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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Covariant Spectator Theory of np scattering: Deuteron magnetic moment and form factors

The deuteron magnetic moment is calculated using two model wave functions obtained from 2007 high precision fits to $np$ scattering data. Included in the calculation are a new class of isoscalar $np$ interaction currents which are automatically generated by the nuclear force model used in these fits. After normalizing the wave functions, nearly identical predictions are obtained: model WJC-1, with larger relativistic P-state components, gives 0.863(2), while model WJC-2 with very small $P$-state components gives 0.864(2) These are about 1\% larger than the measured value of the moment, 0.857 n.m., giving a new prediction for the size of the $\rho\pi\gamma$ exchange, and other purely transverse interaction currents that are largely unconstrained by the nuclear dynamics. The physical significance of these results is discussed, and general formulae for the deuteron form factors, expressed in terms of deuteron wave functions and a new class of interaction current wave functions, are given.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Modeling Internal Material Melting

The purpose of the SEED LDRD was to create new functionality to model internal material melting and solidification inside the state-of-the-art nuclear fuel performance simulation code BISON.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A machine learning framework for accurate and robust analysis of radiation detector pulses

The microscopic properties of atomic nuclei are used to study various scientific questions. They are essential for understanding the fundamental forces of nature and the chemical evolution of the universe. Detecting decay radiation from radioactive nuclei makes it possible to probe these fundamental nuclear properties. Detector waveform traces may contain additional information about the radiation. Generally, advanced signal processing techniques are needed to extract this additional information, often involving fitting the waveform with model response functions using non-linear least-squares optimization with second-order gradient methods. While this is a powerful technique, it is also computationally expensive, leading to slow processing time, which scales with the volume of data. To address this problem, we have developed a machine learning (ML) approach that infers the characteristics of traces from a model detector response function. In particular, we are interested in classifying whether a single recorded trace consists of one or two pulse constituents and estimating the pulse parameters. Furthermore, our proposed ML method can precisely extract the pulses’ parameters, such as energy and timing information, and accurately classify the pulse multiplicity of a trace. Unlike non-learning-based approaches, our ML approach uses neural networks that are significantly faster at inference, as they do not require any optimization during this stage.

Curve fitting↗
DOE OSTI2019

From graphical to model-based distillation column design: A McCabe-Thiele-inspired mathematical programming approach

We propose a mixed-integer nonlinear programming (MINLP) model for simple and complex distillation column design and optimization. The model is based upon the concepts and equations underpinning the McCabe-Thiele method. Generalizing this method, we introduce material balances at various locations of the column and employ binary variables to determine the optimal number of trays and optimal feed locations. We model the vapor–liquid equilibrium using continuous piecewise linear approximating functions. The model is extended to account for multicomponent mixtures and non-constant-molar overflow. We also discuss how to estimate the minimum number of trays and the minimum reflux ratio.

42 ENGINEERING↗
DOE OSTI2023

Quantum dynamics of non-Hermitian many-body Landau-Zener systems

Here, we develop a framework to solve a large class of linearly driven non-Hermitian quantum systems. Such a class of models in the Hermitian scenario is commonly known as multistate Landau-Zener models. The non-Hermiticity is due to the anti-Hermitian couplings between the diabatic levels. We find that there exists a conservation law, unique to this class of models, that describes the simultaneous growth of the unnormalized wave functions. These models have practical applications in Bose-Einstein condensates, and they can describe the dynamics of multispecies bosonic systems. The conservation law relates to a pair-production mechanism that explains the dissociation of diatomic molecules into atoms. We provide a general framework for both solvable and semiclassically solvable non-Hermitian Landau-Zener models. Our findings will open alternative avenues for a number of diverse emergent phenomena in explicitly time-dependent non-Hermitian quantum systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

Baryon fields with U{sub L}(3)xU{sub R}(3) chiral symmetry. III. Interactions with chiral [(3,3)+(3,3)] spinless mesons

