Graphical User Interface Software for Gross Defect Detection at the Atucha-I Plant

At the Atucha-I pressurized heavy water reactor in Argentina, fuel assemblies in the spent fuel pools are stored by suspending them in two vertically stacked layers. This introduces the unique problem of verifying the presence of fuel in either layer without physically moving the fuel assemblies. Movement of fuel, especially from the lower layer, would involve a major effort on the part of the operator. Given that the facility uses both natural uranium and slightly enriched uranium at 0.85 w% 235U, and has been in operation since 1974, a wide range of burnups and cooling times can exist in any given pool. Additionally, while fuel assemblies are grouped together in a uniform fashion, the packing density from group to group can vary within a single pool. A tool called the Spent Fuel Neutron Counter (SFNC) was developed and successfully tested at the site to verify, in an in-situ condition, the presence of fuel up to burnups of 8,000 MWd/t. Since the neutron source term becomes a nonlinear function of burnup beyond this burnup, a new algorithm was developed to predict expected response from the SFNC at measurement locations covering the entire range of burnups, cooling times, and initial enrichments. With the aid of a static database of parameters including intrinsic sources and energy group-wise detector response functions, as well as explicit spent fuel information including burnups, cooling times, enrichment types, and spacing between fuel assemblies, an expected response for any given location can be calculated by summing the contributions from the relevant neighboring fuel assemblies. Thus, the new algorithm maps the expected responses across the various pools providing inspectors with a visual aid in verifying the presence of the spent fuel assemblies. This algorithm has been fully integrated into a standalone application built in LabVIEW. The GUI uses a step-by-step approach to allow the end-user to first calibrate the predicted database against a set of measurements with SFNC at selected locations where spent fuel is present. Once the database is calibrated it can be used to detect gross defects by comparing the measured signal to the one predicted by the database with differences beyond a set tolerance indicating missing fuel.