Hazard Response Modeling Uncertainty (A Quantitative Method). Volume 2. Evaluation of Commonly Used Hazardous Gas Dispersion Models

Abstract

The overall objective of this project is to develop and test computer software containing a quantitative method for estimating the uncertainty in PC- based hazard response models. This software is to be used by planners and engineers in order to evaluate the predictions of hazard response models with field observations and determine the confidence intervals on these predictions. This particular volume (II) provides an example of the application of the software to 14 typical hazard response models and 8 sets of field data. The U.S Air Force and the American Petroleum Institute, among others, have increased emphasis on calculating toxic corridors due to releases of hazardous chemical into the air. There are dozens of PC-based computer models recently developed in order to calculate these toxic corridors. However, the uncertainties in these models have not been adequately determined, partly due to the lack of a standardized quantitative method that could be applied to these models. Individual model developers generally present a limited evaluation of their own model, and the USEPA has published some partial evaluations, but a comprehensive study has not yet been completed.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1993
Accession Number
ADA270095

Entities

People

  • D. G. Strimaitis
  • Joseph Chang
  • Steven R. Hanna

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Atmospheric Motion
  • Chemistry
  • Computational Science
  • Computer Programs
  • Computers
  • Crystal Structure
  • Databases
  • Dielectric Gases
  • Gases
  • Heat Energy
  • Heat Of Vaporization
  • Latent Heat
  • Liquids
  • Meteorology
  • Monte Carlo Method
  • Thermodynamics

Readers

  • Computer Science.
  • Environmental Remediation and Restoration.
  • Regression Analysis.