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Types of Potential Accidents and Reactor Response Codes and Tools Experimental Validation Safety Analysis Approach Licensing Modernization Project Use of PRA in LMP, ASME/ANS, Non-LWR PRA Standard Methods for Incorporating Passive System Reliability into a PRA
Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.
This report describes the successful assembly of a High Flux Isotope Reactor (HFIR) irradiation experiment designed to assess radiation-induced lateral bowing of silicon carbide fiber–reinforced, silicon carbide matrix composite (SiC/SiC) components under a radial fast neutron flux gradient. Excessive bowing of a SiC/SiC channel box in a boiling water reactor could potentially interfere with control blade movements. Similar concerns exist for SiC/SiC fuel cladding in light water reactors. The experiment described herein will provide experimental validation of the structural response of a miniature SiC/SiC channel box and tube specimens with pressurized water reactor diameters during irradiation. The significant radial fast neutron flux gradients that exist in the permanent reflector of HFIR were characterized using detailed three-dimensional neutronic calculations. The three-dimensional displacement damage dose rate profile and the resulting volumetric swelling in SiC were used as inputs to structural analyses that predicted the deformation and stresses in the channel box specimen. The specimens were thoroughly characterized prior to irradiation using traditional dimensional inspection and surface profilometry so that these measurements can later be compared with similar measurements that will be made post-irradiation to determine radiation-induced deformations. Furthermore, fine engraving markers were inscribed along all outer surfaces of the specimen and mapped using a digital microscope and a three-dimensional stage. This technique allowed for accurate measurements of the marker spacings, which can be compared with similar measurements that will be made post-irradiation to provide local radiation-induced strain mapping. The experiment was successfully assembled and is scheduled for insertion during HFIR cycle 492, which is currently scheduled to run from May 25, 2021 to June 18, 2021.
The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.
The Integral Inherently Safe Light Water Reactor (I 2 S-LWR) includes primary-to-secondary coolant heat exchangers located in the downcomer of the reactor pressure vessel. A microchannel heat exchanger (MCHX) configuration is selected to meet the limited available volume and high heat duty requirements. The design, modeling, and optimization of the liquid-liquid MCHX is outlined. In addition, the performance of a MCHX test section representative of the I 2 S-LWR MCHX design is validated experimentally. Experimental results show that heat transfer and pressure drop correlations developed for larger, macroscale channels lead to accurate predictions of performance. Additionally, this study shows that an MCHX can deliver the required heat duties within the available space and pressure drop constraints of the overall I2 S-LWR design.
We have studied the chemical transformations of semi-volatile organic iodide species (RI) in the condensed phase as well as adsorbed onto the surfaces of environmentally relevant particles, e.g., soot (carbon) and dust (silica) under real-world conditions. The combination of chosen experimental methods provide a molecular-level insight into the chemical dynamics of organic iodides. Throughout this project, we have developed new experimental, quantum chemistry, and data analysis capabilities. All experimental work was performed with 127 I.
High-fidelity modeling and simulation were performed for the MIT graphite exponential pile (MGEP) using Monte Carlo neutron transport codes OpenMC and MCNP, and the results were validated by experimental data. The MGEP is being used as the test bed for the design of an autonomous control system for the pile's neutron flux distribution. The main contribution of this work is to generate the training data sets of neutron flux distributions with different locations of control rods that perturb the neutron flux profiles. First, code -to-code cross verification between OpenMC and MCNP was performed to ensure consistency of the numerical modeling within statistical uncertainties. To validate the accuracy of this high-fidelity model, a series of neutron flux measurements were conducted using a Helium-3 (He-3) neutron detector on a mobile platform that is placed inside the pile. Second, the neutron flux profiles were measured in four vertical layers of interest, and compared to the corresponding simulation results. The comparison results shows that the root mean square error is less than 2.5% in the two upper layers, and less than 4.5% in all four measured layers. Here the results validated the accuracy of the modeling and simulation. Finally, the relative change of the neutron flux profiles from moving control rods was analyzed, which identified the layer that has the best sensitivity regarding the control rods movements. Thus, this work identified and provided training data sets of both simulated and experimental neutron flux profiles in the most sensitive layer, paving the path forward to the real-time experimental demonstration of the autonomous control system.
Sodium fast reactors (SFR) are poised to be a leading candidate for the next generation of commercial nuclear reactor deployment. Companies are commissioning designs for SFR increasing the need for experimental and computational analysis to improve the economics and safety of these reactors. Analysis of SFR behavior during reactor transients directly informs the understanding of reactor safety. Particularly, investigating the thermal transients associated with the reactor loss of flow transient allows for informed design decisions to be made regarding reactor safety. During loss of flow transients the flow rate of the coolant is significantly reduced, but not necessarily stopped. The reduction in flow rate results in coolant temperatures exiting the reactor core that can be drastically different than the coolant in upper pool. When these different temperature fluids interact, thermally stratified layers can form causing cyclic thermal fatigue on the reactor vessel potentially leading to pre-material failure. Past experimental studies have lacked high resolution temperature measurements. This research focuses on demonstrating the reliability of novel techniques for acquiring high resolution temperature measurements in a scaled liquid sodium facility. Tests are conducted that simulate postulated loss of flow transients and provide unprecedented spatial temperature distribution measurements.
