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At least 1,135 records · Page 63

The landscape of disc outflows from black hole–neutron star mergers

ABSTRACT We investigate mass ejection from accretion discs formed in mergers of black holes (BHs) and neutron stars (NSs). The third observing run of the LIGO/Virgo interferometers provided BH–NS candidate events that yielded no electromagnetic (EM) counterparts. The broad range of disc configurations expected from BH–NS mergers motivates a thorough exploration of parameter space to improve EM signal predictions. Here we conduct 27 high-resolution, axisymmetric, long-term hydrodynamic simulations of the viscous evolution of BH accretion discs that include neutrino emission/absorption effects and post-processing with a nuclear reaction network. In the absence of magnetic fields, these simulations provide a lower limit to the fraction of the initial disc mass ejected. We find a nearly linear inverse dependence of this fraction on disc compactness (BH mass over initial disc radius). The dependence is related to the fraction of the disc mass accreted before the ouflow is launched, which depends on the disc position relative to the innermost stable circular orbit. We also characterize a trend of decreasing ejected fraction and decreasing lanthanide/actinide content with increasing disc mass at fixed BH mass. This trend results from a longer time to reach weak freezout and an increasingly dominant role of neutrino absorption at higher disc masses. We estimate the radioactive luminosity from the disc outflow alone available to power kilonovae over the range of configurations studied, finding a spread of two orders of magnitude. For most of the BH–NS parameter space, the disc outflow contribution is well below the kilonova mass upper limits for GW190814.

79 ASTRONOMY AND ASTROPHYSICS↗

GeN-ROM—An OpenFOAM®-based multiphysics reduced-order modeling framework for the analysis of Molten Salt Reactors

This work presents a projection-based multiphysics Model Order Reduction (MOR) framework for the analysis of nuclear systems and its application to parametric simulations of Molten Salt Reactors (MSR). The framework, named GeN-ROM, is developed using OpenFOAM® and employs a Proper Orthogonal Decomposition aided Reduced-Basis technique (POD-RB). It can be used to reduce steady-state and transient multiphysics problems involving parametric fluid dynamics, heat exchange, and neutronics phenomena. For the treatment of structural elements in the hydraulic systems, a porous medium approach has been adopted. The reduction process is data-driven and snapshot information is extracted via POD to learn the solution manifold and to build global spatial basis functions. At the data collection phase, GeN-ROM makes use of the solvers available in GeN-Foam, a similarly OpenFOAM®-based multiphysics framework developed for the analysis of nuclear reactors. The global bases are used both to approximate the solution fields and to project the full-order equations onto lower-dimensional subspaces, thus considerably reducing the number of unknowns in a numerical system. This reduction leads to significant computational speedups, which is ideal for multi-query applications such as uncertainty quantification or design optimization. The developed tool has been tested using a 2D multiphysics model of the Molten Salt Fast Reactor (MSFR) with steady-state and transient scenarios, with speedups on the order of 10 – 10 5 .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Critical Assemblies: Dragon Burst Assembly and Solution Assemblies

This work reviews the historical literature associated with the Dragon experiment and water boiler reactors operated at Los Alamos during the Manhattan Project. Frisch’s invited talk given at the American Nuclear Society’s Fast Burst Reactor Conference held at the University of New Mexico in Albuquerque, New Mexico, in 1969 is quoted. From the literature review, basic models for the Dragon experiment and for a water boiler–type assembly (aqueous homogeneous reactor) were created that can be used for conducting multiphysics simulations for criticality excursion studies. This methodology utilizes the coupled neutronic-hydrodynamic method to perform a time-dependent dynamic simulation of a criticality excursion. MCNP® was utilized to calculate important nuclear kinetic parameters that were incorporated into the models. Simulation results compare reasonably well with historic data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Preliminary Comparison of Neutron Detector Sensitivities [Poster]

Nuclear data (ND) is vital to predictive simulations such as those completed with MCNP®. ND sensitivities are used to optimize the design of benchmark experiments. Diverse benchmarks (including neutron noise) are required to further our understanding of ND. Measured and simulated data of a 4.5-kg Pu sphere was used to calculate neutron noise parameters and associated ND Sensitivities

