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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Analytical Methods of Approximating the Fisher Information Matrix for the Lognormal Distribution

Modelling the matter density in the universe through time has become one of the most important open problems in cosmology. One distribution that works particularly well is the lognormal distribution, where if Y follows a lognormal distribution, ln Y follows a normal distribution. In many cases, we want to know how much information a variable carries about some unknown parameter; this can be accomplished by calculating the Fisher information matrix. However, for the lognormal distribution, the Fisher matrix is much more complicated to evaluate in closed form. In this paper, we will look at some analytical methods to evaluate the Fisher matrix.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

On the characterization of biases arising from methods and approximations used for sensitivity analyses

The preliminary assessment of the performance and safety of advanced reactors, as well as the identification of research and development needs, rely on computer simulations due to the lack of operational experience. Those simulations should be based on verified and validated computational tools, calculation schemes, and nuclear data libraries, and should be accompanied of a proper characterization of the involved uncertainties, providing confidence in the computational-based predictions. Thus, sensitivity and uncertainty studies, together with integral experiments, play an essential role in that process. Sensitivities are then a critical element and guidelines about how to produce accurate enough sensitivities depending on the subsequent analyses to be performed are of interest. The present study addresses the sensitivities biases arising from the use of different nuclear data libraries, computational methods and the assumption of modelling simplifications. Not only sensitivities for multiplication factor but also for safety-relevant reactivity responses have been analyzed. In the study, propagated uncertainties are also included for the considered parameters to illustrate the impact of the sensitivity profiles obtained for each case on the final uncertainty. Then, relevant recommendations are given for sensitivity analyses of highly complex systems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Allocation and Operation of A Hydropneumatic Energy Storage with Building Microgrid

Behind-meter application for a recently invented hydropneumatic Ground-Level Integrated Diverse Energy Storage (GLIDES) is focused in this research. Considering possible uncertainties from solar radiation and electricity load in a building microgrid, two-stage stochastic programming is adopted for 15-min operation and a mixed-integer nonlinear stochastic model is built with integrated energy systems of GLIDES, solar panel and power generating unit. In order to make the model computationally tractable, we use sample average approximate method to decrease associated complexity with sample size and improve solving efficiency. The experimental results in deterministic and stochastic operation indicate that best candidate solution from SAA are superior to the solution from expected value problem in terms of optimality gap and variance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

The matrix product approximation for the dynamic cavity method

Stochastic dynamics of classical degrees of freedom, defined on vertices of locally tree-like graphs, can be studied in the framework of the dynamic cavity method which is exact for tree graphs. Such models correspond for example to spin-glass systems, Boolean networks, neural networks, and other technical, biological, and social networks. The central objects in the cavity method are edge messages—conditional probabilities of two vertex variable trajectories. In this paper, we discuss a rather pedagogical derivation for the dynamic cavity method, give a detailed account of the novel matrix product edge message (MPEM) algorithm for the solution of the dynamic cavity equation as introduced, and present optimizations and extensions. Matrix product approximations of the edge messages are constructed recursively in an iteration over time. Computation costs and precision can be tuned by controlling the matrix dimensions of the MPEM in truncations. Without truncations, the dynamics is exact. Data for Glauber–Ising dynamics shows a linear growth of computation costs in time. In contrast to Monte Carlo simulations, the approach has a much better error scaling. Hence, it gives for example access to low probability events and decaying observables like temporal correlations. Here, we discuss optimized truncation schemes and an extension that allows to capture models which have a continuum time limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

On the accuracy of density functional theory and wave function methods for calculating vertical ionization energies

