Search NASA⌕ Search

SEARCH · Search NASA

Results for “Variational analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Negative Medium-Voltage Direct Current Discharges in Air under Simulated Sub-Atmospheric Pressures for All-Electric Aircraft

The increase in the global temperature due to greenhouse gas emissions is a major concern to the world. To achieve the goal of zero emissions by 2050 in the USA the practical realization of all-electric vehicles, particularly all-electric aircraft (AEA), is important. For the design of electrical power systems (EPSs) in all-electric aircraft, a bipolar medium-voltage direct current (MVDC) system of ±5 kV is being investigated. However, several challenges manifest when using such voltages in a low-pressure environment. One of the main challenges is the partial discharge (PD) behavior of the insulation. It is important to study the PD behavior of the insulation by simulating the aviation environment in the lab. This work aimed to study the partial discharge behavior of air under a negative DC voltage in a needle-to-plane electrode geometry by simulating the aviation pressures in the lab. The partial discharge inception voltage (PDIV) and the breakdown voltage (BDV) show an obvious pressure-dependent variation. Regression analysis was performed to better understand the relationship between the PDIV and pressures. Plots were drawn for the average discharge current at each voltage step until breakdown. This paper’s findings can provide valuable insight into the design of EPS for an AEA. To the best of our knowledge, such a study has not been carried out to date.

air discharge↗
DOE OSTI2020

The Cost of Floating Offshore Wind Energy in California Between 2019 and 2032

California’s energy planning is centered around meeting the emissions reduction and renewable energy requirements of Senate Bill 350 by 2030. However, state power system planning is expected to eventually address California’s requirement to achieve 100% of total retail electricity sales from renewable energy and zero-carbon resources by 2045, as mandated by Senate Bill 100. To comply with these directives, California needs to investigate the further development of energy efficiency, storage, and a diverse range of renewable energy, zero-carbon emission, and transmission resources, including offshore wind. Wind resources off the coast of California have the potential to generate a significant portion of the state’s electric energy as it moves toward a zero-carbon economy and can help diversify its energy mix. Floating offshore wind technology, which is suitable for the deep waters along the California coast, is currently in a precommercial phase, with approximately 84 megawatts (MW) installed worldwide at the end of 2019. Globally there are over 7,000 MW in planning and permitting phases of development, with the first commercial-scale projects expected to be operational in 2024. This study provides site-specific cost and performance data for floating offshore wind to inform California’s long-term energy planning. The identification of new resources to meet California’s policy goals at least cost is part of the Integrated Resource Planning (IRP) process, which is coordinated by the California Public Utilities Commission (CPUC). In 2019–2020 IRP modeling, offshore wind was included for the first time as a candidate resource in some sensitivity cases (CPUC 2019). The data and information presented in this report can be used to update offshore wind inputs in future IRP cycles. The authors conducted a geospatial cost analysis over portions of the offshore wind resource area of California. The analyzed spatial domain includes sites with a mean wind speed of at least 7 meters per second and water depths between 40 meters (m) and 1,300 m. Costs and energy production vary across this analysis domain. We calculated these parameters on a grid layout with over 750 sites, with each site representing a 1,000-MW commercial offshore wind power plant. Levelized cost of energy (LCOE) was calculated at each site over the analysis domain. The resulting variation in LCOE across the analysis domain is illustrated through heat maps in this report. Five study areas were selected within the analysis domain where more detailed cost analysis was conducted and cost parameters, such as annual energy production, capital cost expenditures (CapEx), operational cost expenditures (OpEx), and net capacity factors are reported. These five study areas include Morro Bay, Diablo Canyon, Humboldt, Cape Mendocino and Del Norte.

17 WIND ENERGY↗
DOE OSTI2025

Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube

This study presents an analysis of seasonal variations in the atmospheric muon neutrino flux, using 11.3 years of data from the IceCube Neutrino Observatory. By leveraging a novel spectral unfolding method, we explore the energy range from 125 GeV to 10 TeV for zenith angles from 90° to 110°, corresponding to the Antarctic atmosphere. Our findings reveal that the differential measurement of the amplitudes of the seasonal variation is consistent with an energy-dependent decrease reaching (-4.5 ± 1.2)% during Austral winter and increase to (+ 3.9 ± 1.3)% during Austral summer relative to the annual average at 10 TeV. While the unfolded flux exceeds the model predictions by up to 30%, the differential measurement of the seasonal to annual average flux remains unaffected. The measured seasonal variations of the muon neutrino spectrum are consistent with theoretical predictions using the MCEq code and the NRLMSISE-00 atmospheric model.

