Blending Chem-Bio Dispersion Forecasts and Sensor Data
Abstract
In a chemical release incident, two important questions in hazard prediction and assessment are: Where are the sources located? and, What is the plumes dispersion profile? This report details the development, and testing of algorithms to address the two questions. SCIPUFF is the model of choice for forecasting the dispersion which is used in conjunction with sensor data and meteorological data for improving the forecast and the identification of the source parameters. The authors of this report have exploited simple models based on RIMPUFF and a shallow water model to initially test their algorithms prior to using them with SCIPUFF. The data assimilation algorithms illustrate the improved quality of the forecast of the plume profile and the source identification algorithms based on Genetic Algorithms has been tested to identify source characteristics and meteorological parameters with encouraging results.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 31, 2008
- Accession Number
- ADA513600
Entities
People
- Alex Pappachen James
- Anke Beyer-lout
- Gabriel Terejanu
- George Young
- Kerrie Long
- Peter Scott
- Puneet Singla
- Sue Ellen Haupt
- Tarunraj Singh
- Uma Konda
- Yang Cheng
Organizations
- Calspan-University of Buffalo Research Center