The best practice in computational methods for determining vertical ionization energies (VIEs) is assessed, via reference to experimentally determined VIEs that are corroborated by highly accurate coupled-cluster calculations. These reference values are used to benchmark the performance of density functional theory (DFT) and wave function methods: Hartree-Fock theory, second-order Møller-Plesset perturbation theory, and Electron Propagator Theory (EPT). The core test set consists of 147 small molecules. An extended set of six larger molecules, from benzene to hexacene, is also considered to investigate the dependence of the results on molecule size. The closest agreement with experiment is found for ionization energies obtained from total energy difference calculations. In particular, DFT calculations using exchange-correlation functionals with either a large amount of exact exchange or long-range correction perform best. The results from these functionals are also the least sensitive to an increase in molecule size. In general, ionization energies calculated directly from the orbital energies of the neutral species are less accurate and more sensitive to an increase in molecule size. For the single-calculation approach, the EPT calculations are in closest agreement for both sets of molecules. For the orbital energies from DFT functionals, only those with long-range correction give quantitative agreement with dramatic failing for all other functionals considered. The results offer a practical hierarchy of approximations for the calculation of vertical ionization energies. In addition, the experimental and computational reference values can be used as a standardized set of benchmarks, against which other approximate methods can be compared.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Hunting ionic liquids with large electrochemical potential windows

Ionic liquids (ILs) with large electrochemical potential windows (EPWs) are ideally suited to improve the energy and power density of electrical devices for energy storage. However, guidelines are scarcely available for the selection or systematic screening of ILs for practical applications. Here, we present theoretical predictions for the EPW of thousands of cation-anion pairs based on a long-range corrected hybrid density functional theory. The cathodic and anodic potential limits were estimated from the highest occupied molecular orbital and lowest unoccupied molecular orbital energies of individual cations and anions. The approximate method predicts EPWs in reasonable agreement with existing experimental data for several commonly used ionic systems and can be used as a screening tool for a large library of ILs. Five most stable anions, with the cathode stability in the order of B[CN] 4 > PF 6 > BF 4 > BOB > NTf 2 , have been identified. These anions provide the largest EPWs when they are paired with conventional organic cations. The cation stability is reduced upon elongation of the alkyl chain length or branching of the molecular backbone.

catalysis (heterogeneous)↗
DOE OSTI2016

Observation of the spectrally invariant properties of clouds in cloudy-to-clear transition zones during the MAGIC field campaign

We use the spectrally invariant method to study the variability of cloud optical thickness τ and droplet effective radius reff in transition zones (between the cloudy and clear sky columns) observed from Solar Spectral Flux Radiometer (SSFR) and Shortwave Array Spectroradiometer-Zenith (SASZe) during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. The measurements from the SSFR and the SASZe are different, however inter-instrument differences of self-normalized measurements (divided by their own spectra at a fixed time) are small. The spectrally invariant method approximates the spectra in the cloud transition zone as a linear combination of definitely clear and cloudy spectra, where the coefficients, slope and intercept, character-ize the spectrally invariant properties of the transition zone. Simulation results from the SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) model demonstrate that (1) the slope of the visible band is positively correlated with the cloud optical thickness τ while the intercept of the near-infrared band has high negative cor-relation with the cloud drop effective radius reff even without the exact knowledge of τ; (2) the above relations hold for all Solar Zenith Angle (SZA) and for cloud-contaminated skies. In observations using redundant measure-ments from SSFR and SASZe, we find that during cloudy-to-clear transitions, (a) the slopes of the visible band de-crease, and (b) the intercepts of the near-infrared band remain almost constant near cloud edges. The findings in simulations and observations suggest that, while the optical thickness decreases during the cloudy-to-clear transition, the cloud drop effective radius does not change when cloud edges are approached. These results sup-port the hypothesis that inhomogeneous mixing dominates near cloud edges in the studied cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Understanding the optical properties of ambient sub- and supermicron particulate matter: results from the CARES 2010 field study in northern California

