Abstract
LEV is a ventilation system that collects and sucks out particles such as dusts, mists, gases, vapors or fumes out of work station, so that they can’t be breathed in by occupants. There is a lot of LEV allocated and installed in order to help protecting occupants’ health but it doesn’t work properly. To overcome this issue, computational fluid dynamics (CFD) will be implemented. Past studies CFD techniques represent a very significant improvement of air ventilation systems. However, CFD is just a tool in prediction model, which can lead to inaccuracy of predicting airflow due to problems with pre-processing, solver and post-processing with parameter from actual experimental results. As of yet, it is not possible to 100% accurately simulate airflow around a body. These codes are simply models which are close to that of a real flow, but not an exact match. All of these require validation to help minimizing percentage error in CFD methodology. Several strategies are needed to boost effectiveness of LEV in terms of predicting airflow in a geometry model. The outcome of this research can be used as a benchmark or guideline for industries to help improving indoor air quality (IAQ).
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