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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Computational Fluid Dynamics Using the Adaptive Wavelet-Collocation Method

Advancements to the adaptive wavelet-collocation method over the last decade have opened up a number of new possible areas for active research. Volume penalization techniques allow complex immersed boundary conditions to be used with high efficiency for both internal and external flows. Anisotropic methods make it possible to use body-fitted meshes while still taking advantage of the dynamic adaptability properties wavelet-based methods provide. The parallelization of the approach has made it possible to perform large high-resolution simulations of detonation initiation and fluid instabilities to uncover new physical insights that would otherwise be difficult to discover. Other developments include space-time adaptive methods and nonreflecting boundary conditions. This article summarizes the work performed using the adaptive wavelet-collocation method developed by Vasilyev and coworkers over the past decade.

42 ENGINEERING↗
DOE OSTI2016

Improving Lidar Turbulence Estimates for Wind Energy

Remote sensing devices (e.g., lidars) are quickly becoming a cost-effective and reliable alternative to meteorological towers for wind energy applications. Although lidars can measure mean wind speeds accurately, these devices measure different values of turbulence intensity (TI) than an instrument on a tower. In response to these issues, a lidar TI error reduction model was recently developed for commercially available lidars. The TI error model first applies physics-based corrections to the lidar measurements, then uses machine-learning techniques to further reduce errors in lidar TI estimates. The model was tested at two sites in the Southern Plains where vertically profiling lidars were collocated with meteorological towers. Results indicate that the model works well under stable conditions but cannot fully mitigate the effects of variance contamination under unstable conditions. To understand how variance contamination affects lidar TI estimates, a new set of equations was derived in previous work to characterize the actual variance measured by a lidar. Terms in these equations were quantified using a lidar simulator and modeled wind field, and the new equations were then implemented into the TI error model.

17 WIND ENERGY↗
DOE OSTI2013

Monte Carlo solution for uncertainty propagation in particle transport with a stochastic Galerkin method

The stochastic Galerkin method (SGM) is an intrusive technique for propagating data uncertainty in physical models. The method reduces the random model to a system of coupled deterministic equations for the moments of stochastic spectral expansions of result quantities. We investigate solving these equations using the Monte Carlo technique. We compare the efficiency with brute-force Monte Carlo evaluation of uncertainty, the non-intrusive stochastic collocation method (SCM), and an intrusive Monte Carlo implementation of the stochastic collocation method. We also describe the stability limitations of our SGM implementation. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Asymptotically Compatible Reproducing Kernel Collocation and Meshfree Integration for Nonlocal Diffusion

Reproducing kernel (RK) approximations are meshfree methods that construct shape functions from sets of scattered data. We present an asymptotically compatible (AC) RK collocation method for nonlocal diffusion models with Dirichlet boundary condition. The numerical scheme is shown to be convergent to both nonlocal diffusion and its corresponding local limit as nonlocal interaction vanishes. The analysis is carried out on a special family of rectilinear Cartesian grids for a linear RK method with designed kernel support. The key idea for the stability of the RK collocation scheme is to compare the collocation scheme with the standard Galerkin scheme, which is stable. In addition, assembling the stiffness matrix of the nonlocal problem requires costly computational resources because high-order Gaussian quadrature is necessary to evaluate the integral. We thus provide a remedy to the problem by introducing a quasi-discrete nonlocal diffusion operator for which no numerical quadrature is further needed after applying the RK collocation scheme. The quasi-discrete nonlocal diffusion operator combined with RK collocation is shown to be convergent to the correct local diffusion problem by taking the limits of nonlocal interaction and spatial resolution simultaneously. The theoretical results are then validated with numerical experiments. We additionally illustrate a connection between the proposed technique and an existing optimization based approach based on generalized moving least squares.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment

