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At least 1,405 records · Page 78

Fuel Fabrication Specification Impact Analysis for NBSR LEU Conversion

As part of a national initiative to enhance nuclear security and reduce proliferation risks, significant efforts have been undertaken by the National Nuclear Security Administration Material Management and Minimization Office of Reactor Conversion Program to convert U.S. high performance research reactors (USHPRRs) from the use of highly enriched uranium (HEU) to low-enriched uranium (LEU), including the National Bureau of Standards Reactor (NBSR). The current plan is to procure LEU fuel assemblies from commercial fabricators according to fuel specifications tailored for each USHPRR. The analysis conducted at Brookhaven National Laboratory was part of an effort to identify the sources of uncertainty in the fuel specifications that may impact the performance of the NBSR core after its conversion and, in particular, to assess the range of acceptable tolerance limits from the perspective of core safety and reactor performance. Using the stochastic neutronics code MCNP 6.2, the variations in important NBSR neutronics characteristics were analyzed as a function of the specification parameters independently and in combination. The important NBSR specification parameters analyzed were the fuel isotopic composition, the amount of impurity content in cladding, the fuel plate thickness, and the fuel element 235U mass loading. The range of variation of each specification parameter was based on the technical specification limit or available as-fabricated assay data and uncertainties. The NBSR neutronics characteristics selected for analysis were the reactor reactivity characteristics at equilibrium and the equilibrium fuel cycle length. Results show that with variations in the fabrication parameters of the as-fabricated U-10Mo fuel within the specification limitations, the excess reactivity of the NBSR LEU core remains well below the 15% Δk/k technical specification limit, and the shutdown margin is always significantly greater than the required 0.68% Δk/k. This ensures that the NBSR can be operated safely and reliably shut down for all analyzed cases within the specified fabrication limits after the LEU conversion. In the prototypic case, the fuel cycle length was 1.5 days longer than the targeted 38.5 days. In a credible worst-case scenario, where all low-reactivity parameters were combined, the fuel cycle length was reduced to 35.5 days, which is still considered manageable for reactor operations. Variations in cycle length are primarily driven by changes in 235U loading, with other parameters having secondary effects.

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Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments

This paper presents the first application of model calibration to neutron multiplicity counting (NMC) experiments for cross-section optimization that is informed by adjoint-based sensitivity analysis (SA) and first-order uncertainty quantification (UQ). We summarize previous work on SA applied to NMC and describe notable modifications and additions. We give the procedure for first-order UQ and Bayesian-inference-based parameter estimation (PE). We then discuss model calibration applied to NMC of a 4.5-kg sphere of weapons-grade, alpha-phase plutonium metal (the BeRP ball) with the nPod neutron multiplicity counter. For the BeRP ball in bare and polyethylene-reflected configurations, we discuss the sensitivity of the first- and second-moment detector responses (i.e., first and second moments of the NMC distribution, respectively) to the cross sections. We describe the sources of uncertainty in the measured and simulated responses. Specifically, uncertainty in the measured responses is due to both random and systematic sources. Uncertainty in the simulated responses is due to the cross-section covariances. We describe in detail the adjustment to the cross sections and cross-section covariances due to the optimization. Due to the contribution of systematic uncertainties to the measured response uncertainties, the adjustment to the cross sections is similar in trend but larger in magnitude compared to that recommended by previous work. We compare the measured responses to responses simulated with nominal and optimized cross sections, demonstrating that the best-estimate cross sections produce simulations of NMC experiments that are more accurate with reduced uncertainty.