Nuclear Criticality Safety Program (NCSP)↗

Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition

Abstract Vibrational spectroscopy allows us to understand complex physical and chemical interactions of molecular crystals and liquids such as ammonia, which has recently emerged as a strong hydrogen fuel candidate to support a sustainable society. We report inelastic neutron scattering measurement of vibrational properties of ammonia along the solid-to-liquid phase transition with high enough resolution for direct comparisons to ab-initio simulations. Theoretical analysis reveals the essential role of nuclear quantum effects (NQEs) for correctly describing the intermolecular spectrum as well as high energy intramolecular N-H stretching modes. This is achieved by training neural network models using ab-initio path-integral molecular dynamics (PIMD) simulations, thereby encompassing large spatiotemporal trajectories required to resolve low energy dynamics while retaining NQEs. Our results not only establish the role of NQEs in ammonia but also provide general computational frameworks to study complex molecular systems with NQEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-Physics Coupled Seismic Safety Analysis of Molten-Salt Reactors

Pool-type Molten Salt Reactors (MSRs) are a promising advanced nuclear reactor concept relying on passive physical behavior to provide increased safety characteristics. The high heat capacity, high boiling point, unpressurized liquid salt contains the nuclear fuel and as it passes through the vessel achieves criticality and produces nuclear power. The salt then carries away the heat produced along with the delayed neutron precursors towards heat exchangers and primary pumps before entering the core. This forms a highly coupled multiphysics problem between neutronics and fluid flow, which makes modeling these reactors challenging. The safety/licensing case heavily relies on modeling and simulation to prove their safety, and significant effort has been expanded by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to develop the appropriate simulation tools. Their safety/licensing will require a thorough analysis of their behavior during earthquake-based transients. Earthquakes are a transient condition commonly experienced in many regions, and are safely survived by dozens of reactors every year. Nonetheless, significant conservatisms were introduced with limited predictive modeling and simulation available. The first-of-a-kind capability developed by this research will allow for engineers to analyze ranges of design-basis and beyond-design basis accident scenarios to assess the integrity of the reactor vessel and surrounding system, possibly allowing for limiting the costly conservatisms in the design. This projects uses MASTODON, Griffin, and Pronghorn in the NEAMS ecosystem to model the coupled multiphysics problem posed by an earthquake in a molten salt reactor. It marches through a number of number of coupling schemes, from uncoupled simulations to tightly two-way coupled simulations. The appropriate level of coupling for these simulations will then be determined based on the accuracy in the quantities of interest (QoI) and computational effort involved in each scheme. The QoIs chosen for this paper include the mass flow rate across the heat exchanger (for Pronghorn simulations), power output of the reactor (for Griffin simulations), and the maximum Von Mises stress (for MASTODON simulations). This summary paper reports on the current progress of this project, with 2D tightly coupled multiphysics results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Adsorption of molecular iodine and alkyl iodides from spent-nuclear-fuel-reprocessing off-gas using reduced silver mordenite

Radioactive iodine is a hazardous byproduct of spent-nuclear-fuel reprocessing that must be removed from the off-gas stream before it can be discharged. Reduced silver mordenite (Ag 0 Z) is currently the baseline material for iodine capture in the U.S. Although the performance characteristics and capture mechanisms of I 2 and CH 3 I have been established, similar investigations into long-chain organic iodides have yet to be performed. In this study, thin beds of Ag 0 Z were loaded with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I (5 ppm to 50 ppm) carried in a dry air stream at 150°C. The maximum iodine capacity was 105 ± 5 mg I/g Ag 0 Z for all species. Saturated Ag 0 Z samples were characterized using scanning electron microscopy, X-ray fluorescence, X-ray photoelectron spectroscopy, diffuse reflectance UV–visible spectroscopy, pair distribution function analysis, and thermogravimetric analysis. Further, near-complete Ag utilization and similar physical/chemical properties were observed for all samples. Through a comparison with previous studies and an investigation of aged Ag 0 Z, we propose that iodine species react with Ag + at exchange sites, forming α-AgI within the mordenite channels, and with surface Ag 0 nanoparticles, yielding β-/γ-AgI. The available Ag sites in the interior (Ag + ) and exterior (Ag 0 ) of mordenite determine the adsorption capacity since α-AgI formation is limited by the total pore volume. Potential iodine uptake routes were summarized for aging and non-aging environments. A scalable predictive model was implemented for deep-bed iodine removal, and predictions were in good agreement with experimental data. Sensitivity analysis suggests that iodine uptake kinetics is governed by pore diffusion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Demonstration of MOOSE-based Griffin reactor physics, code for heterogeneous lead-cooled fast reactor analysis

