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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Random-matrix approach to the statistical compound nuclear reaction at low energies using the Monte-Carlo technique [PowerPoint]

This theoretical treatment of low-energy compound nucleus reactions begins with the Bohr hypothesis, with corrections, and various statistical theories. The author investigates the statistical properties of the scattering matrix containing a Gaussian Orthogonal Ensemble (GOE) Hamiltonian in the propagator. The following conclusions are reached: For all parameter values studied, the numerical average of MC-generated cross sections coincides with the result of the Verbaarschot, Weidenmueller, Zirnbauer triple-integral formula. Energy average and ensemble average agree reasonably well when the width I is one or two orders of magnitude larger than the average resonance spacing d. In the strong-absorption limit, the channel degree-of-freedom ν a is 2. The direct reaction increases the inelastic cross sections while the elastic cross section is reduced.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Chemical Composition Analysis and Product Consistency Test to Support Enhanced Hanford Waste Glass Models: Results for the Second Set of High Alumina Outer Layer Matrix Glasses

In this report, the Savannah River National Laboratory provides chemical analyses and Product Consistency Test (PCT) results for 16 simulated high level waste glasses fabricated by the Pacific Northwest National Laboratory. The results of these analyses will be used as part of efforts to revise or extend the validation regions of the current Hanford Waste Treatment and Immobilization Plant glass property models to cover a broader span of waste compositions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Toward a Visualization-Supported Workflow for Cyber Alert Management using Threat Models and Human-Centered Design

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated tool support in the effort to make their tasks more efficient, accurate, and timely. This tool support comes in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, often speak of a need for tools which help them merge the data they already have and help them establish appropriate baselines against which to compare potential anomalies. Furthermore, existing threat models that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand they analytic process and how one such model, the MITRE ATT&CK Matrix [32], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into the threat model to inform our eventual visualization designs. We examine data mapping for gaps where the threat model is under-supported by either data or tools. We discuss these gaps as potential design spaces for future research efforts. We also discuss the design of a prototype tool that combines machine-learning and visualization components to support cyber analysts working with this threat model.

Cyber Security↗
DOE OSTI2024

Quantum chaos on edge

Recently, the physics of many-body quantum chaotic systems close to their ground states has come under intensified scrutiny. Such studies are motivated by the emergence of model systems exhibiting chaotic fluctuations throughout the entire spectrum [the Sachdev-Ye-Kitaev (SYK) model being a renowned representative] as well as by the physics of holographic principles, which likewise unfold close to ground states. Interpreting the edge of the spectrum as a quantum critical point, here we combine a wide range of analytical and numerical methods to the identification and comprehensive description of two different universality classes: the near edge physics of “sparse” and the near edge of “dense” chaotic systems. The distinction lies in the ratio between the number of a system's random parameters and its Hilbert space dimension, which is exponentially small or algebraically small in the sparse and dense case, respectively. Notable representatives of the two classes are generic chaotic many-body models (sparse) and invariant random matrix ensembles or chaotic gravitational systems (dense). While the two families share identical spectral correlations at energy scales comparable to the level spacing, the density of states and its fluctuations near the edge are different. Considering the SYK model as a representative of the sparse class, we apply a combination of field theory and exact diagonalization to a detailed discussion of its edge spectrum. Conversely, Jackiw-Teitelboim gravity is our reference model for the dense class, where an analysis of the gravitational path integral and random matrix theory reveal universal differences to the sparse class, whose implications for the construction of holographic principles we discuss. Published by the American Physical Society 2024

Altland, Alexander (ORCID:0000000229914805)↗
DOE OSTI2022

Hybrid quantum-classical simulations of magic angle spinning dynamic nuclear polarization in very large spin systems

Solid-state nuclear magnetic resonance can be enhanced using unpaired electron spins with a method known as dynamic nuclear polarization (DNP). Fundamentally, DNP involves ensembles of thousands of spins, a scale that is difficult to match computationally. This scale prevents us from gaining a complete understanding of the spin dynamics and applying simulations to design sample formulations. We recently developed an ab initio model capable of calculating DNP enhancements in systems of up to ~1000 nuclei; however, this scale is insufficient to accurately simulate the dependence of DNP enhancements on radical concentration or magic angle spinning (MAS) frequency. We build on this work by using ab initio simulations to train a hybrid model that makes use of a rate matrix to treat nuclear spin diffusion. We show that this model can reproduce the MAS rate and concentration dependence of DNP enhancements and build-up time constants. Finally, we then apply it to predict the DNP enhancements in core–shell metal-organic-framework nanoparticles and reveal new insights into the composition of the particles’ shells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed algorithm is effective for lung lobe segmentation in absence of auxiliary structures such as vessels and airways. The most challenging cases are those with mostly incomplete, absent, or near-absent fissures and in cases with poorly revealed fissures due to high image noise. However, the authors observe good performance even in the majority of these cases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to develop code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neural network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Twisted bilayer graphene. I. Matrix elements, approximations, perturbation theory, and a k · p two-band model