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Threadsafe Dynamic Neighbor Lists for Monte Carlo Ray Tracing

Monte Carlo (MC) transport codes offer high-fidelity modeling of particle transport physics, but their high computational cost makes them impractical for many applications. For some applications such as multiphysics and depletion that use finely discretized geometries, a large portion of this computational cost is attributable to ray tracing. Neighbor lists are a well-known method for accelerating ray-tracing calculations in a MC code, but despite their prevalence, little work has been published on the details of their implementation. The fine details can have a significant impact on performance, particularly when using shared-memory parallelism. This paper addresses these details of implementation with a discussion of different neighbor list schemes and their impact on software runtime. Performance tests were run by using OpenMC on a pin-cell problem discretized with up to 200 axial regions. The results demonstrate that switching from surface-based to cell-based neighbor lists leads to a 10 faster calculation rate for the most fine discretization. Finally, using a threadsafe shared-memory data structure results in a 20% faster calculation rate versus simple threadprivate neighbor lists. Results here show that a data structure that is contiguous in memory improves performance by only 1% to 2% over noncontiguous linked lists.

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Annular Flow Simulation Supported by Iterative In-Memory Mesh Adaptation

Various flow regimes exist in a boiling water reactor (BWR) as the steam quality increases in the uprising coolant flow, from bubbly flow, slug/churn flow, to annular flow. The annular flow is characterized by the presence of a fast-moving gas core and the surrounding liquid film flowing on the conduit wall. Additionally, entrained droplets can be observed in the gas core with ingested bubbles in the liquid film. The dynamics occurring on the wavy interface between the liquid film and gas core plays a crucial role in affecting the heat transfer rate and pressure drop within the BWR core. However, a fundamental understanding of annular flow is still lacking, partly due to the difficulty in obtaining detailed local data in annular flow experiments. In the current study, a novel simulation framework is developed for the annular flow by coupling a computational fluid dynamics flow solver with state-of-the-art meshing software. The gas-liquid interface is tracked with the level set method. Based on the computed flow solutions, the computational mesh is dynamically adapted in memory to meet the local mesh resolution requirement. This iterative simulation-adaptation framework can ensure the fine mesh resolution across the interface, which not only helps mitigate the mass conservation degradation known to level set methods but also improves the representation of dramatic interface topological changes such as wave breaking and droplet entrainment. The present investigation will shed light onto the complex interfacial processes involved in annular flow and generate much needed simulation data for annular flow modeling.

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Methodology for Generating Covariance Data of Thermal Neutron Scattering Cross Sections

This paper details and implements a framework for evaluating thermal neutron scattering cross sections that provide S(α,β) data and covariance data for hydrogen in light water. This methodology involves perturbing model parameters of molecular dynamics potentials and fitting the simulation results to experimental data. The framework is general and can be applied to any material or simulation method. The fit is made using the Unified Monte Carlo method to experimentally measure double-differential scattering cross sections of light water at the Spallation Neutron Source at Oak Ridge National Laboratory. Mean values and covariance data were generated for model parameters, phonon density of states, double-differential cross sections, and total scattering cross sections. These posterior parameter values were very similar to their prior values with a maximum relative error of 0.54%. This falls within in the Unified Monte Carlo–calculated uncertainties on the order of 2.7%. Additionally, posterior double-differential cross sections agree favorably with ENDF/B-VIII.0 cross sections. The new thermal scattering law was tested by comparing it against benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook, which showed a slight improvement over the ENDF/B-VIII.0 library. Additionally, the covariance matrix of the phonon density of states was validated to confirm that the spread of k eff from the density of states used to generate the covariance matrix was similar to the spread of k eff from the density of states of the sampled covariance matrix.

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Diffusion Synthetic Acceleration for Heterogeneous Domains, Compatible with Voids

A standard approach to solving the S N transport equations is to use source iteration with diffusion synthetic acceleration (DSA). Although this approach is widely used and effective on many problems, there remain some practical issues with DSA preconditioning, particularly on highly heterogeneous domains. For large-scale parallel simulation, it is critical that both (a) preconditioned source iteration converges rapidly and (b) the action of the DSA preconditioner can be applied using fast, scalable solvers, such as algebraic multigrid (AMG). For heterogeneous domains, these two interests can be at odds. In particular, there exist DSA diffusion discretizations that can be solved rapidly using AMG, but they do not always yield robust/fast convergence of the larger source iteration. Conversely, there exist robust DSA discretizations where source iteration converges rapidly on difficult heterogeneous problems, but fast parallel solvers like AMG tend to struggle applying the action of such operators. Moreover, very few current methods for the solution of deterministic transport are compatible with voids. This paper develops a new heterogeneous DSA preconditioner based on only preconditioning the optically thick subdomains. The resulting method proves robust on a variety of heterogeneous transport problems, including a linearized hohlraum mesh related to inertial confinement fusion. Moreover, the action of the preconditioner is easily computed using O(1) AMG iterations, convergence of the transport iteration typically requires 2 to 5× fewer iterations than current state-of-the-art “full” DSA, and the proposed method is trivially compatible with voids. On the hohlraum problem, rapid convergence is obtained by preconditioning less than 3% of the mesh elements with five to ten AMG iterations.