The MOOSE-based reactor physics code Griffin was assessed on a heterogeneous pin-resolved model of a prototype lead-cooled fast reactor assembly. This model was developed in preparation for future use in MOOSE-based multiphysics calculations for computing hot channel factors. Heterogeneous multigroup cross sections were prepared using the fast reactor multi-group cross section processing code MC{sup 2}-3 using a two-step method. Griffin simulations were performed using the DFEM-SN solver on 576 cores on Argonne's LCRC cluster. Diffusion-based acceleration methods were applied (NDA and CMFD). Reference solutions were generated with continuous energy MCNP and the hybrid MOC/finite element solver PROTEUS-MOC for code-to-code comparison. Space-angle convergence studies were conducted to observe convergence in k-eigenvalue and axial pin power distributions. The fully resolved Griffin calculation was within 68 pcm of the MCNP eigenvalue and exhibited max 1.2% relative error in the axial pin power distribution. Griffin produced nearly identical results to PROTEUS-MOC when using the same 9-group multigroup cross-section set. Griffin demonstrated favorable scaling in wall-clock time and memory usage when using diffusion-based acceleration methods. Griffin is capable of simulating the pin-resolved heterogeneous LFR assembly with good accuracy and performance, and is suitable for future use in coupled high-fidelity hot channel factor simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Nuclear data uncertainty quantification for the nuclide inventory of a Calvert Cliffs spent fuel sample

The impact of nuclear data cross section uncertainties and covariance matrices on the nuclide vector of spent nuclear fuel was investigated; This exercise was carried out for the Calvert Cliffs fuel assembly D047 benchmark available in the SFCOMPO database. Sample P irradiated in rod MKP109 for 4 cycles up to a burnup of approximately 44 GWd/MTU was selected for the analysis. Nuclear data uncertainties were taken from the most recent libraries released by evaluation projects JEFF, ENDF/B and JENDL, and were propagated using the SANDY code via a stochastic sampling approach. This paper provides a quantification of the uncertainty on the concentration of several actinides and fission products relevant for spent fuel management. Uncertainties generally below 5 % were predicted for the concentrations of most of the uranium, neptunium and plutonium isotopes relevant for SNF applications. Curium isotopes carry larger uncertainties that might exceed 10 %. The contribution of cross section uncertainties on the concentrations of fission products was found to be marginal with the exception of a few nuclides. These results can be significantly affected by the lack of evaluated covariance matrices for the capture cross section of several fission products. Burnup tracers such as {sup 148}Nd and {sup 137}Cs have negligible uncertainties because of the power normalisation imposed in every stochastic calculation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparison of Measured Leakage Current Distributions with Calculated Damage Energy Distributions in HgCdTe

This paper presents a combined Monte Carlo and analytic approach to the calculation of the pixel-to-pixel distribution of proton-induced damage in a HgCdTe sensor array and compares the results to measured dark current distributions after damage by 63 MeV protons. The moments of the Coulombic, nuclear elastic and nuclear inelastic damage distribution were extracted from Monte Carlo simulations and combined to form a damage distribution using the analytic techniques first described in [I]. The calculations show that the high energy recoils from the nuclear inelastic reactions (calculated using the Monte Car10 code MCNPX [2]) produce a pronounced skewing of the damage energy distribution. The nuclear elastic component (also calculated using the MCNPX) has a negligible effect on the shape of the damage distribution. The Coulombic contribution was calculated using MRED [3,4], a Geant4 [4,5] application. The comparison with the dark current distribution strongly suggests that mechanisms which are not linearly correlated with nonionizing damage produced according to collision kinematics are responsible for the observed dark current increases. This has important implications for the process of predicting the on-orbit dark current response of the HgCdTe sensor array.

