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Computational Fluid Dynamics Validation Utilizing a Tracer Gas Study Related to a Mine Mill Area Toxic Gas Release for Emergency Response Planning

NAFEMS International Journal of CFD Case Studies

Volume 11, April 2016

ISSN 1462-236X


Computational Fluid Dynamics Validation Utilizing a Tracer Gas Study Related to a Mine Mill Area Toxic Gas Release for Emergency Response Planning

D Hall1, C Strode1, J Rasmuson1, A Korchevskiy1 and R Strode1
1Chemistry & Industrial Hygiene, Inc. 10201 W. 43 Ave., Wheat Ridge, CO 80033, USA

https://doi.org/10.59972/hrt8rrs2

Keywords: Tracer Gas, Emergency Response Planning, Dispersion and Exposure Characterisation

 


Abstract

Context:
Many dispersion models (e.g. DEGADIS, SLAB, INPUFF, and ALOHA) have been developed by regulatory agencies for emergency response related to dense toxic gas releases. The National Oceanic and Atmospheric Administration’s (NOAA) Area Locations of Hazardous Atmospheres (ALOHA) software is an example one such model. However, such models typically over-predict dense toxic gas plume dispersion concentrations and do not take into account complex terrain or complex building canyon geometries. This creates imprecise and inaccurate emergency response plans for industries that utilize such gases for production processes. The application of Computational Fluid Dynamics (CFD) mostly overcomes these challenges and provides a refined understanding of dense gas plume dispersion. Evaluating micro-scale atmospheric models is typically conducted in a wind tunnel tracer gas experiment; however, the one-hour tracer gas experiments utilized in this study evaluation were conducted in a real-world, full-scale, industrial setting. These same industries are often faced with worker health risks related to airborne respirable particulates and fibers with low settling velocities and where transport is dominated by air movement. Thus, it is anticipated that this evaluation may be applied to exposure characterization and risk assessment.

Objective:
To evaluate and validate CFD modeling as a predictor of environmental concentrations based on a dense-gas, supply-line rupture in a micro-scale area covering about four square kilometer (km).

Methods:
Two one-hour, continuous releases of a known mass of pure sulfur hexafluoride (SF6), a dense (molecular weight [MW] 146.1) tracer gas, were emitted from a simulated railcar supply-line rupture in a mountainous area with complex nearby industrial building geometries. During each release, 19 sampling points were distributed near and between more than 60 buildings (restricted primarily to downwind locations) and in open areas up to 1.5 km (0.93 miles) from the release point. A 16 km2 (6.2 square mile) CFD model domain was utilized to predict SF6 concentrations at the 19 tracer gas sampling points as a function of time since the release. Data collected from two onsite meteorological stations during the two releases were used to generate domain inlet wind velocities and small-scale wind direction changes near the release point. Comparison of modeled and measured tracer gas concentrations was completed and statistically evaluated.

Conclusions:
The CFD model predicted the time-averaged SF6 concentrations under varying atmospheric conditions with good precision and reasonable accuracy. The model generated for the first release met three of the five Hanna (Hanna, 2004) criteria and generally predicted the concentrations within a factor of two. However, attempting to model emissions under more extremely varying atmospheric conditions during a second release resulted in over prediction of actual measured concentrations by more than an order of magnitude at some locations.

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Cite this paper

D Hall, C Strode, J Rasmuson, A Korchevskiy, R Strode, Computational Fluid Dynamics Validation Utilizing a Tracer Gas Study Related to a Mine Mill Area Toxic Gas Release for Emergency Response Planning, NAFEMS International Journal of CFD Case Studies, Volume 11, 2016, Pages 31-46, https://doi.org/10.59972/hrt8rrs2

 

Document Details

ReferenceCFDJ11-2
AuthorsHall. D Strode. C Rasmuson. J Korchevskiy. A Strode. R
LanguageEnglish
TypeJournal Article
Date 4th January 2016
OrganisationChemistry & Industrial Hygiene

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