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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Electroweak fragmentation functions for dark matter annihilation

Electroweak corrections can play a crucial role in dark matter annihilation. The emission of gauge bosons, in particular, leads to a secondary flux consisting of all Standard Model particles, and may be described by electroweak fragmentation functions. To assess the quality of the fragmentation function approximation to electroweak radiation in dark matter annihilation, we have calculated the flux of secondary particles from gauge-boson emission in models with Majorana fermion and vector dark matter, respectively. For both models, we have compared cross sections and energy spectra of positrons and antiprotons after propagation through the galactic halo in the fragmentation function approximation and in the full calculation. Fragmentation functions fail to describe the particle fluxes in the case of Majorana fermion annihilation into light fermions: the helicity suppression of the lowest-order cross section in such models cannot be lifted by the leading logarithmic contributions included in the fragmentation function approach. However, for other classes of models like vector dark matter, where the lowest-order cross section is not suppressed, electroweak fragmentation functions provide a simple, model-independent and accurate description of secondary particle fluxes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1980

Design of a recursive vector processor using polynomial splines

The problem of obtaining smoothed estimates of function values, particularly their derivatives, from a finite set of inaccurate measurements is considered. A recursive two-dimensional vector processor is introduced as an approximation to the nonrecursive constrained least-squares estimation. Here, piecewise bicubic Hermite polynomials are extensively used as approximating functions, and the smoothing integral is converted to a discrete quadratic form. This makes it possible to convert the problem of fitting an approximating function to one of estimating the function values and derivatives at the nodes.

Kim, C. S.↗
DOE OSTI2014

Joint discrete universality of Hurwitz zeta functions

We obtain a joint discrete universality theorem for Hurwitz zeta functions. Here the parameters of zeta functions and the step of shifts of these functions approximating a given family of analytic functions are connected by some condition of linear independence. Nesterenko's theorem gives an example satisfying this condition. The universality theorem is applied to estimate the number of zeros of a linear combination of Hurwitz zeta functions. Bibliography: 20 titles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Multi-level methods and approximating distribution functions

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2003

An Approximate Dissipation Function for Large Strain Rubber Thermo-Mechanical Analyses

Mechanically induced viscoelastic dissipation is difficult to compute. When the constitutive model is defined by history integrals, the formula for dissipation is a double convolution integral. Since double convolution integrals are difficult to approximate, coupled thermo-mechanical analyses of highly viscous rubber-like materials cannot be made with most commercial finite element software. In this study, we present a method to approximate the dissipation for history integral constitutive models that represent Maxwell-like materials without approximating the double convolution integral. The method requires that the total stress can be separated into elastic and viscous components, and that the relaxation form of the constitutive law is defined with a Prony series. Numerical data is provided to demonstrate the limitations of this approximate method for determining dissipation. Rubber cylinders with imbedded steel disks and with an imbedded steel ball are dynamically loaded, and the nonuniform heating within the cylinders is computed.

Johnson, Arthur R.↗
DOE OSTI2020

Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Efficient and high-capacity storage materials are indispensable for a hydrogen-based economy. In silico tools can accelerate the process of discovery of new adsorbent materials with optimal hydrogen adsorption enthalpies. Density functional theory is well-poised to become a very useful tool for enabling high-throughput screening of potential materials. In this work, we have identified density functional approximations that provide good performance for hydrogen binding applications following a two-pronged approach. First, we have compiled a data set (H2Bind275) that comprehensively represents the hydrogen binding problem capturing the chemical and mechanistic diversity in the binding sites encountered in hydrogen storage materials. We have also computed reference interaction energies for this data set using coupled-cluster theory. Second, we have assessed the performance of 55 density functional approximations for predicting H 2 interaction energies and have identified two hybrid density functionals (ωB97X-V and ωB97M-V), two double hybrid density functionals (DSD-PBEPBE-D3(BJ) and PBE0-DH), and one semilocal density functional (B97M-V) as the best performing ones. We have recommended the addition of empirical dispersion corrections to systematically underbinding density functionals such as revPBE, BLYP, and B3LYP for improvements in performance at negligible additional cost. We have also recommended the usage of the def2-TZVPP basis set as it represents a good compromise between accuracy and cost, limiting the finite basis set errors to less than 1 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Orbital dependent complications for close vs well-separated electrons in diradicals

