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Incorporating new evaluation on angular distributions and energy spectra of neutron-induced charged particle reactions into the next ENDF library release (Technical Progress Report)
This project aims to provide the improved Evaluated Nuclear Data File (ENDF) using the newly measured data as well as the latest nuclear reaction model for calculating angular distributions and energy spectra on neutron-induced charged particle reactions through the collaboration of Korea Atomic Energy Research Institute (KAERI) and Los Alamos National Laboratory (LANL). The LANL group will provide the experimental data for angular distributions and spectra of (n,p) and (n,α) on several structural materials such as Fe, Ni and Zn isotopes using the Low Energy Neutron-induced Charged-particle (Z) Chamber (LENZ) instrument at Los Alamos Neutron Science Center (LANSCE). The KAERI group will provide the improved evaluated nuclear library which is based on the LANL experimental data, and further will predict angular distributions and spectra of (n,p) and (n,α) reactions on unmeasured nuclides, such as Cr, Mn, Co, Cu and so on. For the first year of this project, we planned to analyze (n,p) and (n,α) reactions for 54,56 Fe and perform new measurements on those reactions for 58,60 Ni isotopes with the LENZ instrument at LANSCE. For improving our evaluation quality, we have studied reaction models to reproduce LANL’s experimental angular distributions and energy spectra using the full Hauser-Feshbach model code, CoH3 with no approximations used. As the first year’s deliverables, we provided the experimental (n,p) and (n,α) reaction cross sections for 54,56 Fe and incorporate new evaluation on angular distributions and energy spectra of neutron-induced charged particle reactions into the current ENDF/B-VIII.0.
Quantitative X-ray tomographic analysis reveals calcium precipitation in cataractogenesis
Cataracts, named for pathological light scattering in the lens, are known to be associated with increased large protein aggregates, disrupted protein phase separation, and/or osmotic imbalances in lens cells. We have applied synchrotron phase contrast X-ray micro-computed tomography to directly examine an age-related nuclear cataract model in Cx46 knockout (Cx46KO) mice. High-resolution 3D X-ray tomographic images reveal amorphous spots and strip-like dense matter precipitates in lens cores of all examined Cx46KO mice at different ages. The precipitates are predominantly accumulated in the anterior suture regions of lens cores, and they become longer and dense as mice age. Alizarin red staining data confirms the presence of calcium precipitates in lens cores of all Cx46KO mice. This study indicates that the spatial and temporal calcium precipitation is an age-related event associated with age-related nuclear cataract formation in Cx46KO mice, and further suggests that the loss of Cx46 promotes calcium precipitates in the lens core, which is a new mechanism that likely contributes to the pathological light scattering in this age-related cataract model.
Innovative Reduced-Order Models for Subsurface Radionuclide Transport in Nuclear Waste Management
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Quantifying uncertainty in machine learning for nuclear binding energy
Techniques from artificial intelligence and machine learning are increasingly employed in nuclear theory; however, the uncertainties that arise from the complex parameter manifold encoded by the neural networks are often overlooked. Epistemic uncertainties arising from training the same network multiple times for an ensemble of initial weight sets offer a first insight into the confidence of machine learning predictions, but they often come with a high computational cost. Instead, we apply a single-model uncertainty quantification method called Δ-UQ that gives epistemic uncertainties with one-time training. Here, we demonstrate our approach on a two-feature model of nuclear binding energies per nucleon with proton and neutron number pairs as inputs. We show that Δ-UQ can produce reliable and self-consistent epistemic uncertainty estimates and can be used to assess the degree of confidence in predictions made with deep neural networks.
Blending and cavern formation within non-Newtonian fluids in stirred tanks: Application to nuclear waste fluid processing
A numerical approach for predicting the time-accurate fluid flow and mixing properties of non-Newtonian fluids is presented. This approach, which is based on the lattice Boltzmann method, is used to characterize the blending in shear-thinning fluids, as well as cavern formation in yield-stress fluids. Predictions compare favorably to measured data and expectations from first-principles theory. Importantly, across the range of fluids and systems here, the simulations require no reparameterization or retuning between scenarios. This generality is exploited to model a nuclear waste processing unit operation.