The occurrence of supercooled liquid water in mixed-phase cloud (MPC) affects their cloud microphysical and radiative properties. The prevalence of MPCs in the mid- and high latitudes translates these effects to significant contributions to Earth’s radiative balance and hydrological cycle. The current study develops and assesses a radar-only, moment-based phase partition technique for the demarcation of supercooled liquid water volumes in arctic, MPC conditions. The study utilizes observations from the Ka band profiling radar, the collocated high spectral resolution lidar, and ambient temperature profiles from radio sounding deployments following a statistical analysis of 5.5 years of data (January 2014–May 2019) from the Atmospheric Radiation Measurement observatory at the North Slope of Alaska. The ice/liquid phase partition occurs via a per-pixel, neighborhood-dependent algorithm based on the premise that the partitioning can be deduced by examining the mean values of locally sampled probability distributions of radar-based observables and then compare those against the means of climatologically derived, per-phase probability distributions. Analyzed radar observables include linear depolarization ratio (LDR), spectral width, and vertical gradients of reflectivity factor and radial velocity corrected for vertical air motion. Results highlight that the optimal supercooled liquid water detection skill levels are realized for the radar variable combination of spectral width and reflectivity vertical gradient, suggesting that radar-based polarimetry, in the absence of full LDR spectra, is not as critical as Doppler capabilities. The cloud phase masking technique is proven particularly reliable when applied to cloud tops with an Equitable Threat Score (ETS) of 65%; the detection of embedded supercooled layers remains much more uncertain (ETS = 27%).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Estimating Ice Water Content for Winter Storms from Millimeter-Wavelength Radar Measurements Using a Synthesis of Polarimetric and Dual-Frequency Radar Observations

The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivity Z and the estimated total number concentration of snow particles N t and the other based on the joint use of Z, specific differential phase K DP , and the degree of riming f rim . A key element of the algorithms is to obtain the “Rayleigh-equivalent” value of Z measured at the Ka band, i.e., the corresponding Z at a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameter D m and incorporating the relationship between the dual-wavelength ratio DWR S/Ka and D m . Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D m relation and Rayleigh assumption for Ka-band K DP are valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR S/Ka can be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value of Z. As a result, the performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements.

Cloud retrieval↗
DOE OSTI2013

Coexistence Analysis of Adjacent Long Term Evolution (LTE) Systems

As the licensing and deployment of Long term evolution (LTE) systems are ramping up, the study of coexistence of LTE systems is an essential topic in civil and military applications. In this paper, we present a coexistence study of adjacent LTE systems aiming at evaluating the effect of inter-system interference on system capacity and performance as a function of some of the most common mitigation techniques: frequency guard band, base station (BS) antenna coupling loss, and user equipment (UE) antenna spacing. A system model is constructed for two collocated macro LTE networks. The developed model takes into consideration the RF propagation environment, power control scheme, and adjacent channel interference. Coexistence studies are performed for a different combination of time/frequency division duplex (TDD/FDD) systems under three different guard-bands of 0MHz, 5MHz, and 10MHz. Numerical results are presented to advice the minimum frequency guard band, BS coupling loss, and UE antenna isolation required for a healthy system operation.

adjacent channel interference↗
DOE OSTI2018

Solubility and Diffusivity: Important Metrics in the Search for the Root Cause of Light- and Elevated Temperature-Induced Degradation

Light- and elevated temperature-induced degradation (LeTID) is a detrimental effect observed under operating conditions in p-type multicrystalline silicon (mc-Si) solar cells. In this paper, we employ synchrotron-based techniques to study the dissolution of precipitates due to different firing processes at grain boundaries in LeTID-affected mc-Si. The synchrotron measurements show clear dissolution of collocated metal precipitates during firing. We compare our observations with degradation behavior in the same wafers. The experimental results are complemented with process simulations to provide insight into the change in bulk point defect concentration due to firing. Several studies have proposed that LeTID is caused by metal-rich precipitate dissolution during contact firing, and we find that the solubility and diffusivity are promising screening metrics to identify metals that are compatible with this hypothesis. While slower and less soluble elements (e.g., Fe and Cr) are not compatible according to our simulations, the point defect concentrations of faster and more soluble elements (e.g., Cu and Ni) increase after a high-temperature firing process, primarily due to emitter segregation rather than precipitate dissolution. Finally, these results are a useful complement to lifetime spectroscopy techniques, and can be used to evaluate additional candidates in the search for the root cause of LeTID.

