LEV) hood flow rates and crossdraft velocities (magnitude and direction). The results of the laboratory experiments and CFD simulations show impressive agreement. I have conducted field studies of industrial hospital ventilation systems resulting in large data sets collected during normal operations. The proposed research will develop three-dimensional models and validate them with laboratory experiments under controlled conditions and further to apply the models to the field data to determine the applicability of CFD simulations to "real life" situations. This project will result in CFD models that are applicable to complicated industrial and hospital spaces and provide information on the validity of using CFD models to describe airflow and contaminant distribution in these spaces. CFD modeling, if validated, should result in more efficient assessment of hazardous conditions and evaluation of intervention strategies.