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Secondary-Source Core Reload Modeling with VERA

The CASL reactor simulation package VERA has been adapted to provide high-fidelity simulation capabilities for modeling source range detector response during subcritical reactor configurations. New features include the activation and shuffling of secondary-source assemblies, use of burned fuel neutron emission data from the ORIGEN depletion solver to the MPACT deterministic neutron transport solver, allowance of user-defined sources in MPACT based on material composition, ability to solve the subcritical source-driven system with neutron multiplication using the MPACT diffusion solver, and transfer of the calculated fission source from MPACT to the continuous-energy Monte Carlo solver Shift for final detector response evaluation using the CADIS methodology for variance reduction. These new capabilities were benchmarked against Watts Bar Unit 1 plant operating data for the first few fuel loading steps and were found to demonstrate excellent agreement with the measured data.

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Generation of the Thermal Scattering Law of Uranium Dioxide with Ab Initio Lattice Dynamics to Capture Crystal Binding Effects on Neutron Interactions

Scattering of thermal neutrons and Doppler broadening of epithermal neutron resonances in uranium and its compounds may be sensitive to crystal binding. The thermal scattering law (TSL) for uranium dioxide, which captures crystal binding effects, has been reevaluated for ENDF/B-VIII.0. Phonon spectra were generated using ab initio lattice dynamics for the paramagnetic phase and validated against experiment. Improved agreement with the Debye-Waller coefficient as a function of temperature is found relative to the spectrum used for the ENDF/B-VII.1 evaluation. The TSL was generated using the phonon expansion method within the NJOY nuclear data processing package and was found to be in reasonable agreement with inelastic neutron scattering measurements. The present evaluation predicts a reduction in the inelastic scattering cross section relative to ENDF/B-VII.1 and a total scattering cross section consistent with neutron transmission experiments

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Validation of Continuous-Energy ENDF/B-VIII.0 16 O, 56 Fe, and 63,65 Cu Cross Sections for Nuclear Criticality Safety Applications

Recently completed cross-section evaluations sponsored in part by the Nuclear Criticality Safety Program were incorporated into the 2018 release of the ENDF/B-VIII.0 cross-section library. Evaluated isotopes of interest to the nuclear data and criticality safety community include 16 O, 56 Fe, and 63,65 Cu. For performance validation, benchmark models defined in the International Criticality Safety Benchmark Evaluation Project Handbook were selected based on energy-integrated k eff sensitivities to total cross sections of interest and compared with experimental values. Of the 102 benchmark configurations that were utilized, 63 are sensitive to 16 O, 32 sensitive to 63,65 Cu, and 25 sensitive to 56 Fe. Selected benchmarks were modeled in SCALE 6.2.3 Criticality Safety Analysis Sequence (CSAS) continuous-energy Monte Carlo k eff calculations with ENDF/B-VII.1, with a hybrid ENDF/B-VII.1 with ENDF/B-VIII.0 data substituted for individual isotopes of interest, and with ENDF/B-VIII.0. ENDF/B-VIII.0 showed improved agreement with experimental k eff for 56 Fe, 63 Cu, elemental copper, and full library substitution while producing lessened agreement for 16 O and 65 Cu. Furthermore, with full library and isotope-specific ENDF/B-VIII.0 performance, a best-case ENDF library was formed by excluding underperforming isotopes’ ENDF/B-VIII.0 data, reverting 16 O and 65 Cu cross sections to ENDF/B-VII.1. This resulted in the average relative deviation between calculated and experimental data improving from 1.45σ for the ENDF/B-VIII.0 library to 1.32σ for the best-case library, relative to benchmark uncertainty.