We investigate the twisted bilayer graphene (TBG) model of Bistritzer and MacDonald (BM) [Bistritzer and MacDonald, Proc. Natl. Acad. Sci. 108, 12233 (2011)] to obtain an analytic understanding of its energetics and wave functions needed for many-body calculations. We provide an approximation scheme for the wave functions of the BM model, which first elucidates why the BM K M -point centered original calculation containing only four plane waves provides a good analytical value for the first magic angle (θ M ≈ 1°). The approximation scheme also elucidates why most of the many-body matrix elements in the Coulomb Hamiltonian projected to the active bands can be neglected. By applying our approximation scheme at the first magic angle to a Γ M -point centered model of six plane waves, we analytically understand the reason for the small Γ M -point gap between the active and passive bands in the isotropic limit w 0 = w 1 . Furthermore, we analytically calculate the group velocities of the passive bands in the isotropic limit, and show that they are almost doubly degenerate, even away from the Γ M point, where no symmetry forces them to be. Furthermore, moving away from the Γ M and K M points, we provide an explicit analytical perturbative understanding as to why the TBG bands are flat at the first magic angle, despite the first magic angle is defined by only requiring a vanishing K M -point Dirac velocity. We derive analytically a connected “magic manifold” w 1 = $2\sqrt{1 + w^{2}_{0}}$ $-\sqrt{2 + 3w^2_0}$, on which the bands remain extremely flat as w 0 is tuned between the isotropic (w 0 = w 1 ) and chiral (w 0 = 0) limits. We analytically show why going away from the isotropic limit by making w 0 less (but not larger) than w 1 increases the Γ M -point gap between the active and the passive bands. Finally, by perturbation theory, we provide an analytic Γ M point k ∙ p two-band model that reproduces the TBG band structure and eigenstates within a certain w 0 , w 1 parameter range. Further refinement of this model are discussed, which suggest a possible faithful representation of the TBG bands by a two-band Γ M point k ∙ p model in the full w 0 , w 1 parameter range.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A windowed mean trajectory approximation for condensed phase dynamics

We propose a trajectory-based quasi-classical method for approximating dynamics in condensed phase systems. Building upon the previously developed optimized mean trajectory approximation that has been used to compute linear and nonlinear spectra, we borrow some ideas from filtering trajectory methods to obtain a novel semiclassical method for the dynamical propagation of density matrices. This new approximation is tested rigorously against standard multistate electronic models, spin-boson models, and models of the Fenna–Matthews–Olson complex. For dissipative systems, the current method is significantly better or as good as many other semiclassical methods available, especially at low temperatures and for off-diagonal density matrix elements, whereas for scattering models, the current method bears similar limitations as mean-field propagation schemes. All results are tested against the numerically exact hierarchical equations of motion method. In conclusion, the new method shows excellent agreement across various parameter regimes with numerically exact results, highlighting the robustness and accuracy of our approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

From IEC 61853 power measurements to PV system simulations.

The IEC 61853 PV module energy rating standard requires measuring module power (and hence efficiency) over a matrix of irradiance and temperature conditions. These matrix points represent nearly the full range of operating conditions encountered in the field in all but the most extreme locations, and create an opportunity to develop alternative approaches to existing modelssuch as the single-diode models and the Sandia Array Performance Modelfor calculating system performance. This report begins by discussing the bilinear interpolation and extrapolation method from IEC 61853-3, and then describes four existing model-based methods that could be used with matrix measurements. Then a new model is developed and all options are compared according to seven objective criteria using the matrix measurements of four PV modules of different technologies. The results show that the new model is an excellent candidate for launching power matrix-based PV system simulations.

