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The neutron standards sublibrary describes specific reaction cross sections, in a limited range, that are so well-known that they are used as ratios or references in other measurements. ENDF/B-VIII.1 remains unchanged from ENDF/B-VIII.0 for the neutron standards sublibrary
This report presents the development and validation of an initial steady-state multiphysics capability for molten salt reactors (MSRs) under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in Fiscal Year 2025. The framework integrates neutronics, thermal-hydraulics, species transport, and thermochemistry to capture the coupled dynamics of liquid-fueled systems. Implementation and testing were performed on two representative designs: the Molten Salt Reactor Experiment (MSRE), a thermal-spectrum, channeled-flow reactor, and the Lotus Molten Salt Reactor (L-MSR), a fast-spectrum, pool-type reactor. The modeling suite employs Griffin for reactor physics and depletion, Pronghorn and SAM for thermal-hydraulics, Thermochimica for chemistry, and Saline for thermophysical properties, with benchmarking and validation carried out against historical MSRE data, experimental flow-loop measurements, and reference depletion calculations from Monte Carlo codes. The framework demonstrated the ability to reproduce key reactor behaviors including temperature feedback, reactivity losses, delayed neutron precursor transport, xenon poisoning, and redox potential evolution. The results confirm the feasibility and accuracy of the coupled models in predicting steady-state and selected transient MSR behaviors. This latter ones are used in this report as a proxy indicating that the steady-state models from which the transient starts are accurate. For MSRE, validation showed good agreement with pump start-up and natural circulation tests, while for the L-MSR, benchmarking confirmed hydraulic calibration and consistency of neutronics–thermal coupling. The tools also provided new insights into species transport, noble metal deposition, and salt solidification dynamics. On the Xenon transport front, the code is validated against the steady state Xenon poisoining measurement and showed good agreement with the experimental value. Identified areas for future work include advanced void transport modeling, three-dimensional simulations, improved alloy corrosion models, and tighter integration with high-fidelity Monte Carlo codes. These developments provide a foundation for high-fidelity MSR simulations that can support reactor design optimization, safety assessments, and long-term operational strategies.
We have used small-angle neutron scattering to determine the vortex lattice phase diagram in the topological superconductor UPt 3 for the applied magnetic field along the crystalline c -axis. A triangular vortex lattice is observed throughout the superconducting state, but with an orientation relative to the hexagonal basal plane that changes with field and temperature. At low temperature, in the chiral B phase, the vortex lattice undergoes a non-monotonic rotation with increasing magnetic field. The rotation amplitude decreases with increasing temperature and vanishes before reaching the A phase. Within the A phase an abrupt ±15° vortex lattice rotation was previously reported by Huxley et al. , Nature 406 , 160-164 (2000). The complex phase diagram may be understood from competing effects of the superconducting order parameter, the symmetry breaking field, and the Fermi surface anisotropy. The low-temperature rotated phase, centered around 0.8 T, reported by Avers et al. , Nature Physics 16 , 531-535 (2020), can be attributed directly to the symmetry breaking field.
Accurate predictive modeling of high explosives in abnormal conditions, such as a fire, is critical to personnel safety. Modeling depends heavily on precise physical characterization of the high explosive in question. The aim of this thesis was to characterize the detonation response to shock and the microstructure at high-temperature (250°C) of PBX 9502 and use these data to attempt to model these results using a new reactive burn model called SURF (Scaled Uniform Reactive Front). In order to characterize the shock response of PBX 9502 at high-temperature a 1D gas gun experiment was designed and executed that provided shock to detonation transition data. These data were then used to do a preliminary calibration of SURF for PBX 9502 at 250°C. Small-angle neutron scattering (SANS) was employed to characterize the void morphology of PBX 9502 as a function of temperature. This was done in order to feed a modified version of SURF called physically informed - SURF (π-SURF) which uses the void size and quantity distribution data as measured by SANS along with the deflagration and detonation characteristics of a high explosive to inform the SURF model. The π-SURF model was then used to model both ambient and high-temperature PBX 9502 SDT response and the results were compared to the physically measured results. It was found that π-SURF works in ambient cases. At high-temperature, however, it was determined that not enough information is known about hot spot formation to use the π-SURF model for high-temperature scenarios.
