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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Entanglement and many-body effects in collective neutrino oscillations

Collective neutrino oscillations play a crucial role in transporting lepton flavor in astrophysical settings, such as supernovae, where the neutrino density is large. In this regime, neutrino-neutrino interactions are important and simulations in the mean-field approximation show evidence for collective oscillations occurring at timescales much shorter than those associated with vacuum oscillations. In this work, we study the out-of-equilibrium dynamics of a corresponding spin model using matrix product states and show how collective bipolar oscillations can be triggered by many-body correlations if appropriate initial conditions are present. We find entanglement entropies scaling at most logarithmically in the system size suggesting that classical tensor network methods could be efficient in describing collective neutrino dynamics more generally. These observation provide a clear path forward, not only to increase the accuracy of current simulations, but also to elucidate the mechanism behind collective flavor oscillations without resorting to the mean-field approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Steel Corrosion Impacts on Radionuclide Immobilization

This progress report (Level 4 Milestone Number M4SF-21LL010302052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline Activity Number SF-21LL01030205. The research is focused on actinide and radionuclide sequestration in steel corrosion products. Fuel matrix degradation models suggest that the near field is likely to be reducing at the time of canister breaching, steel corrosion, and radionuclide release, but more oxidizing conditions may prevail in the far field. The incorporation of radionuclides into corrosion phases may limit the rate of radionuclide release by sequestering a portion of the radionuclide source term. For these reasons there is a need to evaluate the incorporation of Pu and other radionuclides into various Fe-oxide phases, and to understand the behavior of coprecipitated phases during mineral recrystallization processes and during re-oxidation events. Radionuclide coprecipitation with Fe minerals may impact long-term repository performance and is an ongoing research focus at Lawrence Livermore National Laboratory.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Improved quantum algorithms for linear and nonlinear differential equations

We present substantially generalized and improved quantum algorithms over prior work for inhomogeneous linear and nonlinear ordinary differential equations (ODE). Specifically, we show how the norm of the matrix exponential characterizes the run time of quantum algorithms for linear ODEs opening the door to an application to a wider class of linear and nonlinear ODEs. In [1], a quantum algorithm for a certain class of linear ODEs is given, where the matrix involved needs to be diagonalizable. The quantum algorithm for linear ODEs presented here extends to many classes of non-diagonalizable matrices including singular matrices. The algorithm here is also exponentially faster than the bounds derived in [1] for certain classes of diagonalizable matrices. Our linear ODE algorithm is then applied to nonlinear differential equations using Carleman linearization (an approach taken recently by us in [2]). The improvement over that result is two-fold. First, we obtain an exponentially better dependence on error. This kind of logarithmic dependence on error has also been achieved by [3], but only for homogeneous nonlinear equations. Second, the present algorithm can handle any sparse matrix (that models dissipation) if it has a negative log-norm (including non-diagonalizable matrices), whereas [2] and [3] additionally require normality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electrochemical Corrosion of SIMFUEL: Effects of dissolved H2 and noble metal particles

This report describes the results from electrochemical corrosion tests that were conducted using simulated spent fuel (SIMFUEL) materials comprised of UO2 and surrogate fission products. Two SIMFUEL compositions were tested to quantify the effect of noble metal inclusions and dissolved H2 on the UO2 dissolution rate. One material consisted of UO2 with added lanthanide oxides (UO2 N) and the other consisted of UO2 with added lanthanide oxides and noble metals (UO2-H) at concentrations to simulate high burnup fuel. The electrochemical corrosion tests on the SIMFUEL materials were conducted in aqueous electrolyte solutions (pH 10) that were either saturated with air or purged with a H2/Ar gas mixture to maintain a constant dissolved H2 concentration. The results from electrochemical corrosion tests on SIMFUEL can be applied to qualitatively understand and also quantify the separate effects of water chemistry and fuel composition on the degradation behavior of the UO2 matrix. Open circuit potential (OCP) measurements on a SIMFUEL material of known composition (i.e., known fraction of NMPs at the fuel surface) immersed in a known solution chemistry (i.e., pH, Eh, [O2], [H2]) at known temperature provide qualitative insight into the degradation behavior of the UO2 matrix. If the OCP is above the threshold potential at which the oxidative dissolution of U(IV) to U(VI) occurs, the SNF is expected to degrade by oxidative processes under the experimental conditions. The net currents that are measured during potentiostatic tests, during which the surface potential of the SIMFUEL material is fixed by a potentiostat, can be used to quantify the UO2 degradation rate and optimize the rate constant values used in the Fuel Matrix Degradation Model (FMDM) for half reactions that occur on the SNF surface. Specifically, electrochemical measurements enable the estimation of the total anodic current at ECORR–which is the surface potential at which the total anodic and total cathodic currents are equal–so that the rate constant values for key reactions can be calculated. The open circuit potential measurements, potentiostatic tests, surface property measurements (scanning electron microscopy images and electrochemical impedence spectroscopy plots), and solution elemental composition analyses are being performed to update and optimize the FMDM. A case study is presented herein to show how electrochemical corrosion test results and accompanying characterization results for the UO2 N material in air-saturated solution can be used to validate the SNF surface reaction module of the FMDM. Future electrochemical tests will be conducted to provide quantitative information on the effects of NM content (burnup), H2 concentration, water chemistry, temperature, and galvanic couples with cladding and EBS alloys on UO2 degradation that can be used to improve the accuracy and functionality of the FMDM.