Simulations were conducted using the BISON fuel performance code on an automated process to read initial and operating conditions from two databases—the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor Materials Information System (IMIS) database. These databases contain metallic fuel data from the Experimental Breeder Reactor-II (EBR-II) and the Fast Flux Test Facility (FFTF). The work demonstrates use of an integrated framework to access EBR-II fuel pin data for evaluating fuel performance models contained within BISON to predict fuel performance of next-generation metallic fuel systems. Between IMIS and FIPD, there is enough information to conduct 1,977 unique EBR-II metallic fuel pin histories from 29 different experiments, and 338 pins from FFTF MFF-3 and MFF-5 with varying levels of details between the two databases. Each of these fuel performance histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures, and new model developments in BISON since the initial demonstration of this integrated framework. Fission gas release (FGR), cumulative damage fraction, fuel axial swelling, FCCI wastage thickness, cladding profilometry, and burnup were all simulated in BISON and compared to post-irradiation examination (PIE) results to evaluate BISON fuel performance modeling. Implementation of new fuel performance models into a generic BISON input file coupled with IMIS and FIPD yielded results with a better representation of physics than the initial evaluation of the integrated framework. Cladding profilometry, FGR, and fuel axial swelling were found to be in good agreement with PIE measurements for most of the pins simulated. The chosen mechanical contact solver was found to significantly impact the axial fuel swelling and cladding strain predictions when used in conjunction with the U-Pu-Zr hot-pressing model since it bound the fuel to prevent further swelling and increased hydrostatic stresses. This work suggests that fuel performance modeling in BISON under steady-state conditions represents the PIE data well and should be reassessed when new PIE data become available in IMIS and FIPD databases and when improved physical models to better capture fuel performance are added to BISON.
This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.
A detailed biomass pyrolysis kinetics scheme is implemented in reduced-order reactor models to predict chemical species yields from a fluidized bed reactor. The biomass composition in terms of cellulose, hemicellulose, lignins, and extractives are determined for several biomass feedstocks. Model results are compared to yields measured from a two-inch diameter bench-scale fluidized bed reactor operating at fast pyrolysis conditions. The reduced-order chemical reactor models compare favorably with the experimental measurements and capture trends in product yields due to biomass compositional effects such as high ash content. This work offers a computationally inexpensive approach to predict the quality of biomass pyrolysis products in a timely manner. Source code for the reactor models along with a biomass composition web tool are made available online for future scientific research efforts.
Here, this paper presents a modified ADM1 (mADM1) model for use in assessing the influence of active dissolved H 2 extraction on biogas production from anaerobic fermentation reactors, specifically in the context of high-strength brewery wastewater as the feed. The modified model adds regulation factors to account for the varying product stoichiometry of glucose degradation reactions as a function of H 2 concentration in anaerobic digestion, and incorporates the use of both lactate and ethanol as intermediates. The changes to the model are expected to better predict the effects of H 2 removal on the production of H 2 in fermentation processes. Both ADM1 and mADM1 were calibrated against experimental data from a fluidized-bed reactor containing encapsulated acidogenic-acetogenic microbial communities treating real brewery wastewater. The calibrated models were validated against another fluidized-bed reactor identical to the calibration reactor, with the addition of a hollow-fiber membrane module that was used to reduce dissolved H 2 concentrations in the validation reactor. It was found that ADM1 over-estimated the H 2 production rates of the validation reactor (117 mL/day simulated vs. 16.48 mL/day experimental), whereas mADM1 was able to successfully predict fermentation, and specifically the H 2 production rate (17 mL/day). The presented model is a first step towards a model that can predict the effects of dissolved H 2 removal on fermentation processes.
Emissions data were evaluated for a set of test hardware that adapts Collins Aerospace’s aeroengine liquid fueled injector technology to a ground-based turbine. The hardware was specifically developed to operate on 100% hydrogen; however it has the ability to operate on both pure methane and hydrogen and mixtures in between. 16 injector configurations and seven factors (air split, fuel and air swirl, pressure drop, preheat temperature, fuel composition, and flame temperature) were investigated based on a Box Behnken statistical model. Of the 16, configuration 3 was selected for further discussion being in the middle of the statistical design space. A chemical reactor network was developed based on the experimental data obtained and was assessed with three different mechanisms: GRI Mech 3.0, UCSD, and Galway. All factors were held constant except the fuel composition to directly compare chemical pathways for methane and hydrogen. This study was conducted across different flame temperatures of 1500K, 1675K, and 1850K for both hydrogen and methane. Additional lower flame temperatures of 1100K and 1300K were evaluated for hydrogen. Moreover, results for fully premixed and non-premixed results were compared to obtain information on the implications of mixedness on emissions. These results were compared with the Leonard and Stegmaier plot for methane and a similar plot was constructed for hydrogen.
