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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Averages of b-hadron, c-hadron, and $$\tau $$-lepton properties as of 2018: Heavy Flavor Averaging Group (HFLAV)

Abstract This paper reports world averages of measurements of b -hadron, c -hadron, and $$\tau $$ τ -lepton properties obtained by the Heavy Flavour Averaging Group using results available through September 2018. In rare cases, significant results obtained several months later are also used. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, $$C\!P$$ C P violation parameters, parameters of semileptonic decays, and Cabibbo–Kobayashi–Maskawa matrix elements.

Amhis, Y. (ORCID:0000000342821512)↗
DOE OSTI2020

Investigating the Impact of Power-Take-Off System Parameters and Control Law on a Rotational Wave Energy Converter’s Peak-to-Average Power Ratio Reduction

Due to the irregular nature of real waves, the power captured in a wave energy converter (WEC) system is highly variable. This is an important barrier to the effective use of WECs. To address this challenge, this study focuses on a rotational WEC power-take-off system in which high-speed and high-efficiency generators along with a torque/power smoothing inertia element can be effectively utilized. In the first phase of this study, the U.S. Department of Energy’s reference model 3 (WEC-Sim RM3; two-body point absorber), along with a slider-crank WEC, were integrated for linear to rotational conversion. Relative motion between the float and spar in RM3 was the driving force for this slider-crank WEC, which is connected to a motor/generator set through a gearbox. RM3 geometry was scaled down by 25 times to work within the limits of the physical motor/generator set used in the experimentation. Once the integration in a hardware-in-the-loop simulation environment was successfully completed, data on the peak-to-average power ratio was collected for various wave conditions including regular and irregular waves. The control algorithm designed to keep the system in resonance with waves was able to maintain relatively high speed depending on the specific gear ratio and wave period. Initial results with hardware-in-the-loop simulations reveal that gear ratio and crank radius have a strong impact on the peak-to-average power ratio. In addition, it was found that output power from the generator was maximized at a larger gear ratio, as the crank radius was increased.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗
DOE OSTI2021

Manipulating strong electromagnetic fields with the average transverse momentum of relativistic nuclear collisions

Abstract We show that an event-shape engineering based on the mean transverse momentum of charged hadrons, $$[p_t]$$ [ p t ] , provides an optimal handle on the strength of the magnetic field created in central heavy-ion collisions at high energy. This is established through quantitative evaluations of the correlation existing between the event-by-event magnetic field produced by the spectator protons in 5.02 TeV Pb + Pb collisions and the event-by-event $$[p_t]$$ [ p t ] at a given collision centrality. We argue that the event selection based on $$[p_t]$$ [ p t ] provides a better handle on the magnetic field than the more traditional selection based on the event ellipticities. Advantages brought by this new method for the experimental search of the chiral magnetic effect are discussed.

Giacalone, Giuliano (ORCID:0000000287761034)↗
DOE OSTI2019

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

Purpose: To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI. Materials and methods: This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm{sup 2}) and one higher b value (aHBV at 2000 s/mm{sup 2}). The acquired data were postprocessed to generate two different types of trace-weighted images—using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm{sup 2}) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm{sup 2}) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores. Results: Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm{sup 2} sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time). Conclusion: Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

A combined ensemble-volume average homogenization method for lattice structures with defects under dynamic and static loading

In the study of lattices structures, both experiments and numerical simulations are often conducted with small samples. Using combined ensemble and volume averaging, this work introduces a method to extract a macroscopic constitutive response of a lattice material from numerical simulations performed in periodic domains. The domain size needed to obtain statistically accurate results is investigated. Similar to molecular dynamics, the concept of the virial stress is introduced after homogenized equations are derived using the ensemble averaging method. Under static conditions, the virial stress is shown to agree with the volume averaged solid stress. Using the homogenization method, constitutive relations for this stress can be obtained from systems with uniform strains. Application of such obtained constitutive relations to more general cases results in an error proportional to the square of the ratio between the lattice length scale and the macroscopic length scale. Taking advantage of this property, numerical simulations are performed in systems with a uniform gradient of the average velocity. The volume average method is then used to accelerate convergence when studying lattices with defects. To avoid the artificial numerical time scale from the size of a representative volume element divided by the wave speed, a numerical scheme is developed to enforce a spatially uniform velocity gradient within the computational domain while allowing fluctuations of the velocity or displacement to develop naturally. To account for probability distribution of lattice defects, the stress is calculated as the ensemble-volume averaged value. For dynamic systems, energy dissipation properties are also studied.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Filtering, averaging, and scale dependency in homogeneous variable density turbulence