14 SOLAR ENERGY↗
DOE OSTI2025

Oklo Sponsored Testing using PELICAN: System, Subchannel, and High-Fidelity Software Validation (Final CRADA Report)

Argonne National Laboratory (the Contractor), located in Lemont IL, and Oklo, Inc., (the Participant), headquartered in Santa Clara, CA, propose to enter into a Cooperative Research and Development Agreement (CRADA) to perform a gap analysis of thermal hydraulic data, perform prototypical fuel assembly pressure drop and cavitation model validation, generate the experimental data as well as the corresponding uncertainties for this matrix and, finally, develop the validation models with the Argonne system level code SAS4A/SASSYS-1, the Argonne subchannel analysis code DASSH, the Argonne high fidelity code Nek5000, and/or the Idaho National Laboratory code Pronghorn Subchannel. The work outlined below will significantly improve the experimental and validation database currently available for liquid metal fast reactors, thus making it a viable part of a comprehensive reactor design and licensing suite to be used by the participant.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Hierarchical Membrane Dynamics in Phase-Separated Model Membranes

Lipid membranes, the primary matrix of cell membranes, exhibit a hierarchy of dynamics from molecular motions to collective undulations, which control spatiotemporal membrane phenomena and regulate various cellular functions. Thus, understanding how various dynamic modes influence membrane behavior is crucial to uncovering the design rules of cell membranes and implementing them in future technologies. Previous membrane dynamics studies using neutron spin-echo spectroscopy (NSE) have shed light on the dependence of collective membrane fluctuations on viscoelastic membrane properties, demonstrating that thickness fluctuation modes (100ns) are dictated by membrane viscosity, which directly governs fast (ps) molecular diffusive motions. Here, we focus on phase-separating lipid membranes, composed of DMPC:DSPC mixtures, to understand the effect of domain formation/growth on hierarchical matrix dynamics using selective lipid deuteration and different neutron spectroscopy techniques. NSE measurements on DMPC:DSPC-d83 (70:30 mol%) show that bending rigidity of the DMPC-rich matrix graduallyincreases with decreasing temperature - as the fully-fluid membrane approaches the upper phase transition (i.e. with the formation of transient DSPC clusters) - and increases further in the phase coexistence region with the growth of DSPC domains. Comparatively, NSE measurements on DMPC-d54:DSPC-d83 vesicles show pronounced matrix thickness fluctuations in the fully-fluid phase and drastic suppression of this fluctuation mode in the gel-fluid coexistence phase, even when the DMPC-rich matrix is still in its fluid phase. This suppression in fluctuations suggests an increase in the matrix viscosity with the growth of gel DSPC domains, which is further investigated by selectively measuring lipid diffusion in the DMPC-rich matrix using neutron backscattering spectroscopy. Comparisons of the experimental results with coarse-grained MD simulationsillustrate the underlying coupling mechanisms. Overall, these observations indicate a clear mechanical and viscoelastic coupling betweenlipid domains and their host matrix, suggesting that domain formation influences membrane properties beyond local effects.

Carrillo, Jan Michael↗
DOE OSTI2014

A general methodology for inverse estimation of the elastic and anelastic properties of anisotropic open-cell porous materials—with application to a melamine foam

This paper proposes an inverse estimation method for the characterisation of the elastic and anelastic properties of the frame of anisotropic open-cell foams used for sound absorption. A model of viscoelasticity based on a fractional differential constitutive equation is used, leading to an augmented Hooke's law in the frequency domain, where the elastic and anelastic phenomena appear as distinctive terms in the stiffness matrix. The parameters of the model are nine orthotropic elastic moduli, three angles of orientation of the material principal directions and three parameters governing the anelastic frequency dependence. The inverse estimation consists in numerically fitting the model on a set of transfer functions extracted from a sample of material. The setup uses a seismic-mass measurement repeated in the three directions of space and is placed in a vacuum chamber in order to remove the air from the pores of the sample. The method allows to reconstruct the full frequency-dependent complex stiffness matrix of the frame of an anisotropic open-cell foam and in particular it provides the frequency of maximum energy dissipation by viscoelastic effects. The characterisation of a melamine foam sample is performed and the relation between the fractional-derivative model and other types of parameterisations of the augmented Hooke's law is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Corrosion of 316 L stainless steel under the natural circulation of molten NaCl-MgCl 2 salt