Three-quark nucleon interpolating fields in QCD have well-defined SU{sub L}(3)xSU{sub R}(3) and U{sub A}(1) chiral transformation properties, viz. [(6,3)+(3,6)], [(3,3)+(3,3)], [(8,1)+(1,8)], and their mirror images; see [H. X. Chen, V. Dmitrasinovic, A. Hosaka, K. Nagata, and S. L. Zhu, Phys. Rev. D 78, 054021 (2008)]. It has been shown (phenomenologically) in [H. X. Chen, V. Dmitrasinovic, and A. Hosaka, Phys. Rev. D 81, 054002 (2010)] that mixing of the [(6,3)+(3,6)] chiral multiplet with one ordinary (naive) and one mirror field belonging to the [(3,3)+(3,3)], [(8,1)+(1,8)] multiplets can be used to fit the values of the isovector (g{sub A}{sup (3)}) and the flavor-singlet (isoscalar) axial coupling (g{sub A}{sup (0)}) of the nucleon and then predict the axial F and D coefficients, or vice versa, in reasonable agreement with experiment. In an attempt to derive such mixing from an effective Lagrangian, we construct all SU{sub L}(3)xSU{sub R}(3) chirally invariant nonderivative one-meson-baryon interactions and then calculate the mixing angles in terms of baryons' masses. It turns out that there are (strong) selection rules: for example, there is only one nonderivative chirally symmetric interaction between J=(1/2) fields belonging to the [(6,3)+(3,6)] and the [(3,3)+(3,3)] chiral multiplets, that is also U{sub A}(1) symmetric. We also study the chiral interactions of the [(3,3)+(3,3)] and [(8,1)+(1,8)] nucleon fields. Again, there are selection rules that allow only one off-diagonal nonderivative chiral SU{sub L}(3)xSU{sub R}(3) interaction of this type, that also explicitly breaks the U{sub A}(1) symmetry. We use this interaction to calculate the corresponding mixing angles in terms of baryon masses and fit two lowest-lying observed nucleon (resonance) masses, thus predicting the third (J=(1/2), I=(3/2)) {Delta} resonance, as well as one or two flavor-singlet {Lambda} hyperon(s), depending on the type of mixing. The effective chiral Lagrangians derived here may be applied to high density matter calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

TU-D-207B-01: A Prediction Model for Distinguishing Radiation Necrosis From Tumor Progression After Gamma Knife Radiosurgery Based On Radiomics Features From MR Images

Purpose: To develop and validate a prediction model using radiomics features extracted from MR images to distinguish radiation necrosis from tumor progression for brain metastases treated with Gamma knife radiosurgery. Methods: The images used to develop the model were T1 post-contrast MR scans from 71 patients who had had pathologic confirmation of necrosis or progression; 1 lesion was identified per patient (17 necrosis and 54 progression). Radiomics features were extracted from 2 images at 2 time points per patient, both obtained prior to resection. Each lesion was manually contoured on each image, and 282 radiomics features were calculated for each lesion. The correlation for each radiomics feature between two time points was calculated within each group to identify a subset of features with distinct values between two groups. The delta of this subset of radiomics features, characterizing changes from the earlier time to the later one, was included as a covariate to build a prediction model using support vector machines with a cubic polynomial kernel function. The model was evaluated with a 10-fold cross-validation. Results: Forty radiomics features were selected based on consistent correlation values of approximately 0 for the necrosis group and >0.2 for the progression group. In performing the 10-fold cross-validation, we narrowed this number down to 11 delta radiomics features for the model. This 11-delta-feature model showed an overall prediction accuracy of 83.1%, with a true positive rate of 58.8% in predicting necrosis and 90.7% for predicting tumor progression. The area under the curve for the prediction model was 0.79. Conclusion: These delta radiomics features extracted from MR scans showed potential for distinguishing radiation necrosis from tumor progression. This tool may be a useful, noninvasive means of determining the status of an enlarging lesion after radiosurgery, aiding decision-making regarding surgical resection versus conservative medical management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Three-dimensional gravity modeling and focusing inversion using rectangular meshes.

Rectangular grid cells are commonly used for the geophysical modeling of gravity anomalies, owing to their flexibility in constructing complex models. The straightforward handling of cubic cells in gravity inversion algorithms allows for a flexible imposition of model regularization constraints, which are generally essential in the inversion of static potential field data. The first part of this paper provides a review of commonly used expressions for calculating the gravity of a right polygonal prism, both for gravity and gradiometry, where the formulas of Plouff and Forsberg are adapted. The formulas can be cast into general forms practical for implementation. In the second part, a weighting scheme for resolution enhancement at depth is presented. Modelling the earth using highly digitized meshes, depth weighting schemes are typically applied to the model objective functional, subject to minimizing the data misfit. The scheme proposed here involves a non-linear conjugate gradient inversion scheme with a weighting function applied to the non-linear conjugate gradient scheme's gradient vector of the objective functional. The low depth resolution due to the quick decay of the gravity kernel functions is counteracted by suppressing the search directions in the parameter space that would lead to near-surface concentrations of gravity anomalies. Further, a density parameter transformation function enabling the imposition of lower and upper bounding constraints is employed. Using synthetic data from models of varying complexity and a field data set, it is demonstrated that, given an adequate depth weighting function, the gravity inversion in the transform space can recover geologically meaningful models requiring a minimum of prior information and user interaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Diagrammatic Monte Carlo Approach to Real‐frequency Response Functions and the Spin‐Fermion Model of Hot Spots (Final Report)