14 SOLAR ENERGY↗
DOE OSTI2016

Improving Lidar Turbulence Estimates for Wind Energy

Remote sensing devices (e.g., lidars) are quickly becoming a cost-effective and reliable alternative to meteorological towers for wind energy applications. Although lidars can measure mean wind speeds accurately, these devices measure different values of turbulence intensity (TI) than an instrument on a tower. In response to these issues, a lidar TI error reduction model was recently developed for commercially available lidars. The TI error model first applies physics-based corrections to the lidar measurements, then uses machine-learning techniques to further reduce errors in lidar TI estimates. The model was tested at two sites in the Southern Plains where vertically profiling lidars were collocated with meteorological towers. This presentation primarily focuses on the physics-based corrections, which include corrections for instrument noise, volume averaging, and variance contamination. As different factors affect TI under different stability conditions, the combination of physical corrections applied in L-TERRA changes depending on the atmospheric stability during each 10-minute time period. This stability-dependent version of L-TERRA performed well at both sites, reducing TI error and bringing lidar TI estimates closer to estimates from instruments on towers. However, there is still scatter evident in the lidar TI estimates, indicating that there are physics that are not being captured in the current version of L-TERRA. Two options are discussed for modeling the remainder of the TI error physics in L-TERRA: machine learning and lidar simulations. Lidar simulations appear to be a better approach, as they can help improve understanding of atmospheric effects on TI error and do not require a large training data set.

17 WIND ENERGY↗
DOE OSTI2016

A harmonic balance method for PDEs

In this report, we describe some approaches to calculate the non-linear system of equations prescribed by the harmonic balance method (HB), a frequency domain analysis technique for modelling a non-linear system of partial differential equations (PDEs). The approach which we ultimately pursue can be seen as a time-collocation approach, except that the harmonic balance equations are obtained weakly (in the sense used in the calculus of variations). This weak formulation allows us to adapt existing transient or stationary PDEs models in the Panzer/Trilinos framework for frequency domain analysis via the harmonic balance method. We begin with a motivatation for the harmonic balance method and outline its mathematical formulation. We then describe some approaches to calculate the harmonic balance formulae, and their means of implementation through the modification of a Panzer tutorial problem - a stationary Helmholtz equation with a constant Dirichlet boundary condition and a non-linear source. For each of these approaches, we outline the necessary adaptations to solve the corresponding (periodically) transient Helmholtz equation with a (temporally) periodic Dirichlet boundary condition and non-linear source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Evaluation of three lidar scanning strategies for turbulence measurements

Abstract. Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.

Newman, Jennifer F.↗
DOE OSTI2022

Evaluating Grid Strength under Uncertain Renewable Generation

The increasing displacement of synchronous generators with renewable resources such as wind and solar via power electronic interfaces causes a reduction in short-circuit strength and weak grid issues. The variation and uncertainty of renewable energy increase challenges for identifying weak grid conditions. This paper proposes an efficient method to analyze the impact of uncertain renewable energy on grid strength. The proposed method uses the probabilistic collocation method (PCM) to approximate the results of grid strength assessment under uncertain renewable generation, in order to reduce computational burden without compromising result accuracy when compared with traditional Monte Carlo simulation (MCS). To improve the accuracy of the approximation results, the proposed method integrates the K-means clustering technique with PCM to select the approximation samples of input variables. The efficacy of the proposed method is demonstrated by comparison with MCS on the modified IEEE 9-bus system and modified IEEE 39-bus system with multiple renewable generators.

grid strength↗
DOE OSTI2018

Numerical approach based on fractional-order Lagrange polynomials for solving a class of fractional differential equations

