Typical Pressurized Water Reactor Research Articles

On the use of neutron flux gradient with ANNs for the detection of diverted spent nuclear fuel

One of the main tasks in nuclear safeguards is regular inspections of Spent Nuclear Fuel (SNF) assemblies to detect possible diversions of special nuclear material such as 235U and 239Pu. In these inspections, characteristic signatures of SNF such as emissions of neutrons and gamma rays from the radioactive decay, are measured and their consistency with the declared assemblies is verified to ensure that no fuel pins have been removed. Research in this field is focused on both the development of detection equipment and methods for the analysis of the acquired measurement data. In this paper, the use of the neutron flux gradient, which is not considered in regular SNF verification, is investigated in combination with the scalar neutron flux as input to artificial neural network models for the quantification of fuel pins in SNF assemblies. The training and testing of these ANN models rely on a synthetic dataset that is generated from Monte Carlo simulations of a typical intact pressurized water reactor assembly and with different patterns of fuel pins replaced by dummy pins. The dataset consists of unique scenarios so that the ANN can be assessed over “unknown” cases that are not part of the learning phase. Results show that the neutron flux gradient is advantageous for a more accurate reconstruction of diversions within SNF assemblies.

Experimental investigation and prediction of CHF in wire-wrapped rod bundles

The wire-wrapped tight lattice fuel assembly is one of the options for small modular reactors. To clarify the characteristics of critical heat transfer for departure from nucleate boiling, experiments were conducted to investigate the critical heat flux in a wire-wrapped 19-rod bundle. The critical heat flux coincident with associated thermal–hydraulic parameters was obtained under typical pressurized water reactor conditions. Validation of data accuracy was performed to provide confidence in the experiment results. It was found that the critical heat flux in the wire-wrapped rod bundle is sensitive to the change in steam quality at some steam quality regions. Besides, the critical heat flux in wire-wrapped rod bundles has a similar reflection under the effects of local pressure, local mass flux, and steam quality. However, the current correlations tend to overestimate the critical heat flux for a wire-wrapped rod bundle. Hence, further development of KfK-3 correlations was proposed for better prediction of the critical heat flux in wire-wrapped bundles. This work is helpful for rod bundle designs of advanced pressurized water reactors.

Analytic Error Analysis of the Partial Derivatives Cross-Section Model—II: Numerical Results

Accurately predicting errors incurred in a cross-section model for two-step reactor analysis enables the development of optimal case matrices and more efficient cross-section models. In a companion paper, we developed a systematic methodology for the partial derivatives cross-section model through rigorous analytic error analysis. In this paper, we verify our methodology against the conventional “brute force” numerical approach using a typical pressurized water reactor (PWR) lattice. By successfully reproducing known results, we gain confidence in our methodology’s application to advanced reactor environments, where optimal case matrices are generally not known. Our error methodology relies on accurately estimating bounds on the derivatives of the cross-section functions, a task we achieve through an order of convergence study. We use these derivative bounds in derived error expressions to obtain pointwise and setwise cross-section error bounds and verify these results with reference solutions of various two-group cross sections. We then propagate the cross-section error bounds to reactivity error using first-order perturbation theory and analyze their combined effect. Application of this approach to our test problem corroborates our prior qualitative findings with quantitative evidence and reveals the relative magnitudes of interpolation and model form error sources across diverse PWR cross-section functionalizations. Our results suggest systematic pathways for improving case matrix construction to minimize the overall error. These findings also confirm what is well known to the light water reactor design community, which is that interpolation error of cross sections for standard interpolation procedures and case matrix structures is on the order of 10 pcm or less. Future work includes exploring different lattice types and functionalizations, extending reactivity bounds to multi-lattice problems, and investigating historical effects within the macroscopic depletion model.