Nuclear accident progression analysis codes for reactor licensing must be validated using experimental data that was generated at a large enough scale so that the results are representative of full-scale accidents. This report describes a conceptual design of engineering-scale molten salt spill tests that will provide the necessary datasets to support molten salt reactor (MSR) licensing. Design considerations, salt compositions, test variables, processes to be quantified, and suitable measurement techniques are presented and discussed. Aspects of the conceptual engineering-scale molten salt spill test design presented in this report were made using insights from recent laboratory-scale molten salt spill tests conducted at Argonne. Additional input from model developers, MSR vendors, and technical experts will benefit the design of the proposed engineering-scale molten salt spill tests.
Extraction of mission consumable resources such as water and oxygen from the planetary environment provides valuable reduction in launch-mass and potentially extends the mission duration. Processing of lunar regolith for resource extraction necessarily involves heating and chemical reaction of solid material with processing gases. Vibrofluidization is known to produce effective mixing and control of flow within granular media. In this study we present experimental results for vibrofluidized heat transfer in lunar regolith simulants (JSC-1 and JSC-1A) heated up to 900 C. The results show that the simulant bed height has a significant influence on the vibration induced flow field and heat transfer rates. A taller bed height leads to a two-cell circulation pattern whereas a single-cell circulation was observed for a shorter height. Lessons learned from these test results should provide insight into efficient design of future robotic missions involving In-Situ Resource Utilization.
Systems-level nuclear accident analysis codes for reactor licensing must be validated using experimental data that represent behaviors expected during actual full-scale accidents. Some behaviors may arise from coupled processes and only manifest at large scales. This report presents the preliminary design of the Salt Accident Analysis Facility (SAAF, pronounced “safe”), which is an experimental test facility to be constructed at Argonne that can be used to conduct integrated salt accident tests at an engineering scale. The measurement capabilities of the SAAF are based on previously developed methods and will provide the representative datasets that are needed to support molten salt reactor (MSR) licensing. Details of the design, the processes to be quantified, the measurement techniques for quantifying the processes, the variables that can be adjusted to simulate different accident scenarios, and operational considerations are presented herein. This report provides stakeholders the opportunity to give feedback on the test facility capabilities and planned analyses before it is constructed.
With the rise of interest in thermal neutron scattering data for advanced reactor, criticality safety, and shielding applications, new experimental data are required for evaluation of new materials or for re-evaluation (or validations) of previously evaluated materials. New experimental data are evaluated in a three-step process: (1) computing the phonon characteristics, (2) computing the dynamic structure factor (DSF) from the data, and (3) using the experimental setup to simulate the experimental data. All three steps have challenges, ranging from the need for a sufficiently general material simulation code—a processing code that can compute the corresponding DSF—to having a detailed layout of the instrument/beamline/facility where the data were measured. Whereas phonon characteristics of materials can be computed using various methods (molecular dynamics, density functional theory, etc.), a high-fidelity computation of the DSF and the simulation of the experiment based on the DSF is vital to the accuracy of the evaluation. The latter two steps can be achieved by using the two corresponding code systems developed by instrument scientists at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory: (1) OCLIMAX, a program that calculates the dynamic structure factor from DFT and MD simulation results, and (2) MCViNE, a Monte Carlo neutron ray-tracing program designed to simulate neutron scattering experiments. Recently, polyethylene and yttrium hydride were measured at the Wide Angular-Range Chopper (ARCS) and SEQUOIA instrument stations of the SNS. These experiments are simulated using the density functional theory code, the Cambridge Serial Total Energy Package (CASTEP), to compute its phonon characteristics (eigenvalues/vectors and PDOS), which is then processed using OCLIMAX to yield the DSF, and finally the data at each instrument station are simulated by the MCViNE for comparison to the measured data for evaluation. For comparison to conventional evaluation methods, the scattering data processed from OCLIMAX are compared against those processed from the LEAPR module of NJOY, and the results from MCViNE simulations are compared against previously used simplified beamline models implemented in the Monte Carlo N-Particle (MCNP) code.
In this work, a continuum heat and mass transfer model coupling transport phenomena and high-temperature thermochemical reactions is developed for stationary packed-bed and counter-flow moving-bed reactors. After presenting the general modeling framework, we focus on the 2D axisymmetric version of the model for which validation is conducted with experimental results for a packed-bed reactor in the literature for manganese-iron oxide reduction/oxidation and an in-house counter-flow moving-bed reactor for magnesium-manganese oxide reduction up to 1450 °C. Transient simulation results including the local distributions of gas/solid temperatures, oxygen concentration and the extent of reaction, as well as the various energy flow components and energy conversion efficiencies are reported. The results based on the 2D axisymmetric model are also compared with those obtained from a previous 1D model. The comparison shows that capturing the radial variation is critical in reactor modeling and the 2D results demonstrate improved agreement with experiments. Specifically, large temperature variations along the radial direction are observed especially in the reaction zone; this non-uniform radial temperature distribution has a significant effect on the chemical reaction extent due to its strong dependence on temperature; and the overall oxygen concentration at the reactor exit and the predicted system efficiency are slightly lower in the 2D model compared to the 1D model. Finally, the present heat and mass transfer model can provide valuable insights into reactor design, scale-up, and operating conditions selection to maximize system energy storage efficiency.