This three‐year research project was focused on two outstanding condensed matter problems (i) Real‐frequency response functions in Coulomb systems at finite temperature, and Fermi surface (FS) reconstruction in the Spin-Fermion (SF) model. The uniform electron gas (jellium) model, describing electrons interacting via long‐range Coulomb forces on positive neutralizing background, is fundamentally important both for understanding the physics of correlated electrons and for formulation of the time‐dependent density functional theory (TDDFT). The spin-fermion model has found a wide range of applications in the physics of cuprates and iron‐based superconductors to explain the “strange metal" behavior and to suggest a possible pairing mechanism for high‐temperature superconductivity. The project’s goals were development and application of the Diagrammatic Monte Carlo (DiagMC) techniques for solving the above problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1997

The Surface Heat Flux as a Function of Ground Cover for Climate Models

Surface heat fluxes were examined as a function of surface properties and meteorological conditions in a 100 km x 100 km grid square at 1-km spatial resolution centered at the location of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE), the Forest Ecosystem Dynamics site in central Maine, and a semiarid rangeland site around Walnut Gulch, Arizona. This investigation treats the surface heat flux variability within a GCM grid box to provide insight into methods for treating that variability in climate models. The heat fluxes were calculated using NOAA AVHRR and available meteorological data. The average heat fluxes that were estimated using the various area ground-cover representations were compared with the ensemble average heat fluxes for the entire area, which were assumed to be the best representation of the heat fluxes for the areas. Average beat fluxes were estimated for the entire 100 km x 100 km area based on a single ground-cover representation, and the mean error for the area sensible heat flux was about 10% and for the area latent heat flux, 21%. The estimation error was reduced, and in some cases significantly reduced, when the area heat fluxes were estimated by partitioning the area according to significant ground cover. The most significant effect of the partitioning was on the latent heat flux estimates.

Vukovich, Fred M.↗
DOE OSTI2014

Development of multicomponent hybrid density functional theory with polarizable continuum model for the analysis of nuclear quantum effect and solvent effect on NMR chemical shift

We have developed the multicomponent hybrid density functional theory [MC-(HF+DFT)] method with polarizable continuum model (PCM) for the analysis of molecular properties including both nuclear quantum effect and solvent effect. The chemical shifts and H/D isotope shifts of the picolinic acid N-oxide (PANO) molecule in chloroform and acetonitrile solvents are applied by B3LYP electron exchange-correlation functional for our MC-(HF+DFT) method with PCM (MC-B3LYP/PCM). Our MC-B3LYP/PCM results for PANO are in reasonable agreement with the corresponding experimental chemical shifts and isotope shifts. We further investigated the applicability of our method for acetylacetone in several solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Shape restricted additive hazards models: Monotone, unimodal, and U‐shape hazard functions

We consider estimation of the semiparametric additive hazards model with an unspecified baseline hazard function where the effect of a continuous covariate has a specific shape but otherwise unspecified. Such estimation is particularly useful for a unimodal hazard function, where the hazard is monotone increasing and monotone decreasing with an unknown mode. A popular approach of the proportional hazards model is limited in such setting due to the complicated structure of the partial likelihood. Our model defines a quadratic loss function, and its simple structure allows a global Hessian matrix that does not involve parameters. Thus, once the global Hessian matrix is computed, a standard quadratic programming method can be applicable by profiling all possible locations of the mode. However, the quadratic programming method may be inefficient to handle a large global Hessian matrix in the profiling algorithm due to a large dimensionality, where the dimension of the global Hessian matrix and number of hypothetical modes are the same order as the sample size. We propose the quadratic pool adjacent violators algorithm to reduce computational costs. The proposed algorithm is extended to the model with a time‐dependent covariate with monotone or U‐shape hazard function. In simulation studies, our proposed method improves computational speed compared to the quadratic programming method, with bias and mean square error reductions. We analyze data from a recent cardiovascular study.