Thomas, Sara↗
DOE OSTI2024

A mean field homogenization model for the mechanical response of ceramic matrix composites

SiC/SiC composites offer exceptional mechanical stability at high temperatures and under irradiation. These ceramic matrix composites are therefore strong candidate materials for future nuclear energy applications. Their mechanical response, which exhibits pseudo-plasticity, is mediated by matrix cracking, fiber debonding, and fiber pull-out due to slip. Here, this study introduces a mechanistic model for the behavior of unidirectionally reinforced SiC/SiC composites. Specifically a mean field homogenization approach is proposed to account for all deformation and degradation modes during mechanical deformation. The homogenization scheme relies on a Mori Tanaka method that is extended to consider the effects of the coating’s elasto-plastic response on the development of micromechanical fields. Further, the model proposed introduces a method to effectively account for the role of localized damage (i.e., cracks) on mechanical fields within both the fiber and the matrix. Upon validating the model against experimental data, the roles of interface sliding, coating dimensions and intrinsic elastic response, as well as of microstructure (e.g. porosity, fiber volume fraction) are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Nuclear matrix elements from lattice QCD for electroweak and beyond-Standard-Model processes

Over the last decade, numerical solutions of Quantum Chromodynamics (QCD) using the technique of lattice QCD have developed to a point where they are beginning to connect fundamental aspects of nuclear physics to the underlying degrees of freedom of the Standard Model. In this review, the progress of lattice QCD studies of nuclear matrix elements of electroweak currents and beyond-Standard-Model operators is summarized, and connections with effective field theories and nuclear models are outlined. Lattice QCD calculations of nuclear matrix elements can provide guidance for low-energy nuclear reactions in astrophysics, dark matter direct detection experiments, and experimental searches for violations of the symmetries of the Standard Model, including searches for additional CP violation in the hadronic and leptonic sectors, baryon-number violation, and lepton-number or flavor violation. Similarly, important inputs to neutrino experiments seeking to determine the neutrino-mass hierarchy and oscillation parameters, as well as other electroweak and beyond-Standard-Model processes can be determined. As a result, the phenomenological implications of existing studies of electroweak and beyond-Standard-Model matrix elements in light nuclear systems are discussed, and future prospects for the field toward precision studies of these matrix elements are outlined.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Phase-Field Modeling of Damage Evolution in Ceramic Matrix Composite (CMC) and Environmental Barrier Coating (EBC)

Ceramic matrix composites (CMCs) protected by environmental barrier coatings (EBCs) present a promising materials solution for next generation gas turbines. Developments of more robust and efficient EBCs and mechanically tougher CMCs are thus of significant technological importance. Here we develop a phase-field modeling framework that incorporates the thermally grown oxide (TGO), recognized as a critical factor for degradation and failure of EBCs. We simulate crack growth in the TGO and the potential extension into the bond coat / CMC substrate. The model efficiently takes account of the large inelastic deformation induced by the severe volume expansion of TGO, thanks to our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm. A phase-field model is built for damage evolution in CMCs including crack growth and interfacial sliding. The effects of fiber layout and interfacial sliding on the macroscopic toughness of CMCs are revealed by large-scale simulations and compared to experiments.

advanced energy systems and materials↗
DOE OSTI2024

SAGA1 and MITH1 produce matrix-traversing membranes in the CO2-fixing pyrenoid

Abstract Approximately one-third of global CO 2 assimilation is performed by the pyrenoid, a liquid-like organelle found in most algae and some plants. Specialized pyrenoid-traversing membranes are hypothesized to drive CO 2 assimilation in the pyrenoid by delivering concentrated CO 2 , but how these membranes are made to traverse the pyrenoid matrix remains unknown. Here we show that proteins SAGA1 and MITH1 cause membranes to traverse the pyrenoid matrix in the model alga Chlamydomonas reinhardtii . Mutants deficient in SAGA1 or MITH1 lack matrix-traversing membranes and exhibit growth defects under CO 2 -limiting conditions. Expression of SAGA1 and MITH1 together in a heterologous system, the model plant Arabidopsis thaliana , produces matrix-traversing membranes. Both proteins localize to matrix-traversing membranes. SAGA1 binds to the major matrix component, Rubisco, and is necessary to initiate matrix-traversing membranes. MITH1 binds to SAGA1 and is necessary for extension of membranes through the matrix. Our data suggest that SAGA1 and MITH1 cause membranes to traverse the matrix by creating an adhesive interaction between the membrane and matrix. Our study identifies and characterizes key factors in the biogenesis of pyrenoid matrix-traversing membranes, demonstrates the importance of these membranes to pyrenoid function and marks a key milestone toward pyrenoid engineering into crops for improving yields.