We investigate two limits in open-shell diradical systems: O3, in which the interesting orbitals are in close proximity to one another, and (C21H13)2, where there is a significant spatial separation between the two orbitals. In accord with earlier calculations, we find that standard density-functional approximations do not predict the open-shell character for the former case but uniformly predict the open-shell character for the latter case. We trace the qualitatively incorrect behavior in O3 predicted by these standard density functional approximations to self-interaction error and use the Fermi–Löwdin-orbital-self-interaction-corrected formalism to determine accurate triplet, closed-shell singlet, and open-shell broken-spin-symmetry electronic configurations. Analysis of the resulting many-electron overlap matrices allows us to unambiguously show that the broken-spin-symmetry configurations do not participate in the representation of the Ms = 0 triplet states and allows us to reliably extract the singlet–triplet splitting in O3 by analyzing the energy as a function of Fermi-orbital-descriptor permutations. The results of these analyses predict the percentage of open-shell character in O3, which agrees well with conventional wavefunction-based methods. While these techniques are expected to be required in cases near the Coulson–Fischer point, we find that they will be less necessary in diradical systems with well-separated electrons, such as (C21H13)2. Results based on energies from self-interaction-corrected generalized gradient, local density, and Hartree–Fock approximations and experimental results are in generally good agreement for O3. These results help form the basis for deriving extended Heisenberg-like Hamiltonians that are needed for descriptions of molecular magnets when there are competing low-energy electronic configurations.

Chemistry↗
DOE OSTI2015

FOURIER ANALYSIS OF BLAZAR VARIABILITY: KLEIN–NISHINA EFFECTS AND THE JET SCATTERING ENVIRONMENT

The strong variability of blazars can be characterized by power spectral densities (PSDs) and Fourier frequency-dependent time lags. In previous work, we created a new theoretical formalism for describing the PSDs and time lags produced via a combination of stochastic particle injection and emission via the synchrotron, synchrotron self-Compton, and external Compton (EC) processes. This formalism used the Thomson cross section and simple δ-function approximations to model the synchrotron and Compton emissivities. Here we expand upon this work, using the full Compton cross section and detailed and accurate emissivities. Our results indicate good agreement between the PSDs computed using the δ-function approximations and those computed using the accurate expressions, provided the observed photons are produced primarily by electrons with energies exceeding the lower limit of the injected particle population. Breaks are found in the PSDs at frequencies corresponding to the cooling timescales of the electrons primarily responsible for the observed emission, and the associated time lags are related to the difference in electron cooling timescales between the two energy channels, as expected. If the electron cooling timescales can be determined from the observed time lags and/or the observed EC PSDs, then one could in principle use the method developed here to determine the energy of the external seed photon source for EC, which is an important unsolved problem in blazar physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Strongly correlated electrons: Ground states, excited states, and transport. Final report

The research supported by this grant focused on the quantum mechanical theory of the electrons in materials and molecules. Progress was made in dealing with electronic correlation effects in the ground state energy of molecular systems, and with topological concepts to classify the electronic state of molecules and materials, including excitation and transport properties. The physical and chemical properties of molecules and materials derive from their electronic structure, but the latter cannot be calculated exactly even with the most powerful computers because the computational cost of solving the exact equations of quantum mechanics increases exponentially with the number of electrons. The exponential cost originates from the correlations among the electrons that repel each other via Coulombic forces. In this project we have developed a new functional approximation for the ground state electronic energy that includes explicitly, and in a controllable way, the effects of the interelectronic correlations. In addition we have further developed topological concepts for classifying the electronic states of periodic ring molecules and solids. Topological concepts are very powerful because they allow us to predict subtle properties of materials and molecules using very general geometrical properties of the electron wavefunctions that do not depend on the quantitative details of the electronic interactions, which are very difficult to calculate with high accuracy. The development of a new class of controlled functional approximations for the ground state energy of molecules and materials was the main goal of the project. It has been fulfilled with the formulation of the occupation-probabilities natural orbital functional theory (OP-NOFT). This approach introduces new theoretical concepts but practical application has proved to be harder than anticipated. So far it has been utilized only at its lowest level of approximation in the context of relatively small molecules (with up to 16 atoms). The study of topological properties of the electron wavefunctions in materials was not proposed in the original proposal but was prompted during the funding period by our interaction with leading experimental groups in materials chemistry and physics at Princeton University.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Advanced stationary and nonstationary kernel designs for domain-aware Gaussian processes

