Model Of Boiling Water Reactor Research Articles

Transition Core Modeling for Extended-Enrichment Accident-Tolerant Fuels in Light Water Reactors Using PARCS/Polaris

Current plans and efforts of reactor operators and vendors to include extended-enrichment (EE) fuel and accident-tolerant fuel (ATF) in current reactor fleets motivate the study of these changes in reactor physics analysis. This work uses the U.S. Nuclear Regulatory Commission’s core simulator PARCS to do the core calculation and the SCALE Polaris lattice physics code to generate the homogenized, few-group constants. In this work, both pressurized water reactor and boiling water reactor (BWR) colorset models are used to verify the proposed approach. The accuracy presented in the colorset models verified the capability of the PARCS/Polaris procedures for the transition core analysis in light water reactors. For the whole-core calculation, the ATF and EE-ATF transition core models were incorporated, in addition to the nominal core model. The BWR model was chosen to represent the entire core calculation due to its challenging design. The core parameters studied are the core power distribution, power peaking factor, Doppler temperature coefficients, and control rod worth at cold zero power and hot full power. When the core parameters of the transition cores are compared with those of the nominal core in PARCS, the results suggest that there is no drastic change in the core parameters for the implementation of ATF and EE fuels.

Sensitivity and uncertainty analysis of a reduced-order model of nonlinear BWR dynamics. III: Uncertainty analysis results

This work presents a paradigm analysis of the standard deviations induced in the state functions of a reduced-order model of Boiling Water Reactor (BWR) dynamics by the standard deviations in this model’s imprecisely known parameters and initial conditions. This analysis is performed in the model’s stable region in phase-space, where the state functions converge asymptotically to finite, time-independent values, as well as in the regions in phase-space where the model’s state functions asymptotically evolve into periodic limit-cycle oscillations. The region in phase-space where the model’s state functions behave chaotically is also analyzed. The standard deviations of the state functions in the various regions in phase-space are computed using the first-order sensitivities of the state functions with respect to the model’s imprecisely known parameters and initial conditions. It is shown that in the stable region, the standard deviations induced by the imprecisely known model parameters and initial conditions in each of the BWR-model’s state functions are very large immediately after perturbing the initially critical reactor, reaching values that are about 10 times larger than the respective state functions themselves. Although these standard deviations decay to small values after about 140 s into the transient, the amplitudes of the oscillations of these standard deviations at the start of the transient are so large as to possibly cause the BWR-system to transit from the stable region into an oscillatory region in phase-space. In the limit-cycle oscillatory regions in phase space, as well as in the chaotic region, the standard deviations of the state functions are very large, so that an accurate prediction of the actual value of the respective state functions has a low probability of success. The results obtained in this work indicate that the methods used herein should be implemented into the models used for the design and routine analysis of BWRs, in order to quantify deterministically the uncertainties induced into the operational characteristics of BWRs by the imprecisely known parameters underlying these models, particularly when BWRs are operated close to the limits of their stability regions/maps.

Sensitivity and uncertainty analysis of a reduced-order model of nonlinear BWR dynamics: I. Forward sensitivity analysis

This work applies the forward sensitivity analysis method to the reduced-order Boiling Water Reactor (BWR) model originally developed by March-Leuba, Perez and Cacuci [“Universality and Aperiodic Behavior of Nuclear Reactors,” Nucl. Sci. Eng. 86, 401, 1984.] to compute first-order sensitivities of the state functions (power, precursors concentration, reactivity, void fraction and fuel temperature) underlying this model. This reduced-order BWR model comprises point neutron kinetics equations coupled to thermal-hydraulics equations that describe the time evolution of the fuel temperature and coolant density in the recirculation loop. When the heat transfer from the reactor to the coolant is increased under high-power/low-flow operating conditions, this model’s state functions can bifurcate, via a period-doubling cascade of bifurcations, from their steady-state values into a chaotic dynamic evolution. Numerical results for the sensitivities of the state functions with respect to a model parameter that controls the injected neutron population are presented for the following regions in phase-space: (i) the stable region; (ii) the period-one region between the 1st-order bifurcation and the 2nd-order bifurcations; (iii) the period-two region between the 2nd-order bifurcations and the 3rd-order bifurcations; (iv) the period-three region between the 3rd-order bifurcations and the 4th-order bifurcations; (v) the aperiodic/chaotic region, which arises from an infinite cascade of period-doubling bifurcations produced when the heat transfer from reactor to coolant is increased past a critical value. In particular, it is shown that the amplitudes of the oscillations of the sensitivities in the chaotic region reach massive values ±O1023 already within 150 s after the initial perturbation. These results confirm the intuitive expectation that the BWR model is extremely unstable in the chaotic region.Ongoing work aims at performing a comprehensive sensitivity analysis of this reduced-order BWR model using the adjoint sensitivity analysis methodology, by investigating the time evolutions of the sensitivities of all state functions with respect to all model parameters, in the five regions in phase-space that are identified in this work. The sensitivities thus obtained will be used in a subsequent work to perform a comprehensive computation of the standard deviations that would be induced in the BWR model’s state functions by uncertainties that affect the BWR model’s imprecisely known parameter.