Hennacy, Jessica H.↗
DOE OSTI2023

Bayesian Monte Carlo Evaluation of Imperfect (n, 233 U) Data and Model

Conventional nuclear data evaluation methods using generalized linear least squares make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate to minimize the cost function (even for nonlinear models); the model (e.g., of neutron cross section) and experimental data (including covariance data) are without defect and prior PDFs of parameters and measured data are known perfectly. Neglect of covariance between model parameters and measured data in conventional evaluations contributes to imperfections. These assumptions are inherent to the generalized linear least squares minimization method commonly used for resolved resonance region neutron cross section evaluations but are often not justified due to the presence of non-normal PDFs, nonlinear models (e.g., R-matrix formalism), and inherent imperfections in data and models (e.g., imperfect covariance data). Here, these assumptions are removed in a mathematical framework of Bayes’ theorem, which is implemented using the Metropolis-Hastings Monte Carlo method. Most importantly, new parameters are introduced to parameterize discrepancies between the theoretical model and measured data to quantify judgement about discrepancies or imperfections in a reproducible manner. An evaluation of 233U in the eV region using the ENDF-B/VIII.0 library and transmission data (Guber et al.) is presented, and posterior parameters are compared to those obtained by conventional evaluation methods. This example illustrates the effects of removing the most harmful assumption: that of model-data perfection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Present Status of Nuclear Shell-Model Calculations of 0 νββ Decay Matrix Elements

Neutrinoless double beta (0νββ) decay searches are currently among the major foci of experimental physics. The observation of such a decay will have important implications in our understanding of the intrinsic nature of neutrinos and shed light on the limitations of the Standard Model. The rate of this process depends on both the unknown neutrino effective mass and the nuclear matrix element (M 0ν ) associated with the given 0νββ transition. The latter can only be provided by theoretical calculations, hence the need of accurate theoretical predictions of M 0ν for the success of the experimental programs. This need drives the theoretical nuclear physics community to provide the most reliable calculations of M 0ν . Among the various computational models adopted to solve the many-body nuclear problem, the shell model is widely considered as the basic framework of the microscopic description of the nucleus. Here, we review the most recent and advanced shell-model calculations of M 0ν considering the light-neutrino-exchange channel for nuclei of experimental interest. We report the sensitivity of the theoretical calculations with respect to variations in the model spaces and the shell-model nuclear Hamiltonians.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Small Angle Scattering Data Analysis Assisted by Machine Learning Methods

Small angle scattering (SAS) is a widely used technique for characterizing structures of wide ranges of materials. For such wide ranges of applications of SAS, there exist a large number of ways to model the scattering data. While such analysis models are often available from various suites of SAS data analysis software packages, selecting the right model to start with poses a big challenge for beginners to SAS data analysis. Here, we present machine learning (ML) methods that can assist users by suggesting scattering models for data analysis. A series of one-dimensional scattering curves have been generated by using different models to train the algorithms. The performance of the ML method is studied for various types of ML algorithms, resolution of the dataset, and the number of the dataset. The degree of similarities among selected scattering models is presented in terms of the confusion matrix. The scattering model suggestions with prediction scores provide a list of scattering models that are likely to succeed. Therefore, if implemented with extensive libraries of scattering models, this method can speed up the data analysis workflow by reducing search spaces for appropriate scattering models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Bayesian Monte Carlo Evaluation Framework for Imperfect Data and Models [Abstract]

Nuclear data evaluation methods conventionally make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate for minimization of a cost function (even for non-linear models); and that both the model (of, e.g., neutron cross section) and experimental data (including their covariance data) are perfect. These assumptions are inherent to the well-known generalized linear least squares (GLLS) minimization method commonly used for evaluations of resolved resonance region (RRR) neutron cross sections. However, these assumptions are often not justified due to the presence of non-normal PDFs, non-linear models (e.g. R -matrix formalism), and inherent imperfections in data and models (e.g. discrepant data sets, discrepancies between the previous evaluation and newly measured data, or imperfect covariance data). We remove the said assumptions in a mathematical framework of Bayes’ theorem, and implement it using the Metropolis-Hastings Monte Carlo method. Parameters of a new kind are introduced to parameterize inherent imperfections, e.g. , any discrepancies between the theoretical model and measured data. These new parameters enable evaluators to quantify their expert judgement about any discrepancies or imperfections in a reproducible manner. We demonstrate the framework with an ongoing evaluation of 233 U in the eV region using the ENDF-B/VIII library and transmission data measured by Guber, et al. , and compare the posterior parameters to those obtained by conventional evaluation methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Surrogate Model Development of Spent Fuel Degradation for Repository Performance Assessment

