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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators under Mesh Refinement

This paper analyzes a popular computational framework to solve infinite-dimensional Bayesian inverse problems, discretizing the prior and the forward model in a finite-dimensional weighted inner product space. We demonstrate the benefit of working on a weighted space by establishing operator-norm bounds for finite element and graph-based discretizations of Matérn-type priors and deconvolution forward models. For linear-Gaussian inverse problems, we develop a general theory to characterize the error in the approximation to the posterior. We also embed the computational framework into ensemble Kalman methods and MAP estimators for nonlinear inverse problems. Furthermore, our operator-norm bounds for prior discretizations guarantee the scalability and accuracy of these algorithms under mesh refinement.

Bayesian inverse problem↗
DOE OSTI2017

Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators: Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators

Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power time series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.

17 WIND ENERGY↗
DOE OSTI2018

Median statistics estimate of the galactic rotational velocity

We compile a complete collection of 18 recent (from 2000 to 2017) measurements of Θ 0 , the rotational velocity of the Milky Way at R 0 (the radial distance of the Sun from the Galactic center). These measurements use tracers that are believed to more accurately reflect the systematic rotation of the Milky Way. Unlike other recent compilations of Θ 0 , our collection includes only independent measurements. We find that these 18 measurements are distributed in a mildly non-Gaussian fashion and a median statistics estimate indicates Θ 0 = 220 ± 10 kms –1 (2σ error) as the most reliable summary, at R 0 = 8.0 ± 0.3 kpc (2σ error).

(cosmology:) cosmological parameters↗
DOE OSTI2021

Stochastically estimated covariance matrices for independent and cumulative fission yields in the ENDF/B-VIII.0 and JEFF-3.3 evaluations

A Monte-Carlo method for the generation of correlation and covariance matrices for independent and cumulative fission yields has been developed. The method uses a constrained Monte-Carlo resampling structure in order to vary evaluated fission yield libraries in a way that meets basic conservation principles. This results in the generation of correlation/covariance matrices with limited model bias and uncertainty; the matrices are primarily reflective of the evaluated fission yield uncertainties and correlations that arise from the evaluation process. This method has been applied to generate correlation and covariance matrices for all of the fissioning systems of the ENDF/B-VIII.0 and JEFF-3.3 evaluations, marking the first time such matrices have been generated for all of these systems. These covariance matrices have been published online for immediate public use. These correlation and covariance matrices can be used to improve uncertainty estimation in calculations of reactor antineutrino emission rates, decay heat problems, and nuclear forensics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Potential Economic Values of Low-Vapor-Pressure Gasoline-Range Bio-Blendstocks: Property Estimation, and Blending Optimization

Adding non-traditional blendstocks derived from biomass into gasoline has gained renewed interest since it will reduce greenhouse gas emissions and potentially enhance fuel properties and boost engine efficiencies. A competitive bio-blendstock candidate should have either lower prices or superior properties or both relative to conventional gasoline blending components. Gasoline is a mixture of hundreds compounds specified by properties rather than compositions. The addition of bio-blendstocks, most likely oxygenates, will modify the property mixing rules due to the non-ideal interactions between polar and nonpolar components. This paper presents an equation-of-state-based model for predicting Reid vapor pressure, reduced order non-linear property blending models for computing key properties of final gasoline products, and a blending optimization approach to identify key economic drivers. This paper also evaluates the economic values of bio-blendstocks to petroleum refiners using those models. In additional to ethanol, six low-vapor-pressure bio-blendstock candidates were evaluated: i-propanol, n-propanol, i-butanol, diisobutylene, cyclopentanone, and a mixture of furans. Reid vapor pressure, distillation temperatures, and octane numbers were identified as the key economic drivers of adding bio-blendstock. The economic values of those bio-blendstocks range from 2.22 to 4.00 US dollar per gasoline gallon equivalent in 2013 to 2017 5-year averaged price basis. The bio-blendstocks with higher octane numbers may have higher economic values. The uncertainties in property predictions may lead to roughly 15% deviation in the economic value evaluation.