Gaussian process regression is a widely-applied method for function approximation and uncertainty quantification. The technique has gained popularity recently in the machine learning community due to its robustness and interpretability. The mathematical methods we discuss in this paper are an extension of the Gaussian-process framework. We are proposing advanced kernel designs that only allow for functions with certain desirable characteristics to be elements of the reproducing kernel Hilbert space (RKHS) that underlies all kernel methods and serves as the sample space for Gaussian process regression. These desirable characteristics reflect the underlying physics; two obvious examples are symmetry and periodicity constraints. In addition, non-stationary kernel designs can be defined in the same framework to yield flexible multi-task Gaussian processes. We will show the impact of advanced kernel designs on Gaussian processes using several synthetic and two scientific data sets. The results of our research show that including domain knowledge, communicated through advanced kernel designs, has a significant impact on the accuracy and relevance of the function approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An analysis of hydrated proton diffusion in ab initio molecular dynamics

A detailed understanding of the inherently multiscale proton transport process raises a number of scientifically challenging questions. For example, there remain many (partially addressed) questions on the molecular mechanism for long-range proton migration and the potential for the formation of long-lived traps giving rise to burst-and-rest proton dynamics. Using results from a sizeable collection of ab initio molecular dynamics (AIMD) simulations (totaling ∼2.7 ns) with various density functional approximations (Becke-Lee-Yang-Parr (BLYP), BLYP–D3, Hamprecht-Cohen-Tozer-Handy, B3LYP) and temperatures (300–330 K), equilibrium and dynamical properties of one excess proton and 128 water molecules are studied. Two features in particular (concerted hops and weak hydrogen-bond donors) are investigated to identify modes in the system that are strongly correlated with the onset of periods of burst-and-rest dynamics. The question of concerted hops seeks to identify those time scales over which long-range proton transport can be classified as a series of sequential water hopping events or as a near-simultaneous concerted process along compressed water wires. The coupling of the observed burst-and-rest dynamics with motions of a fourth neighboring water molecule (a weak hydrogen-bond donor) solvating the protonated water molecule is also investigated. The presence (absence) of hydrogen bonds involving this fourth water molecule before and after successful proton hopping events is found to be strongly correlated with periods of burst (rest) dynamics (and consistent with pre-solvation concepts). By analyzing several realizations of the AIMD trajectories on the 100-ps time scale, convergence of statistics can be assessed. For instance, it was observed that the probability for a fourth water molecule to approach the hydronium, if not already proximal at the beginning of the lifetime of the hydronium, is very low, indicative of the formation of stable void regions. Furthermore, the correlations of the neighboring water atoms are identified as the fourth water approaches the hydronium. Finally, the temperature effects on structural and dynamical properties are studied.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Assessing the accuracy of compound formation energies with quantum Monte Carlo

Accurately predicting the formation energy of a compound, which describes its thermodynamic stability, is a key challenge in materials physics. Here, we employ a many-body quantum Monte Carlo (QMC) with single-reference trial functions to compute the formation energy of two electronically disparate compounds, the intermetallic VPt2 and the semiconductor CuI, for which standard density functional theory (DFT) predictions using both the Perdew-Burke-Ernzerhof (PBE) and the strongly constrained and appropriately normed (SCAN) density functional approximations deviate markedly from available experimental values. For VPt2, we find an agreement between QMC, SCAN, and PBE0 estimates, which therefore remain in disagreement with the much less exothermic experimental value. For CuI, the QMC result agrees with neither SCAN nor PBE pointing towards DFT exchange-correlation biases, likely related to the localized Cu 3d electrons. Compared to the behavior of some density functional approximations within DFT, spin-averaged QMC exhibits a smaller but still appreciable deviation when compared to experiment. The QMC result is slightly improved by incorporating spin-orbit corrections for CuI and solid I 2 , so that experiment and theory are brought into imperfect but reasonable agreement within about 120 meV/atom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant

Abstract We study stars in the J-regions of the asymptotic giant branch (JAGB) of near-infrared color–magnitude diagrams in the maser host NGC 4258 and four hosts of six Type Ia supernovae (SNe Ia): NGC 1448, NGC 1559, NGC 5584, and NGC 5643. These clumps of stars are readily apparent near 1.0 < F150W − F277W < 1.5 andm F150W = 22–25 mag with James Webb Space Telescope NIRCam photometry. Various methods have been proposed to assign an apparent reference magnitude to this recently proposed standard candle, including the mode, median, sigma-clipped mean, or a modeled luminosity function parameter. We test the consistency of these by measuring intrahost variations, finding differences of up to ∼0.2 mag that significantly exceed statistical uncertainties. Brightness differences appear intrinsic, and are further amplified by the nonuniform shape of the JAGB luminosity function, also apparent in the LMC and SMC. We follow a “many methods” approach to measure consistently JAGB magnitudes and distance moduli to the SN Ia host sample calibrated by NGC 4258. We find broad agreement with distance moduli measured from Cepheids, tip of the red giant branch, and Miras. However, the SN host mean distance modulus estimated via the JAGB method necessary to estimateH 0 differs by ∼0.19 mag among the above definitions, the result of different levels of luminosity function asymmetry. The methods yield a full range of 71−78 km s −1 Mpc −1 , i.e., a fiducial result ofH 0 = 74.7 ± 2.1(stat) ± 2.3(sys, ±3.1 if combined in quadrature) km s −1 Mpc −1 , with systematic errors limited by the differences in methods. Future work may seek to standardize and refine this promising tool further, making it more competitive with established distance indicators.