This paper extends our recent work on the Physics-Informed Neural Networks (PINN) approach for the fixed source diffusion models and applies it to the diffusion theory based k-eigenvalue problems. To make the PINN equitable for the eigenvalue problems, we introduce a novel integral regularization term to the loss function in the framework, and allow the direct inference of the principal eigenvalue and the associated eigenfunction. The regularization term enforces a pre-defined value on the integration of the model predictions, and this value can be directly related to a physical property of the system. We also introduce an additional learnable parameter to approximate the principal eigenvalue. As a proof of principle, we solve the one-group two-dimensional k-eigenvalue neutron diffusion equation in this work. We then provide two numerical examples to demonstrate the applicability of the PINN approach. In each example, we solve the k-eigenvalue diffusion equation in a multi-region configuration constrained with a set of Robin boundary conditions for generality. We use a FEM solution based on the power-iteration method to verify the results of the PINN solution. The results showed relative percentage error in the predicted eigenvalue of about 0.77% and about 1.2% for example 1 and example 2, respectively. The mean absolute error in the predicted flux for example 1 is ∼ 0.002 and for example 2 is ∼ 0.0024. These results indicate some preliminary successes of the PINN application to k-eigenvalue problems. (authors)
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Neutron scattering is a powerful tool to elucidate the structure and dynamics of systems that are important to geochemists, including ion association in complex aqueous solutions, solvent-exchange reactions at mineral–water interfaces, and reaction and transport of fluids in nanoporous materials. This article focusses on three techniques: neutron diffraction, which can reveal the atomic-level structure of aqueous solutions and solids; quasi-elastic neutron scattering, which measures the diffusional dynamics at mineral–water interfaces; and small-angle neutron scattering, which can show how properties of nanoporous systems change during gas, liquid, and solute imbibition and reaction. Furthermore, the usefulness and applicability of the experimental results are extended by rigorous comparison to computational simulations.
We uncover high-order harmonics and the reverse of the squaring-up process, in terms of analyzing the evolution of magnetic orders in a centrosymmetric layered triangular-lattice magnet HoPdAl 4 Ge 2 , based on a detailed study of the crystal structure, magnetic susceptibility, magnetization, heat capacity, and magnetic structure. Temperature dependencies of magnetic susceptibility and heat capacity show two magnetic transitions at T N = 10.5 K and T t = 5.5 K. Below T N , Ho 3+ spins order antiferromagnetically as a transverse spin-density wave with the propagation vector k 1 = (001.5 – δ) with δ ≈ 0.18. Upon further cooling through T t , the high-order harmonics with k n = (001.5 – nδ), n = 3, 5, 7 develop, suggesting a squaring-up process. It is surprising that the squaring-up process does not continue down to 0 K but reverses the trend below 3 K. Magnetic-field-induced metastable transitions were observed in M(H) curves with the fields applied both parallel and perpendicular to the triangular-lattice plane. Neutron-diffraction results suggest that the magnetization process in HoPdAl 4 Ge 2 involves the conversion of k n = (001.5 – nδ) with n = 1, 3, 5, 7, to a ferromagnetic k F = (000) component. It is worth noting that the already weak seventh harmonic magnetic peak is enhanced by applying a small magnetic field in the ab plane at 1.5 K or warming up to 3 K, accompanied by a slight decrease of δ.
