Nuclear Technology / Volume 175 / Number 1 / July 2011 / Pages 286-300
Technical Paper / Special Issue on the 16th Biennial Topical Meeting of the Radiation Protection and Shielding Division / Radiation Transport and Protection
Oak Ridge National Laboratory (ORNL) has been engaged in the development and testing of a computational system that would use a grid of activation foil detectors to provide postdetonation forensic information from a nuclear device detonation. ORNL has developed a high-performance, three-dimensional (3-D) deterministic radiation transport code called Denovo. Denovo solves the multigroup discrete ordinates (SN) equations and can output 3-D data in a platform-independent format that can be efficiently analyzed using parallel, high-performance visualization tools. To evaluate the sensitivities and uncertainties associated with the deterministic computational method numerics, a numerical study on the New York City Times Square model was conducted using Denovo. In particular, the sensitivities and uncertainties associated with various components of the calculational method were systematically investigated, including (a) the Legendre polynomial expansion order of the scattering cross sections, (b) the angular quadrature, (c) multigroup energy binning, (d) spatial mesh sizes, (e) the material compositions of the building models, (f) the composition of the foundations upon which the buildings rest (e.g., ground, concrete, or asphalt), and (g) the amount of detail included in the building models. Although Denovo may calculate the idealized model well, there may be uncertainty in the results because of slight departures of the above-named parameters from those used in the idealized calculations. Fluxes and activities at selected locations from perturbed calculations are compared with corresponding values from the idealized or base case to determine the sensitivities associated with specified parameter changes. Results indicate that uncertainties related to numerics can be controlled by using higher fidelity models, but more work is needed to control the uncertainties related to the model.