Abstract. Measurements of the optical properties (absorption, scattering and extinction) of PM1, PM2.5 and PM10 made at two sites around Sacramento, CA, during the June 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are reported. These observations are used to establish relationships between various intensive optical properties and to derive information about the dependence of the optical properties on photochemical aging and sources. Supermicron particles contributed substantially to the total light scattering at both sites, about 50 % on average. A strong, linear relationship is observed between the scattering Ångström exponent for PM10 and the fraction of the scattering that is contributed by submicron particles (fsca, PM1) at both sites and with similar slopes and intercepts (for a given pair of wavelengths), suggesting that the derived relationship may be generally applicable for understanding variations in particle size distributions from remote sensing measurements. At the more urban T0 site, the fsca, PM1 increased with photochemical age, whereas at the downwind, more rural T1 site the fsca, PM1 decreased slightly with photochemical age. This difference in behavior reflects differences in transport, local production and local emission of supermicron particles between the sites. Light absorption is dominated by submicron particles, but there is some absorption by supermicron particles ( ∼ 15 % of the total). The supermicron absorption derives from a combination of black carbon that has penetrated into the supermicron mode and from dust, and there is a clear increase in the mass absorption coefficient of just the supermicron particles with increasing average particle size. The mass scattering coefficient (MSC) for the supermicron particles was directly observed to vary inversely with the average particle size, demonstrating that MSC cannot always be treated as a constant in estimating mass concentrations from scattering measurements, or vice versa. The total particle backscatter fraction exhibited some dependence upon the relative abundance of sub- versus supermicron particles; however this was modulated by variations in the median size of particles within a given size range; variations in the submicron size distribution had a particularly large influence on the observed backscatter efficiency and an approximate method to account for this variability is introduced. The relationship between the absorption and scattering Ångström exponents is examined and used to update a previously suggested particle classification scheme. Differences in composition led to differences in the sensitivity of PM2.5 to heating in a thermodenuder to the average particle size, with more extensive evaporation (observed as a larger decrease in the PM2.5 extinction coefficient) corresponding to smaller particles; i.e., submicron particles were generally more susceptible to heating than the supermicron particles. The influence of heating on the particle hygroscopicity varied with the effective particle size, with larger changes observed when the PM2.5 distribution was dominated by smaller particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Direct Nonlinear Approximation for Security Region Boundary of Integrated Energy Systems: A Polynomial Chaos Expansion Solution

The strong interdependence of electricity, gas, and heating systems can facilitate fault propagation within integrated energy systems (IESs), posing significant challenges to secure operation. This paper proposes a polynomial chaos expansion (PCE)-based approximation method to accurately characterize the IES security region boundary (IES–SRB). By integrating the Karush-Kuhn-Tucker conditions with PCE theory, the IES-SRB approximation problem is reformulated as a set of nonlinear equations concerning the approximation coefficients. Using the Galerkin projection method, these equations are further transformed into a system of projection equations that govern the polynomial approximation coefficients in the IES-SRB approximation. To reduce computational complexity while maintaining high approximation accuracy, a piecewise polynomial approximation method is proposed. Numerical studies on the E39-G20-H6 and E118-G96-H52 IES test systems demonstrate that the proposed method can accurately and effectively construct IES security regions.

Wu, Chenghao [Northeast Electric Power University]↗
DOE OSTI2015

Electronic properties of excess Cr at Fe site in FeCr{sub 0.02}Se alloy

We have studied the effect of substitution of transition-metal chromium (Cr) in excess on Fe sub-lattice in the electronic structure of iron-selenide alloys, FeCr{sub 0.02}Se. In our calculations, we used Korringa-Kohn-Rostoker coherent potential approximation method in the atomic sphere approximation (KKR-ASA-CPA). We obtained different band structure of this alloy with respect to the parent FeSe and this may be reason of changing their superconducting properties. We did unpolarized calculations for FeCr{sub 0.02}Se alloy in terms of density of states (DOS) and Fermi surfaces. The local density approximation (LDA) is used in terms of exchange correlation potential.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Introduction of the Adding and Doubling Method for Solving Bateman Equations for Nuclear Fuel Depletion