Numerical investigation on boiling crisis in a full-length 5 × 5 fuel assembly under typical pressurized water reactor conditions

Critical heat flux (CHF) presents a research priority in the Pressurized Water Reactor (PWR) safety, as it can lead to the severe accidents and release radioactive materials. In this study, a wall heat flux partition model, proposed by Demarly [1], was employed within the two-fluid model by Computational Fluid Dynamics (CFD) methodology to investigate the characteristics of CHF under typical PWR conditions. A multi-scale interface model was coupled to consider the interfacial transfers in bulk flow during flow regime transition. The models were validated by using experimental data on subcooled flow boiling, boiling crisis in vertical tubes, and rod bundles. The PWR sub-channel and bundle test (PSBT) benchmark, comprising a full-length 5 × 5 fuel assembly with three different types of spacers, was simulated in this study. The CHF value was evaluated, demonstrating an acceptable accuracy compared to the experimental data, with a deviation of less than 10 % in the selected conditions. The CHF location in the cross section was successfully predicted by CFD approach, while the axial location of CHF was underestimated than experimental measurement. Besides, the impacts of mixing vanes with different deflection angles on boiling heat transfer characteristics were analyzed, revealing the crucial role of mixing vanes in the distribution of vapor and dry-patch area fraction in both the circumferential and flow directions.

Heat transfer optimization of uo2-mo fuel using genetic algorithms

Two genetic algorithm (GA) methods were applied to thermal finite element models to optimize the heat transfer efficacy of a UO2-Mo composite fuel pellet with typical pressurized water reactor fuel geometry. Mo additions to UO2 have been shown to increase the thermal conductivity, thus reducing centerline temperatures and temperature gradients. Previous studies evaluated uniformly dispersed Mo or continuous Mo internal geometries (e.g., fins, plates, discs) that were selected using engineering intuition. The current study uses two different implementations of the same GA to optimize Mo placement and minimize the fuel temperature with the only constraint being a maximum 10% Mo volume fraction. One approach superimposed Mo line elements onto the monolithic UO2 pellet model, and the other converted entire UO2 volume elements to Mo. The former method generated 1D heat transfer connections between nodes, whereas the latter method allowed for the formation of 3D structures. Features of the optimal fuel design produced by the GAs included dispersed Mo near the centerline that shifted the peak fuel temperature outward by 0.6 mm, Mo chains in the high-heat-flux region in the mid-to-outer radial zone, and a large continuous structure that spanned the full radius and height of the pellet and accounted for 87.7 % of the total Mo in the pellet. Analysis of this design indicates that the optimal Mo configuration is a balance between creating continuous heat transfer pathways and optimally dispersing Mo to minimize the heat transfer distance through UO2. This architecture ultimately produced an effective thermal conductivity of 11.3 W/m·K under the assumed boundary conditions. This result is higher than any previous values from the literature. Potential fabrication methods and challenges are discussed in addition to the implications on fuel performance.

Secondary system modeling and primary system coupled simulation using MARS-KS

The flexibility of nuclear energy can be achieved by the load following operation and the thermal energy utilization for hydrogen production, desalination, district heating, and Thermal Energy Storage (TES). Thermal energy utilization is performed by transferring the remaining thermal energy over the energy required for electric power generation without changing the reactor power level significantly. For the Pressurized Water Reactor (PWR), it becomes possible by extracting steam from the secondary system and circulating it to a thermal energy application such as the TES system. However, the steam extraction operation affects the behavior of all thermal–hydraulic (TH) variables in the secondary system and further influences the primary system in terms of coolant temperature, reactivity, and reactor power. For thermal energy utilization, it is necessary to secure a technology that can examine the overall stability of the primary and secondary systems in a Nuclear Power Plant (NPP). In this study, based on the system analysis code MARS-KS, an NPP analysis model for SMART, a small-sized integral type PWR, was developed that can simulate major TH variables behavior in the primary and secondary systems at once. Its strength is that major components in the secondary system are modeled without any boundary conditions under matching the heat and mass balance. From the verification calculation of the steady state, it was confirmed that this SMART analysis model can predict the main TH variables of the primary and secondary systems similarly to the plant data. Furthermore, an example calculation was performed for the TES application. The analysis results show that the analysis model is sufficiently applicable to the transient calculation of the primary and secondary systems during the steam extraction operation. This analysis model is expected to be used for the development of technologies such as load following operation and thermal energy utilization in the future.