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A New Era of Nuclear Criticality Experiments: The First 10 Years of Godiva IV Operations at NCERC

The work presented in this paper focuses on the first 10 years (2011–2020) of Godiva IV operations at the National Criticality Experiments Research Center (NCERC). Godiva IV is a fast burst critical assembly constructed of approximately 65 kg of highly enriched uranium fuel alloyed with 1.5% molybdenum for strength. Godiva is one of the last such critical assemblies in the United States and can be used for studies of super-prompt-critical behavior as well as irradiations and demonstrations. An overview of the startup of Godiva IV at NCERC is given followed by a summary of the experiments performed utilizing Godiva IV over the first 10 years of operation at NCERC.

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A New Era of Nuclear Criticality Experiments: The First 10 Years of Flattop Operations at NCERC

The Flattop critical assembly was built and operated from 1958 through 2004 at the Pajarito Site (Technical Area-18), home to the Los Alamos Critical Experiments Facility. Flattop was disassembled in 2005 and refurbished over the course of 3 years. In 2008, Flattop was installed in the National Criticality Experiments Research Center (NCERC) located in the Device Assembly Facility at the Nevada National Security Site. Startup of Flattop with a uranium core occurred in 2011. This paper details the first 10 years of Flattop operations at NCERC (2011–present).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A New Era of Nuclear Criticality Experiments: The First 10 Years of Comet Operations at NCERC

Comet is a general-purpose, heavy-duty, vertical-lift assembly designed for flexibility in conducting a variety of critical experiments. It is currently located at the National Criticality Experiments Research Center (NCERC) in Nevada. In the past, Comet resided at Technical Area-18 in Los Alamos, New Mexico, as part of the Los Alamos Critical Experiments Facility (LACEF). The Comet assembly was relocated to NCERC in 2008 and became fully operational in June of 2011. The first critical experiment performed on Comet at NCERC was a verification of one of the previous configurations of the Zeus experiment series. Over the next 10 years, many additional experiments followed including other Zeus configurations as well as completely new designs. This paper discusses the Comet vertical-lift assembly, the transition from LACEF to NCERC, and a selection of experiments that have been performed on Comet during its first 10 years of operation at NCERC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A New Era of Nuclear Criticality Experiments: The First 10 Years of Planet Operations at NCERC

Planet is a vertical-lift assembly machine currently located at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site. In the past, Planet resided at Technical Area-18 in Los Alamos, New Mexico, as part of the Los Alamos Critical Experiments Facility (LACEF). Following the de-inventorying of LACEF, the Planet assembly was relocated to NCERC in 2008 and became fully operational in June of 2011. The Class Foils experiment, which involves stacking highly enriched uranium foils to obtain a critical configuration, was the first critical experiment performed on Planet. As a major component of the Nuclear Criticality Safety Class taught for the U.S. Department of Energy (DOE) Nuclear Criticality Safety Program, the Class Foils experiment allows personnel from all over the DOE complex to handle nuclear material and to complete the approach to critical safely and successfully. This paper describes the Planet vertical assembly and recent engineering upgrade and a selection of the experiments that have been performed on Planet since its transition to NCERC 10 years ago.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurements of Neutron Scattering from a Copper Sample Using a Quasi-Differential Method in the Region from 2 keV to 20 MeV

Neutron scattering from a copper sample was measured at Rensselaer Polytechnic Institute utilizing the quasi-differential method. The measurement spanned the energy range from 0.5 to 20 MeV using the high-energy scattering system and from 2 keV to 0.5 MeV using the new mid-energy scattering system. Copper was selected as a material of interest to measure due to large discrepancies between experiments and simulations of the Zeus benchmark. The Zeus benchmark consists of a copper reflected highly enriched uranium system, and the angular distribution of copper scattering was thought to potentially be the cause of the discrepancy. The copper measurements found differences in the scattering response particularly in the incident energy region from 1 to 2 MeV for the high-energy measurement and from 2 to 4 keV in the mid-energy system. These differences are particularly noticeable at angles near 90 deg in the high-energy system and back angles in the mid-energy system. Additionally, for ENDF/B-VIII.0 there is a large discrepancy at the forward angle in the energy range around 0.5 MeV. For these reasons, a new evaluation of copper scattering utilizing these results is recommended and perhaps could help to improve the agreement with the Zeus benchmarks.

