A best-estimate reactor core monitor using state feedback strategies to reduce uncertainties

The development and demonstration of a new algorithm to reduce modeling and state-estimation uncertainty in best-estimate simulation codes has been in vestigated. Demonstration is given by way of a prototype reactor core monit or. The architecture of this monitor integrates a control-theory-based, dis tributed-parameter estimation technique into a production-grade best-estima te simulation code. The Kalman Filter-Sequential Least-Squares (KFSLS) para meter estimation algorithm has been extended for application into the compu tational environment of the best-estimate simulation code RELAPS-3D. In con trol system terminology this configuration can be thought of as a "best-est imate " observer. The application to a distributed-parameter reactor system involves a unique modal model that approximates physical components, such as the reactor, by describing both states and parameters by art orthogonal expansion. The basic KFSLS parameter estimation is used to dynamically refi ne a spatially varying (distributed) parameter. The application of the dist ributed-parameter estimator is expected to complement a traditional nonline ar best-estimate simulation code by providing a mechanism for reducing both code input (modeling) and output (state-estimation) uncertainty in complex , distributed-parameter systems.