The UO2 Power-to-Melt Experiment Performed in the High Burnup Chemistry International Program

In this work, a detailed reevaluation of a past power-to-melt experiment performed within the so-called High Burnup Chemistry project is provided. A pressurized water reactor–type UO2 fuel rod was base irradiated in Belgian Reactor 3 up to a peak pellet burnup of 60 MWd/kgU. After base irradiation, the rod experienced a power ramp experiment in Belgian Reactor 2, reaching a ramp terminal level of 70 kW/m (later adjusted to 66 kW/m). Extensive post-irradiation examination was performed after both the base irradiation and the power ramp experiment. After the power ramp experiment, rod cladding failure and local fuel melting were observed. Fuel melting was observed in an 85-mm region around the peak power pellet with a normalized molten fuel radius in the range r/r0 = 0.20 to 0.27. The threshold power for melting derived from this experiment was 63.0 ± 4.4 kW/m.

Investigation of Monte Carlo trained CNNs for neutronics predictions of typical and atypical PWR assemblies

The use of Machine Learning (ML) has gained significant attention in recent years for use in the development of surrogate models capable of predicting various neutronics parameters in Pressurized Water Reactors (PWRs). These approaches aim to provide fast and accurate approximations of conventional model outputs which are typically both computationally expensive and time-consuming to run. A novel supervised learning framework LatticeNet, employing Artificial Neural Networks (ANNs) and computer vision techniques, has been shown to be particularly useful in the prediction of assembly and pin-level parameters such as multiplication factor or pin powers. This framework was validated using deterministically-generated training data for a standard fuel assembly, representing best-case input conditions. This paper investigates the performance of LatticeNet as well as the tools developed alongside when given Monte Carlo-generated inputs and assemblies of varying pin dimensions, assessing the network’s tolerance to training data uncertainty and atypical configurations.

Extension of GeN-Foam to departure from nucleate boiling prediction and validation against the OECD/NRC PSBT benchmark

The prediction of departure from nucleate boiling (DNB) has always been a crucial aspect of thermal-hydraulic codes for the analysis of Light Water Reactors. In this paper, GeN-Foam, a multi-physics code developed based on OpenFOAM, has been enhanced to incorporate DNB prediction using a CHF look-up table as well as post-CHF flow and heat transfer models. To assess GeN-Foam's accuracy in modeling DNB conditions in typical pressurized water reactors (PWRs), a preliminary validation was conducted utilizing Phase II of the PSBT benchmark, including the steady-state fluid temperature (Test Series 1), steady-state DNB (Test Series 4), and transient DNB (Test Series 11T) benchmarks. This paper presents the closure correlations implemented in GeN-Foam, provides a description of the PSBT benchmarks, and includes a comparison between GeN-Foam's predictions and experimental data, as well as code-to-code verification with other participants. The results demonstrate that GeN-Foam exhibits good performance in simulating two-phase flow boiling conditions. Furthermore, GeN-Foam accurately predicts the DNB power and time of occurrence within a ±10 % error range compared to measured values, preliminarily indicating its effectiveness in predicting DNB occurrence and two-phase flow boiling phenomena.

Case studies on radioactivity and decay heat contribution from coating materials of irradiated accident tolerant fuel for a typical PHWR

Seven coating materials such as Al2O3, NbC, Si, SiC, TiN, Y2O3, and ZrC have been considered as a possible coating material towards development of accident tolerant fuel for a typical pressurized heavy water reactor. For an effective severe accident management strategy in addition to spent fuel handling, storage and transport, it is required to know the contribution to the radioactivity burden and decay heat load from the irradiated coating materials of accident tolerant fuel. Under irradiation of coating material in PHWR flux condition, the decay chain of each activated radionuclide has been simulated using ISOGEN code using one group homogenized point cross section. In this paper, radioactivity and decay heat contributions from different irradiated coating materials have been quantified and compared. The minimum contribution to radioactivity and decay heat is observed in SiC after irradiation of 445 days of normal operation. Out of all the coating materials considered in the study, most radioactivity and decay heat were added due to irradiation of coating materials Y2O3. From reactivity load, source term, and decay heat perspectives, silicon-based coating materials are found to be the most suitable.