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Solution Irregularity Remediation for Spatial Discretization Error Estimation for S N Transport Solutions

The discrete ordinates linear Boltzmann transport equation is typically solved in its spatially discretized form, incurring spatial discretization error. Quantification of this error for purposes such as adaptive mesh refinement or error analysis requires an a posteriori estimator, which utilizes the numerical solution to the spatially discretized equation to compute an estimate. Because the quality of the numerical solution informs the error estimate, irregularities, present in the true solution for any realistic problem configuration, tend to cause the largest deviation in the error estimate vis-a-vis the true error. In this paper, an analytical partial singular characteristic tracking (pSCT) procedure for reducing the estimator’s error is implemented within our novel residual source estimator for a zeroth-order discontinuous Galerkin scheme, at the additional cost of a single inner iteration. Here, a metric-based evaluation of the pSCT scheme versus the standard residual source estimator is performed over the parameter range of a Method of Manufactured Solutions test suite. The pSCT scheme generates near-ideal accuracy in the estimate in problems where the dominant source of the estimator’s error is the solution irregularity, namely, problems where the true solution is discontinuous and problems where the true solution’s first derivative is discontinuous and the scattering ratio is low. In problems where the scattering ratio is high and the true solution is discontinuous in the first derivative, the error in the scattering source, which is not converged by the pSCT scheme, is greater than the error incurred due to the irregularity. Ultimately, a pSCT scheme is judged to be useful for error estimation in problems where the computational cost of the scheme is justified. In the presence of many irregularities, such a scheme may be intractable for general use, but in benchmarks, as an analytical tool, or in problems that have nondissipative discontinuities, the scheme may prove invaluable.

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A Machine Learning Method for the Forensics Attribution of Separated Plutonium

Plutonium (Pu) source attribution would be a powerful tool to support nuclear nonproliferation efforts. This capability to find the source of a Pu sample would act as a deterrent to smuggling efforts, and also help regulatory agencies verify declared nuclear activities. Work at Texas A&M University yielded a nuclear forensics methodology, which is capable of determining separated Pu’s reactor of origin, fuel burnup, and the time since irradiation (TSI)—three parameters of interest. The methodology used a set of ten intra-element isotopic ratios found in separated Pu, which was compared to a library of isotopic ratio values produced using neutronics simulations for reactors of interest. By calculating the probability that unknown Pu sample’s isotopic ratio set matched a set in the library, the methodology could predict the three parameters of interest of the sample. One shortcoming of this methodology was an inability to correctly attribute spoofed Pu, where Pu sourced from two different reactors or two different fuel burnup levels are mixed. A new methodology to rectify this vulnerability using machine learning (ML) technique is developed, instead of the maximum likelihood calculation previously used and the results are satisfactory. The ML approach leverages the existing simulated data for training the algorithm, but use them efficiently by only using intra-element isotope ratios that contribute to the attribution one of the three parameters at a time. Previously, all isotope ratios were used to attribute all three parameters together. The new methodology attributes the Pu parameters in three steps, one for each parameter, rather than resolving all of the three parameters simultaneously like the previous maximum likelihood approach. First, a support vector machine classifier with a set of seven isotopic ratios finds the reactor of origin and a set of regression models trained using gaussian process predicts the burnup with a different set of seven isotopes. Finally, TSI is calculated analytically using decay equations. Thus far, the new methodology is capable of attributing pure Pu samples and has been validated using experimental data. The next step will to be augment the classifier training data set with spoofed Pu data.

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