Radiological Dispersion Device (RDD) Modeling

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 the Greenfield experiments being conducted in Israel
  • 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 recent Israeli and Canadian RDD 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 (left panel).