FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations [An article from: Atmospheric Environment] Buy on Amazon

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FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations [An article from: Atmospheric Environment]

Book Details

PublisherElsevier
ISBN / ASINB000RR1FSW
ISBN-13978B000RR1FS9
MarketplaceFrance  🇫🇷

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This digital document is a journal article from Atmospheric Environment, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
The FLACS CFD model, which can be used to estimate the flow and dispersion around buildings and other large roughness obstacles, has been evaluated with tracer data from several field experiments involving obstacle arrays. The following experiments were used in the evaluation exercise: Kit Fox (52 trials with puff and plume releases of slightly dense CO"2 gas in arrays of billboard-shaped obstacles), MUST (37 trials with puff releases of neutrally buoyant tracer gas in an array of 120 shipping containers), Prairie Grass (43 trials with continuous plume releases of neutrally buoyant tracer gas over a flat agricultural field), and the EMU L-shaped building (a wind tunnel experiment involving a release from an open door in the courtyard area of an L-shaped building). The primary focus is on the maximum concentration on the monitoring arcs. The performance statistics are consistently fairly good, with a median of 86% of the predictions within a factor of two of the observations, a median relative bias suggesting a 20% underprediction, a median relative scatter of about 50%, and a median 20% underprediction of the overall experiment maximum. These results are all well within the criteria of acceptance for dispersion models. Evaluations with the EMU L-shaped building data show that 72% of FLACS predictions are within a factor of two of observations, and that the model can predict the dimensions of the recirculating cavity behind the building within a factor of two. It is suggested that these extensive data sets involving tracer releases in obstacle arrays be used to evaluate other CFD models.
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