Nek5000: improvements in the available RANS models, meshing, tutorials, and training
This year, the Nuclear Energy Advanced Modeling Simulation program (NEAMS) thermal-hydraulics report for Nek5000 NRC- and verification and validation (V&V)-driven development focuses on following areas of code application and improvement. First we have continued improvements of RANS modeling capabilities in Nek5000 including improved k-tau model focusing mostly on wallfunction initial implementation with spectral element method (SEM) and initiating investigation of an alternative approach XSEM that greatly reduces discretization errors.
High-level fuel fabrication facility designs from discrete-event simulation
Like other industrial processes, the production of metallic nuclear fuels (MNF) requires that fabrication facilities be able to reliably meet production demands, operate efficiently, and adhere to federal and local safety regulations. In turn, the set of design variables employed by such a facility, such as operations policies, infrastructure and machinery purchased, and the type and number of staff hired, directly impact a facility’s ability to satisfy these goals. Therefore, facility designers must carefully determine which set of design variable values optimally satisfies these constraints. In this paper, we explore how values for these high-level design variables, namely hiring requirements, can be determined in the context of nuclear fuel manufacturing through the coupling of physics-based and discrete-event simulation technologies. Using the Versatile Test Reactor (VTR) program as a case study, we demonstrate how SCALE and MCNP nuclear physics model outputs can be integrated into ExtendSim discrete-event simulation (DES) models of the fuel fabrication process to determine the optimal number of staff hired to ensure fuel production goals are met, operations comply with effective dose limit regulations, and overall project costs are reduced.
Probing Gluon Fluctuations in Nuclei with the First Energy-Dependent Measurement of Incoherent 𝐽/𝜓 Photoproduction in Ultraperipheral PbPb Collisions
Incoherent 𝐽/𝜓 photoproduction in heavy ion ultraperipheral collisions (UPCs) provides a sensitive probe of localized, fluctuating gluonic structures within heavy nuclei. This Letter reports the first measurement of the photon-nucleon center-of-mass energy (𝑊 𝛾N ) dependence of this process in PbPb UPCs at a nucleon-nucleon center-of-mass energy of 5.02 TeV, using 1.52 nb −1 of data recorded by the CMS experiment. The measurement covers a wide 𝑊 𝛾N range of ≈40–400 GeV, probing gluons carrying a fraction 𝑥 of nucleon momentum down to an unexplored regime of 6.5 ×10 −5 . Compared to baseline predictions neglecting nuclear effects, the measured cross sections exhibit significantly greater suppression at lower 𝑥. Additionally, the ratio of incoherent to coherent photoproduction is found to be constant across the probed 𝑊 𝛾N and 𝑥 range, disfavoring the establishment of the black disk limit. This Letter provides critical insights into the 𝑥-dependent evolution of fluctuating gluonic structures within nuclei and calls for further advancements in theoretical models incorporating nuclear shadowing and gluon saturation.
MOOSE-Workbench integration and MOOSE meshing capability enhancements to facilitate inputs and outputs for multiphysics modeling
The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and out put inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.
MOOSE–Workbench Integration and MOOSE Meshing Capability Enhancements to Facilitate Inputs and Outputs for Multiphysics Modeling
The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and output inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.
Data Validation Experiments with a Computer-Generated Imagery Dataset for International Nuclear Safeguards
Computer vision models have great potential as tools for international nuclear safeguards verification activities, but off-the-shelf models require fine-tuning through transfer learning to detect relevant objects. Because open-source examples of safeguards-relevant objects are rare, and to evaluate the potential of synthetic training data for computer vision, we present the Limbo dataset. Limbo includes both real and computer-generated images of uranium hexafluoride containers for training computer vision models. Here, we generated these images iteratively based on results from data validation experiments that are detailed here. The findings from these experiments are applicable both for the safeguards community and the broader community of computer vision research using synthetic data.