In this study, we propose a new set of fractional functions based on the Lagrange polynomials to solve a class of fractional differential equations. Fractional differential equations are the best tools for modelling natural phenomenon that are elaborated by fractional calculus. Therefore, we need an accurate and efficient technique for solving them. The main purpose of this article is to generalize new functions based on Lagrange polynomials to the fractional calculus. At first, we present a new representation of Lagrange polynomials and in continue, we propose a new set of fractional-order functions which are called fractional-order Lagrange polynomials (FLPs). Besides, a general formulation for operational matrices of fractional integration and derivative of FLPs on arbitrary nodal points are extracted. These matrices are obtained using Laplace transform. The initial value problems is reduced to the system of algebraic equations using the operational matrix of fractional integration and collocation method. Also, we find the upper bound of error vector for the fractional integration operational matrix and we indicate convergence of approximations of FLPs. Illustrative examples are included to demonstrate the validity and applicability of the proposed technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Chemical Imaging of Ambient Aerosol Particles: Observational Constraints on Mixing State Parameterization

A new parameterization for quantifying the mixing state of aerosol populations has been applied for the first time to samples of ambient particles analyzed using spectro-microscopy techniques. Scanning transmission x-ray microscopy/near edge x-ray absorption fine structure (STXM/NEXAFS) and computer controlled scanning electron microscopy/energy dispersive x-ray spectroscopy (CCSEM/EDX) were used to probe the composition of the organic and inorganic fraction of individual particles collected on June 27th and 28th during the 2010 Carbonaceous Aerosols and Radiative Effects (CARES) study in the Central Valley, California. The first field site, T0, was located in downtown Sacramento, while T1 was located near the Sierra Nevada Mountains. Mass estimates of the aerosol particle components were used to calculate mixing state metrics, such as the particle-specific diversity, bulk population diversity, and mixing state index, for each sample. Both microscopy imaging techniques showed more changes over these two days in the mixing state at the T0 site than at the T1 site. The STXM data showed evidence of changes in the mixing state associated with a build-up of organic matter confirmed by collocated measurements and the largest impact on the mixing state was due to an increase in soot dominant particles during this build-up. The CCSEM/EDX analysis showed the presence of two types of particle populations; the first was dominated by aged sea salt particles and had a higher mixing state index (indicating a more homogeneous population), the second was dominated by carbonaceous particles and had a lower mixing state index.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Comparison of Daytime Low-Level Cloud Properties Derived From GOES and ARM SGP Measurements

Large-scale satellite data are critical for both verifying and improving general circulation model parameterizations of clouds and radiation for climate prediction. For reliable application of satellite data sets in cloud processes and climate models, it is important to have a reasonable estimate of the errors in the derived cloud properties. The daytime single-layered low-level cloud properties retrieved by the Geostationary Operational Environmental Satellite system (GOES) are compared with ground-based observations and retrievals over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility from June 1998 to December 2006. The GOES retrievals are made via the Visible-Infrared Solar-infrared Split-window Technique. They are spatially averaged within a 0.15° × 0.15° box centered on the ARM SGP site, and the ARM surface observations are temporally averaged ±15 min around the GOES scans to produce collocated pairs. Comparisons are made for monthly means, diurnal means, and one-to-one GOES and ARM collocated pairs. GOES T eff is highly correlated with ARM T top cloud temperature, having an R 2 value of 0.75, though GOES exhibits a cold bias. GOES-retrieved τ and liquid water path have very good agreement with ARM retrievals with R 2 s of 0.45 and 0.47, while r e (GOES), on average, is about 2 μm greater than ARM r e . An examination of solar and viewing geometry has shown that GOES-retrieved mean r e and τ values are impacted by solar zenith angle and especially scattering angle, which is not unexpected and needs to be accounted for by users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Spectral Characteristics of Daily to Seasonal Ground Motion at the Piñon Flats Observatory from Coherence of Seismic Data