Low-enriched-uranium (LEU) reactor systems utilize moderators to improve neutron economy. Solid yttrium hydride is one of the primary moderator candidates for high-temperature (>700 °C) nuclear reactor applications. This is due to its ability to retain hydrogen at elevated temperatures compared to other metal hydrides. For reactor modeling purposes, both neutronic and thermos-mechanical modeling, several high-temperature properties for sub-stoichiometric yttrium hydride (YH2−x) are needed. In this paper, we present an atomistics and a neutron diffraction study of the high-temperature properties of Y and YH2−x. Specifically, we focus on the thermal lattice expansion effects in yttrium metal and yttrium hydride, which also govern bulk thermal expansion. Previously reported physical and mechanical properties for sub-stoichiometric yttrium hydride at ambient conditions are expanded using lattice dynamics to take into account high-temperature effects. Accordingly, an array of newly generated properties is presented that enables high-fidelity neutronics, and thermomechanical modeling. These properties include various elastic moduli, thermal expansion parameters for yttrium and yttrium hydride, and single-phase (YH2−x) and two-phase (Y + YH2−x) density as a function of stoichiometry and density.
Lanthanide element signatures are key to understanding many astrophysical observables, from merger kilonova light curves to stellar and solar abundances. To learn about the lanthanide element synthesis that enriched our solar system, we apply the statistical method of Markov Chain Monte Carlo to examine the nuclear masses capable of forming the r-process rare-earth abundance peak. We describe the physical constraints we implement with this statistical approach and demonstrate the use of the parallel chains method to explore the multidimensional parameter space. We apply our procedure to three moderately neutron-rich astrophysical outflows with distinct types of r-process dynamics. We show that the mass solutions found are dependent on outflow conditions and are related to the r-process path. We describe in detail the mechanism behind peak formation in each case. We then compare our mass predictions for neutron-rich neodymium and samarium isotopes to the latest experimental data from the CPT at CARIBU. Here, we find our mass predictions given outflows that undergo an extended (n,γ)⇌(γ,n) equilibrium to be those most compatible with both observational solar abundances and neutron-rich mass measurements.
We use neutron scattering and bulk property measurements to determine the single-ion crystal-field Hamiltonians of delafossites KErSe 2 and CsErSe 2 . These two systems contain planar equilateral triangular Er lattices arranged in two stacking variants: rhombohedral (for K) or hexagonal (Cs). Our analysis shows that regardless of the stacking order both compounds exhibit an easy-plane ground-state doublet with large J z =1/2 terms and the potential for significant quantum effects, making them candidates for quantum-spin-liquid or other exotic ground states.
The neutron-induced fission yields (NFY) sublibray aims to describe fission yields in neutron-induced reactions. For ENDF/B-VIII.1, there were no new fission yields complete evaluations. However, an important fix the 241 Pu NFY file was implemented, solving a long-standing anomalous discontinuity issue accidentally introduced in ENDF/B-VI.2, decades ago. Additionally, many erroneously large uncertainties, present in NFY from ENDF/B-VIII.0, were corrected.
This work explores the construction of a fast emulator for the calculation of the final pattern of nucleosynthesis in the rapid neutron capture process (the r-process). An emulator is built using a feed-forward artificial neural network (ANN). We train the ANN with nuclear data and relative abundance patterns. We take as input the β-decay half-lives and the one-neutron separation energy of the nuclei in the rare-earth region. The output is the final isotopic abundance pattern. In this work, we focus on the nuclear data and abundance patterns in the rare-earth region to reduce the dimension of the input and output space. We show that the ANN can capture the effect of the changes in the nuclear physics inputs on the final r-process abundance pattern in the adopted astrophysical conditions. We employ the deep ensemble method to quantify the prediction uncertainty of the neural network emulator. The emulator achieves a speed-up by a factor of about 20 000 in obtaining a final abundance pattern in the rare-earth region. The emulator may be utilized in statistical analyses such as uncertainty quantification, inverse problems, and sensitivity analysis.
This engineering calculations and analysis report (ECAR) documents the results of the Advanced Test Reactor (ATR) detailed Monte Carlo N-Particle (MCNP) code full-core model as-run physics analysis performed to support the Colorado School of Mines (CSM) experiment in the B-5 position.