Astronomy & Astrophysics↗
NASA NTRS2014

Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

This paper introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio and number of control surfaces. A doublet lattice approach is taken to compute generalized forces. A rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. Although, all parameters can be easily modified if desired.The focus of this paper is on tool presentation, verification and validation. This process is carried out in stages throughout the paper. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool. Therefore the flutter speed and frequency for a clamped plate are computed using V-g and V-f analysis. The computational results are compared to a previously published computational analysis and wind tunnel results for the same structure. Finally a case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to V-g and V-f analysis. This also includes the analysis of the model in response to a 1-cos gust.

Modeling and Simulation↗
DOE OSTI2022

Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression

Here, we use Gaussian stochastic weight averaging (SWAG) to assess the epistemic uncertainty associated with neural-network-based function approximation relevant to fluid flows. SWAG approximates a posterior Gaussian distribution of each weight, given training data, and a constant learning rate. Having access to this distribution, it is able to create multiple models with various combinations of sampled weights, which can be used to obtain ensemble predictions. The average of such an ensemble can be regarded as the 'mean estimation', whereas its standard deviation can be used to construct 'confidence intervals', which enable us to perform uncertainty quantification (UQ) with regard to the training process of neural networks. We utilize representative neural-network-based function approximation tasks for the following cases: (i) a two-dimensional circular-cylinder wake; (ii) the DayMET dataset (maximum daily temperature in North America); (iii) a three-dimensional square-cylinder wake; and (iv) urban flow, to assess the generalizability of the present idea for a wide range of complex datasets. SWAG-based UQ can be applied regardless of the network architecture, and therefore, we demonstrate the applicability of the method for two types of neural networks: (i) global field reconstruction from sparse sensors by combining convolutional neural network (CNN) and multi-layer perceptron (MLP); and (ii) far-field state estimation from sectional data with two-dimensional CNN. We find that SWAG can obtain physically-interpretable confidence-interval estimates from the perspective of epistemic uncertainty. This capability supports its use for a wide range of problems in science and engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Dynamic aspects of graphene deformation and fracture from approximate density functional theory

Graphene is one of the most intriguing two-dimensional carbon materials. Its mechanical strength and failure are key concerns for materials engineering and applications. Despite the success of fracture mechanics, the mechanism of how pristine materials fail remains an elusive problem. While many theoretical studies based on molecular dynamics using empirical forcefields have tried to address this question, atomic-scale mechanics are not clearly understood. Especially, a widely employed bond-breaking approach based on the critical bond length has not been rigorously tested. Here, utilizing molecular dynamics simulations with density functional based tight binding, we investigate how the failure of the pristine material initiates. The Wiberg bond order (W BO ) to estimate the change of chemical bonds shows a transition from sp 2 (W BO ~ 1.33) to sp 3 (WBO < 1.0) during the deformation. However, it reveals that a single threshold value for either the WBO or bond length is insufficient to decide failure of pristine material without free edges or defects. Instead, collective behaviors of the local atomic group govern the fracture initiation of pristine graphene. Overall, our study provides dynamic mechanical responses based on quantum mechanics, which have not been captured by empirical forcefields, opening opportunities to design properties by precisely coupling the mechanics and quantum mechanics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Erratum: “DFTB+, a software package for efficient approximate density functional theory based atomistic simulations” [J. Chem. Phys. 152, 124101 (2020)]

The implementation of the GPU support in DFTB+, as described in Sec. III C of the original publication,1 was developed based on a previous unpublished implementation by Jacek Jakowski. In order to acknowledge his work on this first implementation, the authors of the original publication wish to include J. Jakowski as co-author. The scientific content of the original publication is not affected.

42 ENGINEERING↗