We investigate relationships between statistics obtained from filtering and from ensemble or Reynolds-averaging turbulence flow fields as a function of length scale. Generalized central moments in the filtering approach are expressed as inner products of generalized fluctuating quantities, q ' ( ξ , x ) = q ( ξ ) - q ¯ ( x ) , representing fluctuations of a field q ( ξ ) , at any point ξ, with respect to its filtered value at x. For positive-definite filter kernels, these expressions provide a scale-resolving framework, with statistics and realizability conditions at any length scale. In the small-scale limit, scale-resolving statistics become zero. In the large-scale limit, scale-resolving statistics and realizability conditions are the same as in the Reynolds-averaged description. Using direct numerical simulations (DNS) of homogeneous variable density turbulence, we diagnose Reynolds stresses, T i j , resolved kinetic energy, kr, turbulent mass-flux velocity, a i , and density-specific volume covariance, b, defined in the scale-resolving framework. These variables, and terms in their governing equations, vary smoothly between zero and their Reynolds-averaged definitions at the small and large scale limits, respectively. At intermediate scales, the governing equations exhibit interactions between terms that are not active in the Reynolds-averaged limit. For example, in the Reynolds-averaged limit, b follows a decaying process driven by a destruction term; at intermediate length scales, it is a balance between production, redistribution, destruction, and transport, where b grows as the density spectrum develops and then decays when mixing becomes strong enough. This work supports the notion of a generalized, length-scale adaptive model that converges to DNS at high resolutions and to Reynolds-averaged statistics at coarse resolutions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Multilevel Parareal Algorithm with Averaging for Oscillatory Problems

The present study is an extension of the work done by Peddle, Haut, and Wingate and Haut and Wingate, where a two-level Parareal method with mapping and averaging is examined. The method proposed in this paper is a multilevel Parareal method with arbitrarily many levels, which is not restricted to the two-level case. We give an asymptotic error estimate which reduces to the two-level estimate for the case when only two levels are considered. Introducing more than two levels has important consequences for the averaging procedure, as we choose separate averaging windows for each of the different levels, which is an additional new feature of the present study. The different averaging windows make the proposed method especially appropriate for nonlinear multiscale problems, because we can introduce a level for each intrinsic scale of the problem and adapt the averaging procedure such that we reproduce the behavior of the model on the particular scale resolved by the level. The method is applied to nonlinear differential equations. The nonlinearities can generate a range of frequencies in the problem. The computational cost of the new method is investigated and studied on several examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Averaging Principle for the Higher Order Nonlinear Schrödinger Equation with a Random Fast Oscillation

This work concerns the problem associated with averaging principle for a higher order nonlinear Schrödinger equation perturbed by a oscillating term arising as the solution of a stochastic reaction–diffusion equation evolving with respect to the fast time. This model can be translated into a multiscale stochastic partial differential equations. Stochastic averaging principle is a powerful tool for studying qualitative analysis of stochastic dynamical systems with different time-scales. To be more precise, under suitable conditions, we prove that there is a limit process in which the fast varying process is averaged out and the limit process which takes the form of the higher order nonlinear Schrödinger equation is an average with respect to the stationary measure of the fast varying process. Finally, by using the Khasminskii technique we can obtain the rate of strong convergence for the slow component towards the solution of the averaged equation, and as a consequence, the system can be reduced to a single higher order nonlinear Schrödinger equation with a modified coefficient.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A practical method for modeling temporally-averaged ocean wave frequency-directional spectra for characterizing wave energy climates

