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Undeclared uranium hitches a ride on cobalt exports from Congo, study says
Philippe (left) and Manzuk quantified the amount of uranium that has been exported from the DRC in cobalt shipments or left behind in the environment. (Photo: Joel Hallberg/UW–Madison)
Researchers at the University of Wisconsin–Madison and Princeton University have published a study in Nature Communications that calls attention to a blind spot in nuclear nonproliferation: The Democratic Republic of the Congo (DRC) has exported thousands of metric tons of uranium, and there is no accounting for where it has gone.
In partnership with Lighthouse Reports and the Financial Times, UW–Madison nuclear engineering professor and nuclear security expert Sébastien Philippe and Ryan Manzuk, a geologist and research fellow in Philippe’s group and at Princeton, conducted the study using countrywide mineralization and geochemical data.
Douglas E. Peplow
Nuclear Technology | Volume 174 | Number 2 | May 2011 | Pages 289-313
Technical Paper | Special Issue on the SCALE Nuclear Analysis Code System / Radiation Protection | doi.org/10.13182/NT174-289
Articles are hosted by Taylor and Francis Online.
Monte Carlo shielding analysis capabilities in SCALE 6 are centered on the Consistent Adjoint Driven Importance Sampling (CADIS) methodology. CADIS is used to create an importance map for space/energy weight windows as well as a biased source distribution. New to SCALE 6 are the Monaco functional module, a multigroup fixed-source Monte Carlo transport code, and the Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) sequence. MAVRIC uses the Denovo code (also new to SCALE 6) to compute coarse-mesh discrete ordinates solutions that are used by CADIS to form an importance map and biased source distribution for the Monaco Monte Carlo code. MAVRIC allows the user to optimize the Monaco calculation for a specific tally using the CADIS method with little extra input compared with a standard Monte Carlo calculation. When computing several tallies at once or a mesh tally over a large volume of space, an extension of the CADIS method called FW-CADIS can be used to help the Monte Carlo simulation spread particles over phase space to obtain more uniform relative uncertainties.