Comparing matching prescriptions between pre-equilibrium and hydrodynamic models in high-energy nuclear collisions
Abstract State-of-the-art simulations of high-energy nuclear collisions rely on hybrid setups, involving in particular a pre-equilibrium stage to let the system evolve from a far-from-equilibrium initial condition towards a near-equilibrated state after which fluid dynamics can be applied meaningfully. A known issue is the mismatch between the equation of state in the fluid-dynamical evolution and the effective one in the previous stage, which leads to discontinuities at the interface between the two models. Here we introduce a new matching prescription at this interface, based on the entropy, and we compare it with the standard one relying on local energy conservation. We study the behavior of various quantities at the switching time between the models and investigate a number of final-state hadronic observables. For the latter, we show that they are not modified significantly by the choice of matching prescription, provided an appropriate normalization is chosen for the initial state. In turn, our approach reduces sizeably the ratio of bulk over thermodynamic pressure at the beginning of the fluid-dynamical stage.
Curvature-slope correlation of nuclear symmetry energy and its imprints on the crust-core transition, radius, and tidal deformability of canonical neutron stars
Background: The nuclear symmetry energy E sym (ρ) encodes information about the energy necessary to make nuclear systems more neutron-rich. While its slope parameter L at the saturation density ρ 0 of nuclear matter has been relatively well constrained by recent astrophysical observations and terrestrial nuclear experiments, its curvature K sym characterizing the E sym (ρ) around 2ρ 0 remains largely unconstrained. Over 520 calculations for E sym (ρ) using various nuclear theories and interactions in the literature have predicted several significantly different K sym –L correlations. Purpose: If a unique K sym –L correlation of E sym (ρ) can be firmly established, it will enable us to progressively better constrain the high-density behavior of E sym (ρ) using the available constraints on its slope parameter L. Here, we investigate if and by how much the different K sym –L correlations may affect neutron star observables. Method: A meta-model of nuclear Equation of States (EOSs) with three representative K sym –L correlation functions is used to generate multiple EOSs for neutron stars. We then examine effects of the K sym –L correlation on the crust-core transition density and pressure as well as the radius and tidal deformation of canonical neutron stars. Results: The K sym –L correlation affects significantly both the crust-core transition density and pressure. It also has strong imprints on the radius and tidal deformability of canonical neutron stars especially at small L values. The available data from LIGO/VIRGO and NICER set some useful limits for the slope L but can not distinguish the three representative K sym –L correlations considered.
MECHANISTIC MULTIPHYSICS MODELING OF CLADDING RUPTURE IN NUCLEAR FUEL RODS DURING LOSS-OF-COOLANT ACCIDENT CONDITIONS
The Loss of Coolant Accident (LOCA) is a design basis accident that is included as part of the safety analysis of nuclear power plants. As the nuclear industry desires to increase the cycle length and discharge burnup of existing nuclear power plants they must demonstrate safe operation during a LOCA on high burnup fuel. During a LOCA transient on high burnup fuel rods, the rods may undergo a process known as fuel fragmentation, relocation, and dispersal (FFRD). To permit dispersal, the cladding encapsulating the fuel must rupture with an opening size large enough to allow the fragmented fuel particles to release. Current licensing tools used by industry and the United States Nuclear Regulatory Commission are limited in geometric fidelity and materials that can be analyzed. These simulation tools generally employ a quasi-two-dimensional (1.5D or Layered1D) or 2D-RZ axisymmetric geometric representations exclusively. While a valid approach under some instances, there are times when important physics have an asymmetric behavior in the fuel rod. Examples include fuel fragmentation, thermal-hydraulic boundary conditions, and cladding rupture, all of which are important for LOCA analysis. As industry pursues burnup extensions it must be demonstrated that fuel dispersal can be mitigated or eliminated. To do this, an understanding of the rupture opening after cladding failure is required. This work presents the development of a model for predicting the