A Method for Backward Failure Propagation in Conceptual System Design

The increased complexity of modern system designs and demands for quicker time to market have made safety-related verification and validation of such systems more challenging. Incorporating safety and risk considerations at the early stages of design is one way to acquire a more robust initial design for novel systems. Inductive fault analysis has its significance at final stages of design, e.g., verification and validation. However, to preclude certain system failure states—especially for the systems with high failure consequences, a designer would innately prefer to trace back and remedy the causes of failure, as compared to a more cumbersome activity of identifying the faults individually and sifting the combinations that lead to the failure of interest. The work presented in this paper is aimed at the development of a backward failure propagation methodology for analyzing the origins of functional failures in a conceptual design of systems including but not limited to nuclear, mechanical, aerospace, process, electrical/electronics, telecommunication, automotive, etc. This method allows the designer to achieve a robust early design based on the analyses of the system’s functional dependencies before proceeding to the detailed design and testing stages. The insights provided by the analysis at the conceptual design stage also reduce redesign efforts, testing costs, and project delays. The proposed method is a functional analysis approach that extends the Integrated System Failure Analysis for backward failure propagation. When provided with an abstract system configuration, a system’s functional model, and a system’s behavioral model, it utilizes a known functional state (typically a failure) to acquire system component modes and the states of other functions. The method includes inversion of the functional failure logic and component behavioral rules using propositional logic and deductive analysis to assess valid states of a system that satisfy the given initial conditions. To test the method’s scalability, we applied the proposed method to a simplified representation of the secondary loop of a typical pressurized water reactor.

Neutronic Characterization for a Pressurized Water Reactor Spent Fuel Assembly

The transfer of nuclear spent fuel from the reactor storage pool to dry storage or for reprocessing or final disposition requires information about its isotopic composition, decay heat, and other thermomechanical properties. The spent nuclear fuel assembly of a typical advanced pressurized water reactor, AP-1000, was characterized using the Monte Carlo MCNPX code and SCALE/ORIGEN code. The simulation of operational history started from the operation of the first fresh core for an average fuel assembly with certain physical isotopic parameters until 25 GWd/tonne U discharge burnup. The analysis considered the calculations of the radionuclide inventories, activity, neutron emission spectrum, gamma-ray emission spectrum, and decay power after 700 effective full power days and for post different time ranges until a 1 million–year cooling period. The comparison of some results of the two codes showed small differences due to the consideration of the continuous-energy variation for neutrons in the MCNPX code and the discrete energy assumption in the SCALE/ORIGEN code.

Automated analysis of Baffle Bolts

The Baffle bolts (BB) are components of the lower internals of the vessel of Pressurized Water Reactor (PWR) nuclear power plants. They are subjected to ultrasonic testing (UT) inspection as part of the Long-Term Operation (LTO) of the PWR plants worldwide. Unlike other areas undergo inspection, usually there are more than one thousand bolts in a typical PWR reactor. The goal of the paper is to present how the Artificial Intelligence (AI) can be integrated into the inspection of the baffle bolts described in the introduction of the present document. The scope of the project was limited to the analysis of the signals acquired during the inspection to discriminate between healthy BB and those showing signals that need to be evaluated by an expert. Some different independent algorithms are used by the automated analysis system, which counts with a support decision system to achieve the most robust result possible. First inspection of its kind was carried out in winter 2021 with promising results, being scheduled the next one in Fall 2022. The expectation is to get the system qualified according to the criteria stablished by the normative. AI can be applied to UT inspections being the major limitation the amount of data, in a dual sense: train the data needed for the algorithms and obtain a confident improvement of the productivity. A key point of the project has been to create working teams of professionals that bring together knowledge in UT and AI.