This paper introduces and evaluates the Adding and Doubling Method (ADM) for solving the Bateman equations for depletion systems with varying numbers of nuclides and compares it to the Chebyshev Rational Approximation Method (CRAM), both implemented in the reactor physics analysis application Griffin. ADM, when applied to the Crank-Nicolson Finite Difference method, can produce results comparable in accuracy and precision to CRAM with comparable run times for systems with 35 or 297 nuclides. For systems with more than 300 nuclides, the matrix-matrix operations required by ADM are significantly more costly than the matrix-vector operations required by CRAM, making CRAM the more efficient method for systems with large numbers of nuclides. ADM is an accurate method that maintains other advantages over CRAM in that it does not depend on pre-generated coefficients or require complex number operations. ADM also manages to outperform CRAM by a factor of more than 250 in terms of run time for depletion systems that require multiple Bateman solves while the depletion matrix and time step size remain constant over all depletion intervals.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Calculation of the thermal conductivity of nanostructured Bi{sub 2}Te{sub 3} with the real phonon spectrum taken into account

The results of calculations of lattice thermal conductivity in bismuth telluride are presented and its decrease in a nanostructured material due to boundary scattering is estimated. Calculation is carried out using the lattice-dynamics method with the real phonon spectrum and the phonon–phonon interaction taken into account. Its results well agree with experimental data for the crystalline material. The estimates for the nanostructured material give a decrease in the thermal conductivity by 30% for grain sizes of 20 nm. Calculations by this method are compared with those obtained using approximate methods of description of the spectrum and scattering processes. It is shown that the least difference in the estimates (about 10%) can be obtained when using the approximation of a constant matrix element of phonon–phonon scattering with correction of the frequency dependence for acoustic modes.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Spectral partitioning with blends of eigenvectors

We report many common methods for data analysis rely on linear algebra. We provide new results connecting data analysis error to numerical accuracy in the context of spectral graph partitioning. We provide pointwise convergence guarantees so that spectral blends (linear combinations of eigenvectors) can be employed to solve data analysis problems with confidence in their accuracy. We apply this theory to an accessible model problem, the ring of cliques, by deriving the relevant eigenpairs and finding necessary and sufficient solver tolerances. Analysis of the ring of cliques provides an upper bound on eigensolver tolerances for graph partitioning problems. These results bridge the gap between linear algebra based data analysis methods and the convergence theory of iterative approximation methods. These results explain how the combinatorial structure of a problem can be recovered much faster than numerically accurate solutions to the associated linear algebra problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Stochastic DC optimal power flow with reserve saturation

We propose an optimization framework for stochastic optimal power flow with uncertain loads and renewable generator capacity. Our model follows previous work in assuming that generator outputs respond to load imbalances according to an affine control policy, but introduces a model of saturation of generator reserves by assuming that when a generator’s target level hits its limit, it abandons the affine policy and produces at that limit. This is a particularly interesting feature in models where wind power plants, which have uncertain upper generation limits, are scheduled to provide reserves to balance load fluctuations. Here, the resulting model is a nonsmooth nonconvex two-stage stochastic program, and we use a stochastic approximation method to find stationary solutions to a smooth approximation. Computational results on 6-bus and 118-bus test instances demonstrate that by considering the effects of saturation, our model can yield solutions with lower expected generation costs (at the same target line violation probability level) than those obtained from a model that enforces the affine policy to stay within generator limits with high probability.

17 WIND ENERGY↗
DOE OSTI2025

Exploring Data Set Bias and Decision Support with Predictive Uncertainty Through Bayesian Approximations and Convolutional Neural Networks

Individual seismic catalogs can contain multiscale observations from fault level to global scales and associated waveforms from discrete events reflect crustal structure across many different scales and locations. Seismic network aperture, geographic location, and observation distance may not provide informative guidance or intuition on how different catalogs will behave across models trained under different conditions. We rely on uncertainty to provide guardrails for when to trust model decisions, but understanding when our uncertainty is trustworthy is an open challenge. Here, in this work, we explore Bayesian approximation methods for assigning predictive uncertainty in seismic event classification problems. We find that computationally expensive Bayesian approximations do not outperform simple ensemble methods. We also find that when exploiting multiple seismic event catalogs, joint training with data from all the catalogs combined with Bayesian approximations and supervised training for classification can obscure bias and result in less robust uncertainty while also not providing substantial performance benefits compared to training individual models for each catalog.

58 GEOSCIENCES↗