We investigate coherences of seismic data recorded during three years (2015–2017) at the Piñon Flats Observatory (PY) array and a collocated 148 m deep borehole station B084, along with oceanic data from a buoy southwest of the PY array. Seismic and barometric recordings at PY stations are analyzed with a multitaper spectral technique. The coherence of signals from seismic sources is >0.6 at 0.05–8 Hz between closely spaced (<65m) surface stations and decreases to ~0.2 in frequency bands in which the wavelengths are smaller than interstation distances. There are several local coherence increases at 1–8 Hz between nearby (<65 m) surface stations, whereas large coherence values between a surface and 148 m deep borehole stations are only present at the secondary microseism (~0.14 Hz). These points to significant modification of seismic recordings in the top crust, and those continual near-surface failures might produce shallow rapidly attenuating signals at surface stations. Incoherent local atmospheric effects induce incoherent seismic signals in low- and high-frequency ranges through different coupling mechanisms. Between 0.003 and 0.05 Hz, atmospheric loadings generate ground tilts that contaminate the two horizontal seismic recordings and decrease their coherence, whereas the vertical component is less affected. At 1–8 Hz, coupling of atmospheric pressure with surface structures transmits incoherent signals into the ground, degrading the seismic coherence in all three components. The two horizontal coherences show seasonal variations with extended coherent frequency bands in winter and spring, likely to be produced by seasonal variations in microseisms and local ground tilts. The coherences also contain high anomalies between 2 and 4 Hz resulting from anthropogenic activities. The results provide useful information on instrument characteristics and variations in the shallow crustal response to earthquakes, seasonal and ambient sources of seismic energy, along with atmospheric pressure–temperature changes and anthropogenic activities.

Geochemistry & Geophysics↗
DOE OSTI2013

Minimal multi-element stochastic collocation for uncertainty quantification of discontinuous functions

We propose a multi-element stochastic collocation method that can be applied in high-dimensional parameter space for functions with discontinuities lying along manifolds of general geometries. The key feature of the method is that the parameter space is decomposed into multiple elements defined by the discontinuities and thus only the minimal number of elements are utilized. On each of the resulting elements the function is smooth and can be approximated using high-order methods with fast convergence properties. The decomposition strategy is in direct contrast to the traditional multi-element approaches which define the sub-domains by repeated splitting of the axes in the parameter space. Such methods are more prone to the curse-of-dimensionality because of the fast growth of the number of elements caused by the axis based splitting. The present method is a two-step approach. Firstly a discontinuity detector is used to partition parameter space into disjoint elements in each of which the function is smooth. The detector uses an efficient combination of the high-order polynomial annihilation technique along with adaptive sparse grids, and this allows resolution of general discontinuities with a smaller number of points when the discontinuity manifold is low-dimensional. After partitioning, an adaptive technique based on the least orthogonal interpolant is used to construct a generalized Polynomial Chaos surrogate on each element. The adaptive technique reuses all information from the partitioning and is variance-suppressing. We present numerous numerical examples that illustrate the accuracy, efficiency, and generality of the method. When compared against standard locally-adaptive sparse grid methods, the present method uses many fewer number of collocation samples and is more accurate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A New Decade in Seismoacoustics (2010–2022)

Several sources of interest often generate both low‐frequency acoustic and seismic signals due to energy propagation through the atmosphere and the solid Earth. Seismic and acoustic observations are associated with a wide range of sources, including earthquakes, volcanoes, bolides, chemical and nuclear explosions, ocean noise, and others. The fusion of seismic and acoustic observations contributes to a better understanding of the source, both in terms of constraining source location and physics, as well as the seismic to acoustic coupling of energy. Here in this review, we summarize progress in seismoacoustic data processing, including recent developments in open‐source data availability, low‐cost seismic and acoustic sensors, and large‐scale deployments of collocated sensors from 2010 to 2022. Similarly, we outline the recent advancements in modeling efforts for both source characteristics and propagation dynamics. Finally, we highlight the advantages of fusing multiphenomenological signals, focusing on current and future techniques to improve source detection, localization, and characterization efforts. This review aims to serve as a reference for seismologists, acousticians, and others within the growing field of seismoacoustics and multiphenomenology research.

58 GEOSCIENCES↗