size and location of the rupture opening in failed fuel rods during LOCA conditions using advanced modeling and simulation tools. In order to supply the rupture model with appropriate boundary conditions, improvements to fuel fragmentation, axial relocation and oxidation modeling were required. First, the eXtended Finite Element Method (XFEM) is used to mechanistically predict the number of fuel fragments that form due to material strength randomization, criteria for strength randomization, mesh density, power ramping rates and irradiation effects. These predictions with associated uncertainty were compared to empirical correlations developed for UO2 verifying that they can be used with increased confidence in subsequent axial relocation analyses. Secondly, a new first-of-its-kind Layered2D computational framework was developed that provides the ability to apply azimuthally varying boundary conditions while providing discrete layers to track fuel movement during the LOCA. An existing fuel axial relocation model developed for Layered1D was extended to work within the Layered2D framework. A large sensitivity study was performed on the initial version of the model to identify modeling parameters of particular importance, with the emissivity used for radiation after blowdown being the primary source of uncertainty. Then, a simplistic approach to incorporate mechanical degradation of the cladding due to oxidation was also developed to investigate the impact of reduced cladding thickness on predictions of the time to failure of cladding tubes. It was found that the cladding will typically rupture prior to a reduction in thickness that is sufficient to impact the rupture behavior. A model was then developed for predicting cladding rupture that transfers the cladding surface temperatures, rod internal and external pressures, fast neutron fluence, and fast neutron flux from a more detailed Layered1D, Layered2D, or 2D-RZ analysis to a 3D cladding only analysis. Comparisons of the rupture model to a few experiments indicate reasonable predictions. The rupture model was then applied to two accident tolerant fuel concepts (FeCrAl and Cr-coated Zircaloy) where it predicted that both ATF concepts would have smaller rupture openings and delayed rupture times than the standard Zircaloy-4 cladding material under identical loading conditions.
Apparent temperatures of neutron-poor and neutron-rich compound nuclei
The possibility of the dependence of the nuclear caloric curve on neutron excess sets a limit on the accuracy of our knowledge of the nuclear equation of state, and thus impacts predictive capabilities of nuclear reaction and nuclear astrophysics models. To date, theoretical models have not reached consensus on the magnitude or sign on the asymmetry dependence. To provide constraints, we have measured evaporated particles and heavy residues for complete and incomplete fusion-evaporation reactions in inverse kinematics. The temperatures extracted from the observed light charged particles tend to favor higher temperatures for the neutron-rich fused systems, though they are near the limits of the systematic uncertainty. The present measurement may be used as an upper limit to constrain the asymmetry dependence of the nuclear caloric curve.
Fission fragment decay simulations with the CGMF code
The CGMF code implements the Hauser-Feshbach statistical nuclear reaction model to follow the de-excitation of fission fragments by successive emissions of prompt neutrons and γ rays. The Monte Carlo technique is used to facilitate the analysis of complex distributions and correlations among the prompt fission observables. Starting from initial configurations for the fission fragments in mass, charge, kinetic energy, excitation energy, spin, and parity, Y(A,Z,KE,U,J,π), CGMF samples neutron and γ-ray probability distributions at each stage of the decay process, conserving energy, spin and parity. Nuclear structure and reaction input data from the RIPL3 library are used to describe fission fragment properties and decay probabilities. Characteristics of prompt fission neutrons, prompt fission γ rays, and independent fission yields can be studied consistently. Correlations in energy, angle and multiplicity among the emitted neutrons and γ rays can be easily analyzed as a function of the emitting fragments. Finally, in its current version, CGMF is limited to certain spontaneous fission reactions on Pu and Cf isotopes, as well as neutron-induced fission reactions up to 20 MeV on U, Np, and Pu isotopes.
Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program
This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.