Simulation of Interactions and Emergent Failure Behavior During Complex System Design

Emergent behavior is a unique aspect of complex systems, where they exhibit behavior that is more complex than the sum of the behavior of their constituent parts. This behavior includes the propagation of faults between parts, and requires information on how the parts are connected. These parts can include software, electronic and mechanical components, hence requiring a capability to track emergent fault propagation paths as they cross the boundaries of technical disciplines. Prior work has introduced the functional failure identification and propagation (FFIP) simulation framework, which reveals the propagation of abnormal flow states and can thus be used to infer emergent system-wide behavior that may compromise the reliability of the system. An advantage of FFIP is that it is used to model early phase designs, before high cost commitments are made and before high fidelity models are available. This has also been a weakness in previous research on FFIP, since results depend on arbitrary choices for the values of model parameters and timing of critical events. Previously, FFIP has used a discrete set of flow state values and a simple behavioral logic; this has had the advantage of limiting the range of possible parameter values, but it has not been possible to model continuous process dynamics. In this paper, the FFIP framework has been extended to support continuous flow levels and linear modeling of component behavior based on first principles. Since this extension further expands the range of model parameter values, methods and tools for studying the impact of parameter value changes are introduced. The result is an evaluation of how the FFIP results are impacted by changes in the model parameters and the timing of critical events. The method is demonstrated on a boiling water reactor model (limited to the coolant recirculation and steam outlets) in order to focus the analysis of emergent fault behavior that could not have been identified with previously published versions of the FFIP framework.

Simulation of the Lower Head Boiling Water Reactor Vessel in a Severe Accident

The objective of this paper is the simulation and analysis of the BoilingWater Reactor (BWR) lower head during a severe accident. The COUPLE computer code was used in this work to model the heatup of the reactor core material that slumps in the lower head of the reactor pressure vessel. The prediction of the lower head failure is an important issue in the severe accidents field, due to the accident progression and the radiological consequences that are completely different with or without the failure of the Reactor Pressure Vessel (RPV). The release of molten material to the primary containment and the possibility of steam explosion may produce the failure of the primary containment with high radiological consequences. Then, it is important to have a detailed model in order to predict the behavior of the reactor vessel lower head in a severe accident. In this paper, a hypothetical simulation of a Loss of Coolant Accident (LOCA) with simultaneous loss of off-site power and without injection of cooling water is presented with the proposal to evaluate the temperature distribution and heatup of the lower part of the RPV. The SCDAPSIM/RELAP5 3.2 code was used to build the BWR model and conduct the numerical simulation.

Void reactivity feedback in BWRs with MA bearing MOX fuels

In this study, we analyzed a response of a boiling water reactor (BWR) core with homogeneous U–Pu–MA fuel to a change of an in-core void percentage. We employed a 3D, full core BWR model for the stochastic code MCNPX together with the continuous energy cross-section library ENDF B-VII.0. The results show that the main positive contribution to the void effect in the fuels with Pu–MA content around 11–15% consist of the decreased thermal capture in Pu-240, Pu-239 and Am-241 and increased fast and resonance fission of U-238, Pu-239 and Pu-240. We also present a core configuration with as much as 3.45% MA of heavy metal content that still provides a negative total void worth and also a global negative void coefficient in the vicinity the operational void profile. The corresponding Pu/MA fraction indicates that a BWR may be used for MA burning without entering into a positive void feedback regime. Eventually, we show why a 3D model is necessary for a correct assessment of the void behavior.

