Simulation of Fog Oil Deposition During Military Training Operations

Abstract

In this study we evaluate the ability to simulate deposition of a fog oil (Standard Grade Fuel Number 2 or SGF2) obscurant on the ground using the SCIPuff aerosol transport model. Model results are compared to actual deposition of fog oil measure on the ground during two military training exercises in Alaska. One exercise took place during late summer; the other occurred during midwinter. The results show that SCIPuff can be used to give a general picture of the spatial deposition of fog oil by successfully reproducing the overall trends of the field data and predicting the deposition to within an order of magnitude or better. Improved predictive capability might be realized using more sophisticated flow solvers employing computational fluid dynamics (CFD) and large eddy simulation (LES) methods. However, use of CFD and LES would increase significantly the computational expense required. This study shows that model results are sensitive to the aerosol droplet size distribution used and that there appears to be some dependency of this size distribution on air temperature or fog oil used (pure SGF2 vs. SGF2:diesel mix). To improve the predictive modeling capability of aerosol transport models, it is recommended that further work be accomplished to quantify the environmental and mixture effects on the airborne fog oil droplet size distribution. In lieu of this information, an estimate of the deposition, good to within about an order of magnitude, can be obtained using a lognormal droplet size distribution with a mean droplet size of 1 micrometer and variance of 1.7.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2008
Accession Number
ADA491391

Entities

People

  • Robert B. Haehnel

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Temperature
  • Boundary Layer
  • Computational Fluid Dynamics
  • Diesel Fuels
  • Dispersions
  • Engineering
  • Environment
  • Fluid Dynamics
  • Fluid Flow
  • Large Eddy Simulation
  • Meteorological Data
  • Military Training
  • Particle Size
  • Predictive Modeling
  • Simulations
  • Standards
  • Training

Readers

  • Atmospheric Remote Sensing.
  • Computational Fluid Dynamics (CFD)
  • Petroleum Engineering