Descriptor sliding mode observer based fault tolerant control for nuclear power plant with actuator and sensor faults

In sophisticated and complex system such as nuclear power plant, fault estimation and fault tolerant control always play an important role in maintaining the system stability and assuring satisfactory and safe operation. Thus, in this work a fault estimation and fault tolerant control scheme based on sliding mode theory is proposed for a pressurized water reactor type nuclear power plant considering simultaneous actuator and sensor faults. First, using descriptor sliding mode observer approach, an accurate estimation of the system states and sensor fault vector have been obtained simultaneously. Then, based on the estimated information, an integral type sliding mode control scheme is proposed to stabilize the resulting faulty system. With the help of Lyapunov stability theory, reachabilities of the proposed sliding mode surfaces are shown in both the state estimation space and the error estimation space, simultaneously. Finally, the efficacy of the proposed control scheme is shown by applying it to a nuclear power plant.

Investigations on the Pu-to-244Cm ratio method for Pu accountancy in pyroprocessing

Non-uniformity of Pu and Cm composition in used nuclear fuel was analyzed to determine its effect on Pu accountancy in pyroprocessing, while employing the Pu-to-244Cm ratio method. Burnup simulation of a typical pressurized water reactor fuel assembly, required for the analysis, was carried out using MCNP code. Used fuel nuclide composition, as a function of nine axial and two radial meshes, were evaluated. The axial variation of neutron flux and self-shielding effects were found to affect the uniformity of Pu and Cm compositions and in turn the Pu-to-244Cm ratio. However, the results of the study showed that these non-uniformities do not affect the use of Pu-to-244Cm ratio method for Pu accountancy, if the measurement samples are drawn from the voloxidized powder at the feed step of pyroprocessing. ‘Material Unaccounted For’ and its uncertainty estimates are also presented for a pyrprocessing facility to verify safeguards monitoring requirements of the IAEA.

Numerical analysis on subcooled boiling in PWR coolant channel based on a modified multi-scale interface model

A modified multi-scale interface model was employed with the Eulerian two-fluid framework to investigate the three-dimensional characteristics of subcooled boiling characteristics in a typical Pressurized Water Reactor (PWR) coolant channel with mixing grid. Based on the morphology identification by adopting an advanced interface topology map, the phase-average method and the interface-reconstruction method can be applied for dispersed bubble and sharp interface, respectively, to improve the calculated precision of interfacial transfers. Models were validated by using the dam break data for sharp interface topology and employing the flow boiling experimental data for the phase distribution in both radial and axial directions. The calculated results agreed well with the experimental data. Thermohydraulic characteristics in the coolant channel were obtained, including void fraction, phase velocity and flow streamline, based on which, the effects of mixing vane on the localized field were analyzed. The vapor volume fraction was decreased in downstream of spacer grid due to the mixing effect, while the lateral flow was enhanced. The vapor accumulation phenomenon was captured and the sharp interface between the liquid and the accumulated vapor was identified by the modified model. Based on this, the interfacial transfer characteristics of the sharp interface was considered in simulations.

Determination of neutron flux redistribution factors for a typical pressurized water reactor ex-core measurements using Monte Carlo technique