Marshall, C. J.↗

Comparison of Measured Dark Current Distributions with Calculated Damage Energy Distributions in HgCdTe

This paper presents a combined Monte Carlo and analytic approach to the calculation of the pixel-to-pixel distribution of proton-induced damage in a HgCdTe sensor array and compares the results to measured dark current distributions after damage by 63 MeV protons. The moments of the Coulombic, nuclear elastic and nuclear inelastic damage distributions were extracted from Monte Carlo simulations and combined to form a damage distribution using the analytic techniques first described in [1]. The calculations show that the high energy recoils from the nuclear inelastic reactions (calculated using the Monte Carlo code MCNPX [2]) produce a pronounced skewing of the damage energy distribution. While the nuclear elastic component (also calculated using the MCNPX) contributes only a small fraction of the total nonionizing damage energy, its inclusion in the shape of the damage across the array is significant. The Coulombic contribution was calculated using MRED [3-5], a Geant4 [4,6] application. The comparison with the dark current distribution strongly suggests that mechanisms which are not linearly correlated with nonionizing damage produced according to collision kinematics are responsible for the observed dark current increases. This has important implications for the process of predicting the on-orbit dark current response of the HgCdTe sensor array.

Marshall, C. J.↗

Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model

Quantum simulations offer the potential to predict the structure and dynamics of nuclear many-body systems that are beyond the capabilities of classical computing. Generally, preparing the ground state of strongly-interacting many-body systems relevant to nuclear physics is however inefficient, even using ideal quantum computers. In addition, currently available NISQ-era quantum devices possess modest numbers of qubits, limiting the size of quantum many-body systems that can be simulated. In this context, a reformulation of the quantum many-body problems using truncated model spaces and Hamiltonians is desirable to make them more amenable to near-term quantum computers. The importance of symmetries in low-energy theories, including effective field theories (EFTs), lattice quantum chromodynamics (QCD), and effective model spaces for nuclear systems, in particular their interplay with the reduction of active Hilbert spaces, is well known. Lesser known is the fact that the non-commutivity of some symmetries and truncations of the model space can be profitably combined with variational calculations to rearrange the entanglement into localized structures and enable more efficient simulations. Here, the goal of the present study is to explore and utilize the non-commutivity of symmetries and model-space truncations of quantum many-body systems important to nuclear physics, particularly in combination with variational algorithms for quantum simulations and effective Hamiltonian learning. We introduce an iterative hybrid classical-quantum algorithm, Hamiltonian learning variational quantum eigensolver (HL-VQE), that simultaneously optimizes an effective Hamiltonian, thereby rearranging entanglement into the effective model space, and the associated ground-state wavefunction. Quantum simulations, using classical computers and IBM's superconducting-qubit quantum computers, are performed to demonstrate the HL-VQE algorithm, in the context of the Lipkin-Meshkov-Glick (LMG) model of interacting fermions, where the Hamiltonian transformation corresponds to an orbital rotation. We use a mapping where the number of qubits scales with the $\log$ of the size of the effective model space, rather than the particle number. HL-VQE is found to provide an exponential improvement in LMG-model calculations of the ground-state energy and wavefunction, compared to naive truncations without Hamiltonian learning, throughout a significant fraction of the Hilbert space. In the context of EFT, this corresponds to counterterms scaling exponentially with the cut-off as opposed to power law. Implementations on IBM's QExperience quantum computers and simulators for 1- and 2-qubit effective model spaces are shown to provide accurate and precise results, reproducing classical predictions. For a range of parameters defining the LMG model, the HL-VQE algorithm is found to have better scaling of quantum resources requirements than previously explored algorithms. In particular, the HL-VQE scales efficiently over a large fraction of the model space, in contrast to VQE alone. This work constitutes a step in the development of entanglement-driven quantum algorithms for descriptions of nuclear many-body systems. This, in part, leverages the potential of noisy intermediate-scale quantum (NISQ) devices. The exponential scaling of counterterms observed in this study suggests the possibility of more general applicability to other non-perturbative EFTs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cerberus and the Zeus Suite of Critical Experiment Benchmarks [Slides]