Wave energy resource characterization investigations have been hindered because frequency-directional wave spectra are not broadly available for many coastal regions due to the insufficient spatial coverage of buoy observation networks and spectral wave model hindcast outputs. We address this problem by developing and validating a practical method for approximating temporally-averaged frequency-directional wave spectra averaged over periods of months or years from bulk wave parameters, which are available at a much greater coverage and resolution than frequency-directional wave spectra. While the temporally averaged frequency-directional wave spectrum over these periods cannot be used for analyzing a single sea state, it aggregates multiple sea states, identifies dominant wave energy systems representing wave climate, and resolves their spectral characteristics. Therefore, modelling temporally averaged frequency-directional wave spectra is of great value for planning and designing wave energy projects, e.g., resource characterization, site assessment, and conceptual design of wave energy converters. Temporally-averaged frequency-directional wave spectra and related important wave energy parameters approximated using this method are found to be more accurate than commonly used parametric wave spectrum models. This method can be applied to a wide range of wave climates given its universality and high accuracy. Also, the availability of bulk wave parameters from multi-decade high-resolution wave model hindcasts is increasing.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Average-atom calculations of bound-free and free-free cross sections in dense plasmas

Cross sections for photo-induced bound-free and free-free transitions in plasmas are evaluated in the average-atom approximation and applied to determine opacities of dense plasmas of light elements. Parameters characterizing the plasmas (chemical potential, average ionic charge, free electron density, bound and continuum wave functions, and occupation numbers) are obtained from the average-atom model. Lowest-order calculations of the free-free cross sections, which diverge in the low-frequency limit, are regularized by accounting for the finite electron-ion relaxation time. The resulting analysis provides the basis for average-atom studies of plasma opacities. Such studies are presented for dense lithium, beryllium, boron, and carbon. Applications are given to Rosseland mean opacities of dense hydrogen and deuterium plasmas and to comparisons of free-free to bound-free opacities in shock-compressed plasmas. Average-atom cross section and opacity calculations are extended to plasmas consisting of more than one ionic species, boron nitride, polystyrene, and a composite H, He, C plasma.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Accurate Consensus-based Distributed Averaging with Variable Time Delay in Support of Distributed Secondary Control Algorithms

We report that distributed secondary control has been widely used in hierarchical control structures, where multiple distributed generators (DGs) need to coordinate to regulate system voltage and frequency. In these systems, consensus algorithms determine the average of a group of dynamic states (e.g. voltages measured by a group of DGs). To be useful, consensus algorithms must be computationally efficient, stable and accurate. In practice, numerous practical implementation challenges significantly affect the consensus equilibrium. In this paper, we quantify the accuracy deviations of the distributed average observer algorithms proposed in the literature to demonstrate the problems with the state-of-the-art distributed averaging techniques. A novel approach is proposed that achieves accurate average tracking in the presence of time-varying communication delays among agents. In our implementation, time synchronization of all distributed controllers is enabled by a novel software platform, called Resilient Information Architecture Platform for the Smart Grid (RIAPS). The proposed distributed average observer is implemented on hardware controllers and its effectiveness is validated in a controller hardware-in-the-loop testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Spatially Averaged Ice Contents of Ice-Wedge Polygon Cross-Sections to 3-m Depth, July 2013, Utqiagvik, Alaska

This dataset contains spatially averaged estimates of ice content (volume percent) for two-dimensional cross-sectional profiles (from trough center to trough center to a depth of 3 meters) of low- and flat-centered ice-wedge polygons (three of each type) located near Utqiagvik, Alaska. A combination of soil pits, trenches, and cores were used to describe, sample, and map the cross-section stratigraphy of soil horizons and ice wedges for each polygon at 6 depth intervals. Observed soil horizons were assigned to four types with increasing amounts of organic components (mineral, mineral/organic, organic/mineral, and organic). The average ice contents of each soil horizon type below the permafrost boundary and wedge ice were weighted by their cross-sectional area fractions to calculate spatially averaged estimates of ice content for each polygon. In the active layer, spatially averaged estimates of volumetric water contents were similarly determined and reported here as “ice” content to enable estimates of the soil’s structurally competent porosity and excess ice in permafrost layers. In this dataset, the file AK13_ice_contents.csv includes cross-sectional area fractions and spatially averaged ice contents for soil layers and horizon types at the six depth intervals. The file AK13_permafrost_ice_fractions.csv contains the calculated partitioning of ice contents into pore ice and excess ice fractions for the three permafrost-dominated depth intervals. In addition, there is a data dictionary file for each of these data files and a file-level metadata file. These data were generated by the Department of Energy’s Soil Carbon Response to Environmental Change Scientific Focus Area and were used as inputs to model simulations examining the consequences of thaw-affected subsidence and microtopography change on active layer thickness of low-relief polygonal tundra landscapes in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