Astroparticle Physics and High-Energy Cosmic Pheno↗
DOE OSTI2022

Spatiotemporal Variations of Evapotranspiration in Amazonia Using the Wavelet Phase Difference Analysis

The relationships and seasonal-to-annual variations among evapotranspiration (ET), precipitation (P), terrestrial water storage anomalies (TWSA), radiation (downward shortwave radiation, DSR), and phenology (leaf area index, LAI) are complex across the Amazon basin. Here, to analyze how ET is controlled by these influencing factors, we used wavelet phase difference (WPD) to investigate the effects of P, TWSA, DSR, and LAI on ET at different spatiotemporal scales. The Amazon-scale averaged ET has strong correlations with these factors at the annual and multi-year periodicities. The patterns of WPDs have south-north and west-east divides due to the significant variation in climatic conditions. The results demonstrate that ET is mainly affected by water and energy availability while vegetation regulates both processes. The deep soil moisture/groundwater can provide strong subsidies to ET during the meteorological dry season in the water-limited area of Amazon. The WPD can well reflect the responses of ET to the variations of P, TWSA, DSR, and LAI, and the process of vegetation sustaining ET in the dry years in the water-limited area of the Amazon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Covariance-Free Bifidelity Control Variates Importance Sampling for Rare Event Reliability Analysis

Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems, particularly when failure is a rare event. To implement multifidelity modeling, estimators that efficiently combine information from multiple models/sources are necessary. In past works, the variance reduction techniques of control variates (CV) and importance sampling (IS) have been leveraged for this task. In this paper, we present the CVIS framework—a creative take on a coupled CV and IS estimator for bifidelity reliability analysis. The framework addresses some of the practical challenges of the CV method by using an estimator for the control variate mean and sidestepping the need to estimate the covariance between the original estimator and the control variate through a clever choice for the tuning constant. Furthermore, the task of selecting an efficient IS distribution is also considered, with a view towards maximally leveraging the bifidelity structure and maintaining expressivity. Additionally, a diagnostic is provided that indicates both the efficiency of the algorithm as well as the relative predictive quality of the models utilized. Finally, the behavior and performance of the framework is explored through analytical and numerical examples.

Markov chain Monte Carlo↗
DOE OSTI2025

Analysis of Polarized Dust Emission Using Data from the First Flight of SPIDER

Using data from the first flight of Spider and from the Planck High Frequency Instrument, we probe the properties of polarized emission from interstellar dust in the Spider observing region. Component-separation algorithms operating in both the spatial and harmonic domains are applied to probe their consistency and to quantify modeling errors associated with their assumptions. Analyses of diffuse Galactic dust emission spanning the full Spider region demonstrate (i) a spectral energy distribution that is broadly consistent with a modified-blackbody (MBB) model with a spectral index of β d = 1.45 ± 0.05 (1.47 ± 0.06) for E (B)-mode polarization, slightly lower than that reported by Planck for the full sky; (ii) an angular power spectrum broadly consistent with a power law; and (iii) no significant detection of line-of-sight polarization decorrelation. Tests of several modeling uncertainties find only a modest impact (~10% in σ r ) on Spider's sensitivity to the cosmological tensor-to-scalar ratio. The size of the Spider region further allows for a statistically meaningful analysis of the variation in foreground properties within it. Assuming a fixed dust temperature T d = 19.6 K, an analysis of two independent subregions of that field results in inferred values of β d = 1.52 ± 0.06 and β d = 1.09 ± 0.09, which are inconsistent at the 3.9σ level. Furthermore, a joint analysis of Spider and Planck 217 and 353 GHz data within one subregion is inconsistent with a simple MBB at more than 3σ, assuming a common morphology of polarized dust emission over the full range of frequencies. This evidence of variation may inform the component-separation approaches of future cosmic microwave background polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

An evaluation of air quality in major urban areas of India

Rapid economic growth and burgeoning population have contributed to enhanced levels of PM 2.5 concentrations in urban regions of India. Evaluation of ambient air quality facilitates the assessment of effectiveness of emission control measures and early identification of new sources. This study provides a comprehensive statistical analysis of PM 2.5 concentrations in key urban areas across India, including Delhi, Kolkata, Mumbai, Chennai, Hyderabad, and several regional centers. Data from 2017 to 2023 was analyzed using trend analysis, cluster analysis, principal component analysis, and geostatistical interpolation to understand spatiotemporal variations and sources. The analysis reveals significant differences in spatial distribution of PM 2.5 concentrations with high annual averages in urban regions in Indo-Gangetic plain (82–123 μg m −3 ) and relatively lower concentrations (29–46 μg m −3 ) in southern urban areas of Kerala, Tamil Nadu and Andhra Pradesh. Delhi state had the highest 24-averaged PM 2.5 concentrations (112 μg m −3 ) followed by urban regions in Uttar Pradesh, Bihar and West Bengal (94 μg m −3 ). Trend analysis from 2017 to 2023 revealed an overall 2.5% decline in site-wide PM2.5 concentrations, with the exception of Ludhiana, which exhibited a consistent annual increase of 10%. Principal component analysis (PCA) attributes 30% of the variance to wintertime emissions, 13% to biomass burning, and 18% to the regional haze in the northern Indo-Gangetic Plain. Different analyses clearly demonstrates the contribution of biomass burning to pollution in Delhi and surrounding cities. Transboundary pollution to Kolkata is likely from the highly polluted region in Indo-Gangetic Plain. Coastal cities of Mumbai and Chennai has relatively lower pollution attributed to the influence of sea breeze dilution, with mostly local contribution and some potential transport from upwind industry clusters. Hyderabad also has local contribution due to high density of vehicular traffic and local small industries. This study shows that mitigation efforts targeting clusters of regions should be undertaken to curb the high PM2.5 pollution. Policy measures should be implemented both at local and the intra-state level to address shared sources and transport of pollution.