Jiang, Yuan↗
DOE OSTI2014

A New Approach to Estimating the Probability for β-delayed Neutron Emission

The probability for neutron emission following β decay, Pn, is a crucial property for a wide range of physics and applications including nuclear structure, r-process nucleosynthesis, the control of nuclear reactors, and the post-processing of nuclear fuel. Despite much experimental effort, knowledge of Pn values is still lacking in very neutron-rich nuclei, requiring predictions from either systematics or theoretical models. Traditionally, systematic predictions were made by investigating the Pn value as a function of the decay Q value and the neutron separation energy in the daughter nucleus. A new approach to Pn systematics is presented which incorporates the half-life of the decay and the Q value for β-delayed neutron emission. This prescription correlates the known data better, and thus improves the estimation of Pn values for neutron-rich nuclei. Such an approach can be applied to generate input values for r-process network calculations or in the modeling of advanced fuel cycles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Efficient Algorithms for Estimating the Absorption Spectrum within Linear Response TDDFT

We present a special symmetric Lanczos algorithm and a kernel polynomial method (KPM) for approximating the absorption spectrum of molecules within the linear response time-dependent density functional theory (TDDFT) framework in the product form. In contrast to existing algorithms, the new algorithms are based on reformulating the original non-Hermitian eigenvalue problem as a product eigenvalue problem and the observation that the product eigenvalue problem is self-adjoint with respect to an appropriately chosen inner product. This allows a simple symmetric Lanczos algorithm to be used to compute the desired absorption spectrum. The use of a symmetric Lanczos algorithm only requires half of the memory compared with the nonsymmetric variant of the Lanczos algorithm. The symmetric Lanczos algorithm is also numerically more stable than the nonsymmetric version. The KPM algorithm is also presented as a low-memory alternative to the Lanczos approach, but the algorithm may require more matrix-vector multiplications in practice. We discuss the pros and cons of these methods in terms of their accuracy as well as their computational and storage cost. Applications to a set of small and medium-sized molecules are also presented.

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

UNVEILING THE NATURE OF THE UNIDENTIFIED GAMMA-RAY SOURCES. V. ANALYSIS OF THE RADIO CANDIDATES WITH THE KERNEL DENSITY ESTIMATION

Nearly one-third of the γ-ray sources detected by Fermi are still unidentified, despite significant recent progress in this area. However, all of the γ-ray extragalactic sources associated in the second Fermi-LAT catalog have a radio counterpart. Motivated by this observational evidence, we investigate all the radio sources of the major radio surveys that lie within the positional uncertainty region of the unidentified γ-ray sources (UGSs) at a 95% level of confidence. First, we search for their infrared counterparts in the all-sky survey performed by the Wide-field Infrared Survey Explorer (WISE) and then we analyze their IR colors in comparison with those of the known γ-ray blazars. We propose a new approach, on the basis of a two-dimensional kernel density estimation technique in the single [3.4] – [4.6] – [12] μm WISE color-color plot, replacing the constraint imposed in our previous investigations on the detection at 22 μm of each potential IR counterpart of the UGSs with associated radio emission. The main goal of this analysis is to find distant γ-ray blazar candidates that, being too faint at 22 μm, are not detected by WISE and thus are not selected by our purely IR-based methods. We find 55 UGSs that likely correspond to radio sources with blazar-like IR signatures. An additional 11 UGSs that have blazar-like IR colors have been found within the sample of sources found with deep recent Australia Telescope Compact Array observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparison of Load Models for Estimating Electrical Efficiency in DC Microgrids: Preprint

This paper compares several electrical load models for estimating the efficiency of DC vs. AC distribution in microgrids. Candidate models include energy balance, harmonic power flow, and time-domain modeling. Model results are compared with numerical studies and validated with experimental measurements. Based on quantitative and qualitative considerations, the most appropriate load modeling approach for larger-scale DC distribution efficiency studies is proposed.

DC distribution↗
DOE OSTI2018

Secondary Ion Mass Spectrometry Methodology for Isotopic Ratio Measurement of Micro‐Grains in Thin Sections: True Grain Size Estimation and Deconvolution of Inter‐Grain Size Gradients and Intra‐Grain Radial Gradients

In a thin section, grains that were approximately spherical in situ appear circular in cross section, and the distribution of apparent diameters frequently assumed to be their size distribution. Scanning ion imaging by secondary ion mass spectrometry (SIMS) is capable of providing precise (< 1‰) stable isotope ratio measurements of such grains, but, importantly, also registers their rate of evolution in apparent size as they are ablated by the primary beam. By assessing rates of radius change with depth, the described methodology enables the ‘true’ size of grains to be estimated, as well as the distance of the sectioned surface from the original grain centre. Transects in three dimensions are made possible, and this capability enables better identification (and thus separation) of both inter‐grain chemical signatures as a function of grain size, and intra‐grain radial trends. In this example, we highlight the specific application to pyrite (FeS 2 ) minerals, which are frequently analysed by SIMS to determine their inter‐grain and intra‐grain geochemical variations, particularly in their sulfur stable isotopic ratios (δ 34 S). Benefits of the new methodology over the Faraday cup ‘spot mode’ are described. Data correction algorithms and precision considerations are discussed.