In model simulations of deep geologic repositories, UO 2 fuel matrix degradation typically begins as soon as the waste package breaches and groundwater contacts the fuel surface. The initial degradation rate depends on the timing of these events, burnup of the fuel, temperature, and concentrations of dissolved reactants. Estimating the initial rate of degradation is fairly straightforward, but as UO 2 corrosion products precipitate on the fuel surface and the movement of dissolved species between the fuel surface and environment is impeded by the precipitated solids, the rate is more difficult to quantify. At that point, calculating the degradation rate becomes a reactive-transport problem in which a large number of equations must be solved by iteration for a large number of grid cells at each time step. The consequence is that repository simulations, which are already expensive, become much more expensive, especially when hundreds or thousands of waste packages breach. The Fuel Matrix Degradation (FMD) model is the process model of the Spent Fuel and Waste Science and Technology (SFWST) campaign of the US Department of Energy (DOE). It calculates spent fuel degradation rates as a function of radiolysis, redox reactions, electrochemical reactions, alteration layer growth, and diffusion of reactants through the alteration layer. Like other similar fuel degradation process models, it is a complicated model requiring a large number of calculations and iterations at each time step.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Modeling Workloads of a Linear Electromagnetic Code for Load Balancing Matrix Assembly

This report presents our work to model the workloads of a linear electromagnetic application based on the method of moments in the frequency domain to effectively load balance the matrix assembly. This application is particularly challenging to load balance due to its lack of persistent iterative behavior, its operation under tight memory constraint (where the matrix may fill 80% of memory on each node), and the algorithmic complexity of the computational method. This report describes the first step in our work to apply an inspector-executor approach for load balancing workloads where key parameters are exposed during the inspector phase and a pre-trained model is applied to predict relative task weights for the load balancer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Investigation of Coupled Processes in Fractures and the Bordering Matrix via a Micro‐Continuum Reactive Transport Model

Abstract In multi‐mineral fractured rocks, the altered porous layer on the fracture surface resulting from preferential dissolution of the fast‐reacting minerals can have profound impacts on subsequent chemical‐physical alteration of the fractures. This study adopts the micro‐continuum approach to provide further understanding of reactive transport processes in the altered layer (AL), and mass exchanges with the bordering matrix and fracture. The modeling framework couples the Darcy‐Brinkman‐Stokes (DBS) solver in COMSOL Multiphysics and the geochemical modeling capability of CrunchFlow. Three‐dimensional steady state simulations with systematically varied chemical‐physical parameters of the AL were performed to examine the impacts of individual factors and processes. Our simulation results confirm previous observations that dissolution of the fast‐reacting mineral (i.e., calcite) is largely controlled by diffusion across the AL. We also show that dissolution of the slow‐reacting mineral (i.e., dolomite), which controls AL development and fracture enlargement, increases with surface area and has a complex dependence on different local rate‐limiting processes. In particular, advection can result in evident spatial variations in the local dissolution rates of dolomite, although it does not affect the bulk chemistry significantly. The difference in the spatial patterns between simulations with and without advection in the AL is more noticeable in the locations with smaller apertures, with up to 20% difference in local reaction rates. Therefore, it is important to include a full depiction of advection, diffusion, and reactions for accurately capturing local dynamics that control long‐term fracture evolution.

58 GEOSCIENCES↗
DOE OSTI2020

Predicting ductility of Mg/SiCp nanocomposite under multiaxial loading conditions based on unit cell modeling

This article presents an investigation on the ductility of Mg/SiCp under nine different multiaxial loading conditions based on a unit cell (or called representative volumetric element, RVE) finite element model. The constitutive relationship of magnesium matrix is characterized by a model combined Lode angle dependent plasticity model with the CPB06 plasticity model, which is able to describe the tension-compression asymmetry in magnesium matrix. The debonding of the matrix-particle interface and matrix fracture are considered by the modified Mohr-Coulomb (MMC) fracture model. Simulation results show that the interface debonding and subsequent matrix fracture are responsible for the ductility and fracture of nanocomposite. The computational results with parametric studies are compared and well correlated with experimental data, and it finally gives a stress-based full fracture locus of Mg/SiCp nanocomposite.

42 ENGINEERING↗