Hysplitbacktrajectories↗
DOE OSTI2025

The DESI Y1 RR Lyrae catalog I: Empirical modeling of the cyclic variation of spectroscopic properties and a chemodynamical analysis of the outer halo

We present the catalog of RR Lyrae stars observed in the first year of operations of the Dark Energy Spectroscopic Instrument (DESI) survey. This catalog contains 6,240 RR Lyrae stars out to $\sim100$ kpc from the Galactic center and over 12,000 individual epochs with homogeneously-derived stellar atmospheric parameters. We introduce a novel methodology to model the cyclical variation of the spectroscopic properties of RR Lyrae from single-epoch measurements. We employ this method to infer the radial velocity and effective temperature variation of fundamental mode and first-overtone RR Lyrae stars and to determine their systemic velocities and mean temperatures. For fundamental mode pulsators, we obtain radial velocity curves with amplitudes of $\sim$30--50 km s$^{-1}$ and effective temperature curves with 300--1,000 K variations, whereas for first-overtone pulsators these amplitudes are $\sim20$ km s$^{-1}$ and $\sim 600$ K, respectively. We use our sample to study the metallicity distribution of the halo and its dependence on Galactocentric distance ($R_{\rm GC}$). Using a radius-dependent mixture model, we split the data into chemodynamically distinct components and find that our inner halo sample ($R_{\rm GC}\lesssim50$ kpc) is predominantly composed of stars with [Fe/H] $\sim-1.5$ dex and largely radial orbits (with an anisotropy parameter $\beta\sim0.94$), that we associate with the Gaia-Sausage-Enceladus merger event. Stars in the outer halo field exhibit a broader and more metal-poor [Fe/H] distribution with more circular orbits ($\beta\sim0.39$). The metallicity gradient of the metal-rich and the metal-poor components is found to be $0.005$ and $0.010$ dex kpc$^{-1}$, respectively. Our catalog highlights DESI's tantalizing potential for studying the Milky Way and the pulsation properties of RR Lyrae stars in the era of large spectroscopic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Analysis of Compressibility Effects and Nonlinear Property Variations in a Supercritical CO2 Mixing Layer

Calculations are performed using the large eddy simulation technique to qualitatively assess the effects of fluid compressibility and thermodynamic nonlinearities on the dynamics of a supercritical flow field. Resulting data are also used to interrogate instantaneous subfilter-scale fields, as modeled by the mixed-dynamic Smagorinsky closure and gradient diffusion model. A three-dimensional wall-resolved calculation of a spatially evolving mixing layer composed solely of carbon dioxide is performed. This is followed by a coarse grid calculation to examine model performance as a function of resolution. Theoretical analysis indicates that the partial derivatives of density with respect to pressure and temperature are important modulators of the temperature and pressure field evolution, respectively. Results pertaining to subfilter velocity-velocity and velocity-temperature fields indicate that the models are most stressed in the regions where compressibility and thermo-fluid nonlinearities dominate the physics.