Importance Ranking of Parameters Affecting Reactor Dynamics Using the Taguchi Method

In the simulation of nuclear plant behavior through system codes, there are often uncertainties associated with the large number of model parameters required as code inputs. The use of the Taguchi method is investigated for the importance ranking of uncertainties when a single metric is used to characterize system performance. The proposed procedure is illustrated on a simplified boiling water reactor (BWR) model to determine the dominant parameters affecting the maximum limit cycle amplitude (MLCA) in BWRs. A reduced-order BWR model is used for the analysis. A regression model is also generated to predict the MLCA as a function of the parameter values in their assumed uncertainty regions. The results indicate that (a) 7 out of the 11 parameters (factors) under consideration have a significant impact on the MLCA, (b) a linear regression model can be constructed to predict the MLCA with 88% confidence, (c) higher-order effects of the control factors are negligible, and, (d) cross effects between the factors are negligible compared to their individual effects. The results also indicate that the use of the Taguchi method leads to a 99.4% reduction in the computational effort over a full factorial experiment design. The use of the Taguchi method is not proposed to replace the well-established conventional methods for sensitivity and uncertainty analysis but rather to assist them in the selection of the parameters that may require more detailed analysis.

Some Measure Theoretic Issues in Probabilistic Dynamics

Probabilistic dynamics (or continuous event tree approach) is a methodology used for the probabilistic risk assessment of systems where statistical dependence between failure events may arise because of indirect coupling through the controlled/monitored physical process and/or direct coupling through software/hardware/human intervention. Both the continuous and discrete time/space forms of the probabilistic dynamics frameworks assume that the set of possible trajectories describing the evolution of the system as a function of time in its state-space consists of measurable (and hence compact) subsets. Using a reduced-order boiling water reactor model, it is shown that this assumption may not be valid for systems of practical interest to nuclear engineering. The consequences of violating the measurability assumption on the probabilistic model accuracy are illustrated for the discrete time/state-space approach. Some guidelines for the choice of time/state discretization are also proposed.

Simplified distributed parameters BWR dynamic model for transient and stability analysis

This paper describes a simplified model to perform transient and linear stability analysis for a typical boiling water reactor (BWR). The simplified transient model was based in lumped and distributed parameters approximations, which includes vessel dome and the downcomer, recirculation loops, neutron process, fuel pin temperature distribution, lower and upper plenums reactor core and pressure and level controls. The stability was determined by studying the linearized versions of the equations representing the BWR system in the frequency domain. Numerical examples are used to illustrate the wide application of the simplified BWR model. We concluded that this simplified model describes properly the dynamic of a BWR and can be used for safety analysis or as a first approach in the design of an advanced BWR.

Hierarchical Fuzzy Logic Water-Level Control in Advanced Boiling Water Reactors

A hierarchical fuzzy logic controller (FLC) is applied to control the water level in an analytical simulation using a simplified advanced boiling water reactor model. To reduce the control effort of the feedwater pump, the linguistic variable, change in pressure, was adopted. Four linguistic variables were used for the FLC design, and the number of control rules became large if the conventional FLC design method was used. Using a hierarchical rule structure reduces the total number of control rules and thus the final decision tables. To reduce the design effort, two methods were separately developed for fine-tuning. One tunes the scaling factors using an optimization method, and the other tunes the control rules using a method similar to a fuzzy model reference control. The simulation results show that the performance of the hierarchical FLC is comparable to that of the proportional-integral controller, but use of the designed controller results in a shorter settling time.

Pulsational characteristics of two-cassette model of boiling-water reactor

On a large-scale two-cassette model of the natural-circulation loop of a reactor with vertical dimensions and reduced hydraulic-drag coefficients of the basic loop elements that are close to the full-scale values, an experimental investigation has been conducted, with the following conclusions: