A novel method to improve dose assessment due to severe NPP accidents based on field measurements and particle swarm optimization

Severe nuclear power plant (NPP) accidents are those which involve significant core degradation and lead the plant to conditions more severe than a design basis accident. Under such conditions the accident progression might become unpredictable and the source term estimation, imprecise by orders of magnitude. The consequence is a dose assessment very far from the reality and a deficient decision making support. This work presents a novel approach to improve accuracy of dose estimation, based on field measurements and particle swarm optimization (PSO) algorithm. The main idea is to determine a correction matrix, which once applied to the originally estimated (incorrect) dose distribution map, generates a corrected one, which better fits to the field measurements. The proposed correction matrix is the result of a concatenation of geometric transformations and an amplification/attenuation factor, aimed to fit the shape of the original map and radiation intensities in order to match the field measurements. Finding the optimum transformations (correction matrix) is, however a complex nonlinear optimization problem, which has been successfully solved by using a PSO algorithm. Results demonstrate that PSO was able to find good correction transformations, which can be used to better project future dose distributions and, consequently, improve decision making support.