Comparison of NARAC predicted and measured ground deposition as a function of downwind distance shows the improvement produced by the use of a dynamic cloud rise algorithm rather than a static cloud model. (Courtesy of Kevin Foster)
Modeling of radiological dispersal devices (RDD) requires dispersion models that treat a variety of radionuclides, material types, and particle sizes. NARAC develops more accurate near-source and downwind RDD models are developed through the use of the latest experimental data on explosive dispersal of materials. Examples include:
- Implementation of a dynamic cloud rise model that significantly improves the match to experimental deposition data over that resulting from a static cloud rise approach
- Improved cloud rise thermal stabilization heights derived from field experiments
- Addition of a "ballistic” particle correction derived from experiments conducted by Sandia National Laboratories (SNL) that show that larger particles (>100 micrometer diameter) produced by some types of RDDs are ejected and leave the influence of the thermally buoyant cloud faster than previously assumed
- Investigation of improved methods for coupling particles to the rising buoyant gas cloud
- Evaluation of RDD models against data from international field experiments using radionuclide surrogates
The incorporation of ballistic particle behavior (right panel) produces a dispersion pattern with increased near-source ground contamination but significantly reduced downwind concentrations relative to the original model prediction of a hypothetical release (left panel).
NARAC’s Aeolus model can operationally simulate dispersal from an RDD in an urban environment. Video is of a hypothetical simulation of urban release.