This presentation finds that as it was designed, Cerberus is extremely sensitive to copper nuclear data. Just changing copper nuclear data to another library can swing simulated keff by >1000 pcm. ENDF/B-VIII.1 and JENDL-5.0 both show large downward trends in keff as copper interstitial thickness is increased

ENDF/B-VIII.1↗

MOSAIC: An Effective FFT-based Numerical Method to Assess Aging Properties of Concrete

As the nuclear fleet in the United States ages and subsequent license renewal applications grow, the prediction of concrete durability at extended operation becomes more important. To address this issue, a Fast-Fourier Transform (FFT) method is utilized to simulate aging-related degradation of concrete within the Microstructure Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) software. MOSAIC utilizes compositional phase maps to simulate damage from radiation-induced volumetric expansion (RIVE), applied force, creep, and thermal expansion. This compositional detail allows each mineral in the microstructure to be assigned specific material properties, allowing the simulation to be as accurate and representative as possible. The principal goal of MOSAIC is to simulate the effects of nonlinear aging mechanisms occurring in nuclear concrete on the macroscopic mechanical properties, using only the aggregate microstructure compositional information as a starting point. Here, several realistic example simulations are shown to demonstrate the utility and uniqueness of the MOSAIC software.

36 MATERIALS SCIENCE↗

Mesoscale modelling of dynamic porosity in cement hydrate gel during a water sorption cycle: A lattice Boltzmann study

We describe a lattice Boltzmann modelling framework for fluid sorption coupled to a dynamic model of cement hydrate microstructure upon which it is possible to explore ideas of water sorption in cement emergent from NMR and other recent experimental studies. The results of the first simulations using the model are presented. We show that it is possible to extract transport and microstructural relaxation parameters from the simulations that are in good qualitative agreement with experiment. We discuss limitations of the methodology.

36 MATERIALS SCIENCE↗

In-Situ Transmission Electron Microscopy Study of the Evolution of Extended Defects in Oxide Nuclear Fuels

In-situ transmission electron microscopy (TEM) with simulated extreme environments is an effective tool for understanding and tracking microstructural changes down to the atomic scale. The objective of this research is to study the effect of temperature on the evolution of extended defects in ThO2 and UO2. Here, we present in-situ TEM isochronal thermal annealing experiments using a micro-electro-mechanical-system (MEMS)-based heating holder. ThO2 and UO2 single crystal specimens were grown inside an inert silver ampoule using hydrothermal synthesis. Both samples were irradiated using 2 MeV protons at 600oC up to 0.1 dpa at Texas A&M University’s Accelerator Laboratory. Fig. 1a shows a weak-beam dark field TEM image of ThO2 after irradiation, indicating the presence of faulted 1/3 <111> type dislocation loops. This presentation will discuss the effect of annealing temperature (600oC, 800oC, 1000oC, 1100oC, etc.) on dislocation loop density, size and distribution, loop nature (interstitial/vacancies) and Burgers vector, as well as the formation of voids in both ThO2 and UO2. This work will also discuss the interaction between defects during annealing. The in-situ TEM annealing cycle is shown in Fig 1b. This research significantly improves the understanding of defect behavior in oxide nuclear fuels with temperature and will aid computational modeling efforts. This work was supported as part of the Center for Thermal Energy Transport under Irradiation (TETI) Energy Frontier Research Center, funded by the U.S. Department of Energy Office of Science.

36 MATERIALS SCIENCE↗

DL_POLY Quantum 2.0: A modular general-purpose software for advanced path integral simulations

DL_POLY Quantum 2.0, a vastly expanded software based on DL_POLY Classic 1.10, is a highly parallelized computational suite written in FORTRAN77 with a modular structure for incorporating nuclear quantum effects into large-scale/long-time molecular dynamics simulations. This is achieved by presenting users with a wide selection of state-of-the-art dynamics methods that utilize the isomorphism between a classical ring polymer and Feynman’s path integral formalism of quantum mechanics. Here, the flexible and user-friendly input/output handling system allows the control of methodology, integration schemes, and thermostatting. DL_POLY Quantum is equipped with a module specifically assigned for calculating correlation functions and printing out the values for sought-after quantities, such as dipole moments and center-of-mass velocities, with packaged tools for calculating infrared absorption spectra and diffusion coefficients.

36 MATERIALS SCIENCE↗