The corrosion behavior of 316 L stainless steel (SS) was studied via the natural circulation of molten eutectic NaCl-MgCl 2 salt through a microloop. The post-corrosion tested 316 L SS microloop sections were characterized with microscopy techniques to determine the microstructural and microchemical changes that occurred at the alloy/salt interface. It was found that 316 L SS showed heterogeneous dissolution at the hot-leg, whereas deposition of corrosion products occurred at the cold-leg. For the first time, experimentally obtained molten salt flow-induced corrosion of 316 L SS results were combined with computational thermodynamic-kinetic models to validate the dissolution and deposition in terms of elemental compositional changes at the alloy/salt interface. The thermodynamic-kinetic modeling predicted that the heterogeneous dissolution of Cr and Fe from the hot-leg section of 316 L SS persisted throughout the salt circulation. The model also estimated that, despite Cr deposition starting earlier than Fe, the total redeposition of Fe is expected to be significantly greater than that of Cr over the circulation of salt. Furthermore, the modeling accurately predicted the subsurface enrichment of Mo which is attributed to the reduced Cr activity and the relatively higher diffusion rate of Mo within the alloy matrix. Here, the agreement between modeling and experimental results confirms that Fe chlorides dissolve at the hot-leg and subsequently deposit at the cold-leg due to activity changes driven by the thermal gradient. By contrast, Cr was not detected in the cold-leg deposits, which is attributed to its weaker temperature dependence on activity, limiting its redeposition under these conditions.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Skin factor and potential formation damage from chemical and mechanical processes in a naturally fractured carbonate aquifer with implications to CO 2 sequestration

Here, in this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO 2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

What can the GRACE seasonal cycle tell us about lake-aquifer interactions?

Lake-aquifer interactions have been the subject of investigation and debate for decades. Traditional investigation methods include measurement of water flux across the groundwater-surface water interface, application of heat and environmental tracer methods, conducting numerical simulations of the water flow, and mass balance-based approaches. We first review, evaluate and describe the different approaches that have been applied for examining lake-aquifer interactions and propose an additional complementary approach. While the leakage from lakes and its slow movement through porous media (laminar flow) is well characterized by existing methods, modeling the rapid and turbulent flow through preferred pathways (faults/karst) remains a challenging task. To better understand the nature, and the full scale, of the lake aquifer interactions, and using Lake Nasser and the underlying Dakhla subbasin of the Nubian Sandstone Aquifer System (NSAS) in the Western Desert of Egypt (area: 0.66 x 10 6 km 2 ) as a test site, we examine, model, and correlate temporally and spatially, the variations in Gravity Recovery and Climate Experiment terrestrial water storage (GRACE TWS ) solutions, with precipitation, lake levels, area, and water volume. We review current GRACE applications in hydrology and present our novel approach. Findings include: firstly, large seasonal fluctuations (peak: Nov./Dec.; trough: July/Aug.) in Lake Nasser's surface water levels (average annual fluctuations: from 3.7 m to 7.5 m), area (average area: 3622 km 2 but up to 4530 km 2 ), and volume (annual average: 13.4 km 3 , and up to 34 km 3 ) are observed throughout years 2006 to 2015. These fluctuations are accompanied by an increase in GRACE TWS (average: 50 ± 13 mm/yr, up to 77 ± 18 mm/yr) over Lake Nasser and by a progression of a front of increasing GRACE TWS values (> 50 ± 13 mm) away from the lake reaching distances of up to 700 km some 3 to 5 months following peak lake level periods. The areas witnessing the seasonal increase in GRACE TWS display a progressive increase in phase and decrease in amplitude with distance from the lake. Secondly, the negligible precipitation over the Dakhla subbasin cannot account for the observed seasonal GRACE TWS patterns and neither can the leakage signal from Lake Nasser. Thirdly, overall similarities in the distribution of GRACE TWS seasonal spatial patterns are observed. During high lake level periods (e.g., Dec. 2007; Feb. 2015) additional, and more distant, areas from Lake Nasser saw increases in GRACE TWS and vice versa during low lake level periods (e.g., July 2006; Aug. 2010). These observations are consistent with Lake Nasser being the main source of modern recharge for the Dakhla subbasin and suggest a new conceptual model for the subbasin: a slow groundwater flow through a porous matrix and a rapid groundwater flow along a network of faults, fractures, and karst topography across the matrix. We suggest that the proposed conceptual model for the interaction between Lake Nasser and the Dakhla subbasin could be applicable to aquifers of similar geologic, climatic, and hydrologic settings worldwide and that approaches similar to those advocated here could be used to investigate the validity of this suggestion.

54 ENVIRONMENTAL SCIENCES↗