Jones, Clive↗
DOE OSTI2017

NPQ (T) : a chlorophyll fluorescence parameter for rapid estimation and imaging of non-photochemical quenching of excitons in photosystem-II-associated antenna complexes: New, rapid probe of non-photochemical quenching

In photosynthesis, light energy is absorbed by light-harvesting complexes and used to drive photochemistry. However, a fraction of absorbed light is lost to non-photochemical quenching (NPQ) that reflects several important photosynthetic processes to dissipate excess energy. Currently, estimates of NPQ and its individual components (q E , q I , q Z and q T ) are measured from pulse-amplitude-modulation (PAM) measurements of chlorophyll fluorescence yield and require measurements of the maximal yield of fluorescence in fully dark-adapted material (F m ), when NPQ is assumed to be negligible. Unfortunately, this approach requires extensive dark acclimation, often precluding widespread or high-throughput use, particularly under field conditions or in imaging applications, while introducing artefacts when F m is measured in the presence of residual photodamaged centres. To address these limitations, we derived and characterized a new set of parameters, NPQ (T) , and its components that can be (1) measured in a few seconds, allowing for high-throughput and field applications; (2) does not require full relaxation of quenching processes and thus can be applied to photoinhibited materials; (3) can distinguish between NPQ and chloroplast movements; and (4) can be used to image NPQ in plants with large leaf movements. Finally, we discuss the applications benefits and caveats of both approaches.

chlorophyll fluorescence↗
DOE OSTI2017

Remotely sensed physical property estimation from powder contaminated surfaces

It is the intent of this paper to demonstrate the veracity of a method to estimate the total solid contaminant mass present on a sparsely coated surface encompassing a pixel from longwave infrared spectra. Sparsely coated surfaces create complex radiometry due to the interactions of electromagnetic energy between intimate materials. Current algorithms can be used on intimate mixtures to identify the abundances of materials in a pixel, but they cannot provide additional property information. Radiative transfer models can create mixture signatures, but only with a set of well-characterized physical parameters that are typically not known or are difficult to retrieve. Finally, the approach described here creates a parameter inversion model from a radiative transfer model and uses empirically measured mixture data to retrieve physical characteristics of the contaminated surface and derive a total contaminant mass present.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Estimation of grain boundary segregation enthalpy and its role in stable nanocrystalline alloy design

Grain boundary segregation provides a method for stabilization of nanocrystalline metals—an alloying element that will segregate to the boundaries can lower the grain boundary energy, attenuating the driving force for grain growth. The segregation strength relative to the mixing enthalpy of a binary system determines the propensity for segregation stabilization. This relationship has been codified for the design space of positive enthalpy alloys; unfortunately, quantitative values for the grain boundary segregation enthalpy exist in only very few material systems, hampering the prospect of nanocrystalline alloy design. We present a Miedema-type model for estimation of grain boundary segregation enthalpy, with which potential nanocrystalline phase-forming alloys can be rapidly screened. Calculations of the necessary enthalpies are made for ~2500 alloys and used to make predictions about nanocrystalline stability.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Estimating U.S. Methane Emissions from the Natural Gas Supply Chain. Approaches, Uncertainties, Current Estimates, and Future Studies

A growing number of studies have raised questions regarding uncertainties in our understanding of methane (CH 4 ) emissions from fugitives and venting along the natural gas (NG) supply chain. In particular, a number of measurement studies have suggested that actual levels of CH 4 emissions may be higher than estimated by EPA" tm s U.S. GHG Emission Inventory. We reviewed the literature to identify the growing number of studies that have raised questions regarding uncertainties in our understanding of methane (CH 4 ) emissions from fugitives and venting along the natural gas (NG) supply chain.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Mean Estimate Distances for Galaxies with Multiple Estimates in NED-D

Numerous research topics rely on an improved cosmic distance scale (e.g., cosmology, gravitational waves) and the NASA/IPAC Extragalactic Database of Distances (NED-D) supports those efforts by tabulating multiple redshift-independent distances for 12,000 galaxies (e.g., Large Magellanic Cloud (LMC) zero-point). Six methods for securing a mean estimate distance (MED) from the data are presented (e.g., indicator and Decision Tree). All six MEDs yield surprisingly consistent distances for the cases examined, including for the key benchmark LMC and M106 galaxies. The results underscore the utility of the NED-D MEDs in bolstering the cosmic distance scale and facilitating the identification of systematic trends.

79 ASTRONOMY AND ASTROPHYSICS↗