42 ENGINEERING↗
DOE OSTI2022

Genetic mapping of sugarcane aphid resistance in sorghum line SC112-14

Sugarcane aphid [Melanaphis sacchari (Zehntner)] is a destructive pest that has had an economic effect on sorghum in North America since 2013. The identification, development, and use of resistant sorghum germplasm is the most feasible strategy to control the pest. Nevertheless, the genetic control of sugarcane aphid (SCA) resistance is unknown for most sorghum resistant lines. To identify the genetic regions that confer SCA resistance in sorghum line SC112-14, 103 recombinant inbred lines (RILs) derived by its cross with the susceptible line PI 609251 were evaluated for their SCA resistance response in Georgia during two consecutive years. The resistance response was determined based on two ratings (2 wk apart) for aphid population size (APS) and aphid-induced plant damage (APD) each year. Segregation for SCA resistance was observed for the first APS and both APD ratings, and the broad-sense heritability estimate ranged from .71 to .76, respectively. A quantitative trait locus analysis using a high-density linkage map of 3,852 single nucleotide polymorphisms (SNPs) detected an 81-kb genomic region on chromosome 6 that explained 50–55% of the phenotypic variation. Comparative mapping analysis found that the resistance locus in SC112-14 is located 8- and 10-cM upstream of the Henong 16 (RMES1) and Tx2783 resistance loci, respectively, and encloses the SNP Sbv3.1_06_2316351 associated in Haitian resistant lines. Therefore, the line SC112-14 is an additional SCA resistance source that can be combined or strategically used with other resistance sources to assure a more robust host plant resistance to the SCA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Sensitivity Analysis of Modal Parameters of a Jacket Offshore Wind Turbine to Operational Conditions

Accurate estimation of offshore wind turbine (OWT) modal parameters has a prominent effect on the design loads, lifetime prediction, and dynamic response of the system. Modal parameters can vary during the operation of OWTs. This paper studies the variation and sensitivity analysis of an OWT’s modal parameters with respect to operational and environmental conditions. Three finite element models of a jacket-supported OWT at the Block Island Wind Farm are created within the OpenSees, SAP2000, and OpenFAST platforms and validated using experimental measurements. The OpenFAST model is used to simulate the modal parameters of the turbine under various wind speed, rotor speed, power, yaw angle, mean sea level, blade pitch angle, and soil spring values. The model-predicted modal parameters of the first fore–aft (FA) and side–side (SS) modes are compared to those identified from experimental measurements. Results from the simulations show that the first FA natural frequency and damping ratio mostly depend on the rotor speed and wind speed, respectively, while yaw angle and mean sea level do not have a visible effect. It is observed that there is about 8% stiffening in the first FA frequency and an aerodynamic damping of 7.5% during the operation of the OWT.

17 WIND ENERGY↗
DOE OSTI2026

Validation of the DESI DR2 Ly$α$ forest full-shape analysis

We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$α$ (Ly$α$) forest full-shape analysis. This analysis combines three-dimensional Ly$α$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$α$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$$h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $fσ_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$α$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$α$ forest studies.

Herbold, M. [Chicago U., KICP; Ohio State U.] (ORC↗
DOE OSTI2024

Antiferromagnetic Ordering in Quasi-One-Dimensional FeBi 4 S 7

Here, we report a detailed study of the synthesis, composition, magnetic structure, and transport properties of a quasi-one-dimensional antiferromagnet FeBi 4 S 7 that contains chains of edge-sharing FeS 6 octahedra. High-resolution powder X-ray diffraction (PXRD) analysis, aided by variation of synthetic conditions, suggests that the true formula of the material is Fe 1.2 Bi 3.8 S 7 , due to the minor substitution of Fe into Bi sites. This finding is in agreement with crystal structure refinement from neutron powder diffraction data as well as with the small band gap of 0.23 eV determined from electrical transport measurements. Analysis of the neutron diffraction pattern collected below the antiferromagnetic ordering temperature of 64 K revealed ferromagnetic coupling between the Fe moments in the chains of FeS 6 octahedra. The overall ordering, however, is antiferromagnetic due to the antiparallel arrangement of moments on neighboring chains. The collinear spin arrangement is described by a k-vector (1, 0, 1/2), which indicates doubling of the unit cell in the c direction and the loss of the C-centering translation as compared to the nuclear cell. The ferromagnetic nature of the sulfide-bridged chains of Fe 2+ ions in FeBi 4 S 7 , in contrast to the antiferromagnetic coupling between Fe moments in compounds with similar structural fragments, can be justified by the analysis of metric parameters that characterize the Fe–S bonding in these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elliptically-Contoured Tensor-variate Distributions with Application to Image Learning

Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate for data arising from distributions with heavier or lighter tails. We study a general family of elliptically contoured (EC) TV distributions and derive its characterizations, moments, marginal, and conditional distributions. We describe procedures for maximum likelihood estimation from data that are (1) uncorrelated draws from an EC distribution, (2) from a scale mixture of the TVN distribution, and (3) from an underlying but unknown EC distribution, for which we extend Tyler’s robust estimator. A detailed simulation study highlights the benefits of choosing an EC distribution over the TVN for heavier-tailed data. We develop TV classification rules using discriminant analysis and EC errors and show that they better predict cats and dogs from images in the Animal Faces-HQ dataset than the TVN-based rules. A novel tensor-on-tensor regression and TV analysis of variance (TANOVA) framework under EC errors is also demonstrated to better characterize gender, age, and ethnic origin than the usual TVN-based TANOVA in the celebrated labeled faces of the wild dataset.

97 MATHEMATICS AND COMPUTING↗