Implications of advanced computational methods for reactivity initiated accidents in nuclear reactors.

• Autor(a) principal: Busquim e Silva, Rodney Aparecido
• Data de Publicação: 2015
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
• Texto Completo: http://www.teses.usp.br/teses/disponiveis/3/3139/tde-20072016-142605/
• topic: Análise do núcleo; Cinética pontual inversa; Engenharia nuclear; Extended Kalman filter; Filtros de Kalman; Inverse point kinetics; Nuclear core analysis; Nuclear power plant; PARCS 3D; PARCS 3D; Reactivity; Reatividade; Reatores nucleares; RELAP5; RELAP5; Thermal hydraulic and neutronics coupling

Advanced computational tools are applied to simulate a nuclear power plant (NPP) control rod assembly ejection (CRE) accident. The impact of these reactivity-initiated accidents (RIAs) on core reactivity behavior, 3D power distribution and stochastic reactivity estimation are evaluated. The three tools used are: the thermal-hydraulic (TH) RELAP5 (R5) code, the neutronic (NK) PARCS (P3D) code, and the coupled version P3D/R5, with specially developed linkage using the environment code MATLAB. This study considers three different-size cores: NPP1 (2772 MWt); NPP2 (530 MWt); and NPP3 (1061 MWt). The three cores have the same general design and control rod assembly (CRA) positions, and the ejected CRA has similar worth and at the same rod ejection pace. The CRE is assessed under both hot zero power (HZP) and hot full power (HFP) conditions. The analyses indicate that RIA modeling and simulation should be carried out through a systematic coding and configuration approaches, otherwise the results will not capture the true transient behavior of the core under analysis. The simulation of one code depends on the appropriate configuration of parameters generated by the other code and on the correct determination of the TH/NK mapping weight factors for the various mesh regions in each of the models. From the design point of view, the standalone codes predict milder magnitude of power and reactivity increase compared to the coupled P3D/R5 simulation. The magnitudes of reduced peak power and reactivity become larger as the core size shrinks. The HFP simulation shows that the three NPPs have the same transient peak value, but the post-transient steady power is lower for a smaller core. The HZP analysis indicates that the transient peak is lower for the smaller core, but the post-transient power occurs at the same level. The three-dimensional (3D) power distributions are different among the HFP and HZP cases, but do not depend on the size of the core. The results indicate: i) HFP: core power increases in the area surrounding the ejected rod/bank assembly, and this increase becomes lower as the NPPs shrinks however, the power is well-distributed after the transient; and ii) HZP: the area surrounding the CRA stays hotter, but the 3D peak assembly factor becomes lower, during and after the transients, as the NPPs shrinks. These features confirm that the smaller cores yield a safer response to a given inserted reactivity compared to larger cores. A stochastic extended Kalman filter (EKF) algorithm is implemented to estimate the reactivity based on the reactor power profile, after the addition of random noise. The inverse point kinetics (IPK) deterministic method is also implemented and the results of the application of EKF and IPK are compared to the P3D/R5 simulation. The following sophisticated strategies made the EKF algorithm robust and accurate: the system is modeled by a set of continuous time nonlinear stochastic differential equations; the code uses a time step directly based on the power measured and applies that to the model for online discretization and linearization; filter tuning goes automatically up from the first time step; and the state noise covariance matrix is updated online at each time step. It was found that the IPK reactivity has higher noise content compared to the EKF reactivity for all cases. Thus, the EKF presents superior and more accurate results. Furthermore, under a small reactivity insertion, the IPK reactivity varies widely from positive to negative values: this variation is not observed within the EKF. A sensitivity analysis for three distinct standard deviation (SD) noise measurements suggests that EKF is superior to IPK method, independent of the noise load magnitude. As the noise content increases, the error between the IPK and P3D/R5 reactivity also increases. A sensitivity analysis for five distinct carry-over effects of different random noise loads indicates that the random addition of different noise loads to the reactor power does not change the overall performance of both algorithms.