In a typical pressurized water reactor, neutron detectors located outside the reactor core monitor reactor power. In addition, they are also used to measure the reactivity of the control rods. A novel approach to calculate the ex-core neutron detector response in a typical pressurized water reactor using the Monte Carlo technique is presented. A detailed ex-core model of the Krško nuclear power plant was developed using the Monte Carlo neutron transport code MCNP. Due to the location of the ex-core neutron detectors, the hybrid code ADVANTG is used to generate variance reduction parameters to accelerte the convergence of the results outside the reactor core. To use ADVANTG, the fixed neutron source had to be reconstructed from the criticality core calculation. This paper presents the sensitivity analysis of the response of the ex-core detectors to the neutron data libraries used, the description of the fixed neutron source and the ADVANTG parameters. It was found that a pin-wise description of the neutron source for at least two rows of fuel assemblies at the core periphery is necessary for accurate results. Our results show the importance of a correct description of the prompt neutron spectra in the high energy region and the impact this has on the response of the ex-core detectors. The method in which the prompt neutron fission spectra for important fission nuclides are weighted by the calculated reaction rates has been shown to be the best approximation, with deviations from the reference calculation within statistical uncertainty. The effect of nuclear data libraries on the response of the ex-core detector was investigated, and the difference between the ENDF/B-VII.0 and the ENDF/B-VIII.0 nuclear data libraries was ∼11%. When the deficient evaluation of the 56Fe isotope included in the ENDF/B-VIII.0 nuclear data library was replaced by the improved evaluation from the IAEA INDEN project, the differences decreased to ∼3.7%. In addition, neutron flux redistributions due to control rod movement were investigated and flux redistribution factors were updated using Monte Carlo particle transport methods. The reaction rate redistribution factors obtained with methods presented in this paper are within 1% agreement with the currently used factors.

Establishment of DeCART/MIG stochastic sampling code system and Application to UAM and BEAVRS benchmarks

In this study, a DeCART/MIG uncertainty quantification (UQ) analysis code system with a multi-correlated cross section stochastic sampling (S.S.) module was established and verified through the UAM (Uncertainty Analysis in Modeling) and the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) benchmark calculations. For the S.S. calculations, a sample of 500 DeCART multi-group cross section sets for two major actinides, i.e., 235U and 238U, were generated by the MIG code and covariance data from the ENDF/B-VII.1 evaluated nuclear data library. In the three pin problems (i.e. TMI-1, PB2, and Koz-6) from the UAM benchmark, the uncertainties in kinf by the DeCART/MIG S.S. calculations agreed very well with the sensitivity and uncertainty (S/U) perturbation results by DeCART/MUSAD and the S/U direct subtraction (S/U-DS) results by the DeCART/MIG. From these results, it was concluded that the multi-group cross section sampling module of the MIG code works correctly and accurately. In the BEAVRS whole benchmark problems, the uncertainties in the control rod bank worth, isothermal temperature coefficient, power distribution, and critical boron concentration due to cross section uncertainties were calculated by the DeCART/MIG code system. Overall, the uncertainties in these design parameters were less than the general design review criteria of a typical pressurized water reactor start-up case. This newly-developed DeCART/MIG UQ analysis code system by the S.S. method can be widely utilized as uncertainty analysis and margin estimation tools for developing and designing new advanced nuclear reactors.

A study on the feasibility of using Uranium Nitride (UN) fuel in Pressurized water reactors (PWR)

MCNPX computer code is used to design a three-dimensional model for a typical Pressurized Water reactor (PWR) core. Uranium Nitride fuel (UN) was tested for the reactor and the results were compared with a typical UO2 fuel. Neutron spectrum, power distributions, plutonium isotopes productions, and kinetics and safety parameters were evaluated. It was found that thermal neutron spectrum is harder in UN than in UO2. UN can achieve a longer fuel residence time in the reactor than UO2. Kinetic and safety parameters are within the acceptable range similar to UO2. Control rod worth is lower in UN due to thermal flux hardening. This research was carried out with the addition of three types of variations of burnable poison.

PCTRAN Westinghouse AP1000 Power Control of Pressurized Water Reactor Using Simulink of MATLAB

This paper introduces the simulation, and controls using Simulink of MATLAB for PCTRAN (Personal Computer Transient Analysis) of the power control system (PWR) type pressurized water reactor of PWR WESTINGHOUSE AP1000. The power controller model produces mathematical model description in nonlinear relation form in Simulink of MATLAB which is an important and popular program used at most universities for education. The power controller is described by a block diagram in this paper and some details introduce to clearly understand the work function. The results of action control compared with the PCTRAN programme in modes of automatic and manual control.