Mathematical & Computational Biology↗
DOE OSTI2011

Grounding annotations in published literature with an emphasis on the functional roles used in metabolic models

Accurate genome annotations in databases are a critical resource available to the scientific community for analysis and research. Inaccurate and inconsistent annotations exist as a result of errors generated from mass automated annotation, and currently act as a barrier to the application of bioinformatics. The purpose of this effort was to improve the SEED by improving the connection of functional roles to literature references. Direct literature references (DLits), found through searches of PubMed and other online databases such as SwissProt, were attached to protein sequences within the PubSEED to provide literature support for the roughly 2,500 distinct functional roles used to construct metabolic models within the Model SEED. Only DLits in which a researcher asserted the function of a protein were attached to sequences. Starting from a list of 1,072 functional roles that did not previously have DLit support, we were able to connect sequences to literature for 655 functional roles, at least 484 of which were in the original list of unsupported roles. When added to the existing set of sequences having DLits, the resulting set of DLit-sequence pairs (the foundation set) now connects approximately 4,300 DLits to approximately 5,600 distinct protein sequences obtained from approximately 16,000 genes (some of these genes have identical protein sequences). From the foundation set, we construct projection sets such that each set contains one member of the foundation set and projections of its functional role onto similar genes. The projection sets revealed 120 inconsistent annotations within the SEED. Two types of inconsistencies were corrected through manual annotation in the PubSEED: instances in which two identical protein sequences had been annotated with different functions, and instances when projected functions contradicted previous annotations. 26,785 changes to gene function assignment, 219 of which were to previously uncharacterized proteins, resulted in a more consistent and accurate set of input data from which to construct revised metabolic models within the Model SEED.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Real-time evolution of Anderson impurity models via tensor network influence functionals

In this work, we present and analyze two tensor network-based influence functional approaches for simulating the real-time dynamics of quantum impurity models such as the Anderson model. Via comparison with recent numerically exact simulations, we show that such methods accurately capture the long-time nonequilibrium quench dynamics. The two parameters that must be controlled in these tensor network influence functional approaches are a time discretization (Trotter) error and a bond dimension (tensor network truncation) error. We show that the actual numerical uncertainties are controlled by an intricate interplay of these two approximations, which we demonstrate in different regimes. Our work opens the door to using these tensor network influence functional methods as general impurity solvers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

How well do we know the neutron structure function?

Given a model of the nuclear effects in the deuteron, one can obtain the neutron structure function from a combination of proton and deuteron measurements. Historically, the results have been very sensitive to the details of the extraction, but recent works have shown that this is often the result of inconsistent kinematics between the calculations of nuclear effects and the structure function data. We present a detailed analysis of the uncertainty in the neutron $F_{2n}$ structure function extracted from inclusive deuteron and proton deep-inelastic scattering data, including experimental uncertainties and the model dependence associated with the deuteron wave-function, the different convolution calculations for the deuteron, and the prescription for the off-shell corrections. We find a significantly smaller range of results than earlier comparisons. In addition to improving the extraction of the neutron structure, this also provided an important baseline that will allow future, model-independent extractions of neutron structure to be used to examine nuclear medium effects in the deuteron.

Arrington, John↗
DOE OSTI2024

Linear Time-Invariant Models of a Large Cumulus Ensemble

Abstract Methods in system identification are used to obtain linear time-invariant state-space models that describe how horizontal averages of temperature and humidity of a large cumulus ensemble evolve with time under small forcing. The cumulus ensemble studied here is simulated with cloud-system-resolving models in radiative–convective equilibrium. The identified models extend steady-state linear response functions used in past studies and provide accurate descriptions of the transfer function, the noise model, and the behavior of cumulus convection when coupled with two-dimensional gravity waves. A novel procedure is developed to convert the state-space models into an interpretable form, which is used to elucidate and quantify memory in cumulus convection. The linear problem studied here serves as a useful reference point for more general efforts to obtain data-driven and interpretable parameterizations of cumulus convection.

Meteorology & Atmospheric Sciences↗
NASA NTRS1990

Unitary-matrix models as exactly solvable string theories

Exact differential equations are presently found for the scaling functions of models of unitary matrices which are solved in a double-scaling limit, using orthogonal polynomials on a circle. For the case of the simplest, k = 1 model, the Painleve II equation with constant 0 is obtained; possible nonperturbative phase transitions exist for these models. Equations are presented for k = 2 and 3, and discussed with a view to asymptotic behavior.

Periwal, Vipul↗