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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A New Window into the Baryon Cycle at Cosmic Noon with Line Intensity Mapping: Forecasts for auto- and cross-correlations in [CII]-158$μ$m, HI 21 cm, CO$_{J+1\rightarrow J}$, and H$α$ galaxies

Across the peak of cosmic star formation at $z\sim1-2$, inflow, processing, and feedback drive rapid changes in the spatial distribution and chemical composition of baryons in galaxies and surrounding reservoirs; this baryon cycle can be tomographically mapped by line intensity mapping (LIM) of atomic hydrogen, ionized carbon, and carbon monoxide. We present a simulation-based forecasting framework for detecting auto- and cross-power spectra between spectroscopic surveys of four such tracers at $z\sim0.5-1.7$ mapping the same deep field - TIM, EoRSpec/FYST, MeerKAT, & Euclid. We forward-model 3-D distributions for these tracers from magnetohydrodynamic simulations, directly capturing the two-halo, one-halo, and shot statistics without relying on analytical decompositions. We further detail a signal-to-noise formalism, tailored to LIM surveys with highly anisotropic geometries and Fourier-space coverage. We demonstrate that galaxy cross-correlations will be the dominant discovery channel for current-generation surveys. These instruments will detect the auto-spectra for CO and HI 21 cm and the CO $\times$ 21 cm cross-spectrum at modest S/N $\sim 1-10$, while placing upper limits on the [CII]-158$μ$m signals. [CII], CO, and HI LIM will be $\sim3-30\times$ ($0.5-1.5$ dex) more sensitive to cross-correlation with the Euclid survey, however, than their respective auto-correlations, constraining all three models of line emission at high significance (S/N $\sim 10-40$) within this decade. Finally, we formulate a staged instrumental trajectory with planned or reasonable improvements, including the as-proposed SKA-Mid. We forecast advancing the per-$k$-mode sensitivities of each auto-, galaxy-line, and line-line spectrum by several orders of magnitude, enabling new percent- and sub-percent level constraints on cosmology and the redshift evolution of star formation and the baryon cycle.

Agrawal, Shubh [Pennsylvania U., Dept. Math.]↗
DOE OSTI2019

Non-targeted discovery-based analysis for gas chromatography with mass spectrometry: A comparison of peak table, tile, and pixel-based Fisher ratio analysis

The ability to discover minute differences between samples or sample classes for gas chromatography coupled to mass spectrometry (GC-MS) can be a challenging endeavor, especially when those differences are not a priori . Fisher ratio (F-ratio) analysis is an apt technique to probe the differences between GC-MS chromatograms. F-ratio analysis is a supervised, non-targeted, discovery-based method that compares two different samples (or sample classes) to reduce the GC-MS dataset into a hit list composed of class distinguishing compounds. Three different F-ratio techniques, peak table, tile, and pixel-based were used to “discover” nine non-native analytes that were spiked into gasoline at four different nominal concentrations of 250, 85, 25, 5 parts-per-million (ppm). For the tile and pixel-based F-ratio calculations, a novel methodology is introduced to improve the sensitivity of the F-ratio calculations while reducing false positives. Furthermore, we use a combinatorial technique using null class comparisons, termed null distribution analysis, to determine a statistical F-ratio cutoff for analysis of the hit lists. The pixel-based algorithm was the most sensitive method and was able to “discover” all nine spiked analytes at a nominal concentration of 250 ppm albeit with one false positive interspersed towards the bottom of the hit list. The pixel-based software was also able to “discover” more of the spiked analytes at the lower concentrations with seven of the spiked analytes “discovered” at 85 ppm, four of the spiked analytes “discovered” at 25 ppm, and one analyte “discovered” at 5 ppm.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System

High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1980

Analytical and experimental study of mean flow and turbulence characteristics inside the passages of an axial flow inducer

The inviscid and viscid effects existing within the passages of a three bladed axial flow inducer operating at a flow coefficient of 0.065 are investigated. The blade static pressure and blade limiting streamline angle distributions were determined and the three components of mean velocity, turbulence intensities, and turbulence stresses were measured at locations inside the inducer blade passage utilizing a rotating three sensor hotwire probe. Applicable equations were derived for the hotwire data reduction analysis and solved numerically to obtain the appropriate flow parameters. The three dimensional inviscid flow in the inducer was predicted by numerically solving the exact equations of motion, and the three dimensional viscid flow was predicted by incorporating the dominant viscous terms into the exact equations. The analytical results are compared with the experimental measurements and design values where appropriate. Radial velocities are found to be of the same order as axial velocities within the inducer passage, confirming the highly three dimensional characteristic of inducer flow. Total relative velocity distribution indicate a substantial velocity deficiency near the tip at mid-passage which expands significantly as the flow proceeds toward the inducer trailing edge. High turbulence intensities and turbulence stresses are concentrated within this core region. Considerable wake diffusion occurs immediately downstream of the inducer trailing edge to decay this loss core. Evidence of boundary layer interactions, blade blockage effects, radially inward flows, annulus wall effects, and backflows are all found to exist within the long, narrow passages of the inducer.

Gorton, C. A.↗
DOE OSTI2021

A Data-Driven Global Sensitivity Analysis Framework for Three-Phase Distribution System with PVs

Global sensitivity analysis (GSA) of distribution systems with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution systems. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of PV and load power injections. The sampling-based method approximates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-node distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.

14 SOLAR ENERGY↗
DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method

Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (ders). to address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines taylor series expansion knowledge with a data-driven regression technique. the proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified taylor expansion. to mitigate the approximation loss that surges due to the der integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. comparative analysis in the 13-bus and 123-bus ieee unbalanced feeders shows that the proposed hybrid algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.

data-driven↗
DOE OSTI2026

Modeling the Cosmological Lyman-𝛼 Forest at the Field Level

The distribution of absorption lines in the spectra of distant quasars, called the Lyman-𝛼 (Ly-𝛼) forest, is a unique probe of cosmology and the intergalactic medium at high redshifts and small scales. The statistical power of ongoing redshift surveys demands precise theoretical tools to model the Ly-𝛼 forest. We address this challenge by developing an analytic, perturbative forward model to predict the Ly-𝛼 forest at the field level for a given set of cosmological initial conditions. Our model shows a remarkable performance when compared with the Sherwood hydrodynamic simulations: it reproduces the Ly-𝛼 forest flux power spectrum, its cross-correlation with dark matter halos, and the one-point probability distribution function of both fields at the percent level down to scales of a few Mpc. Our work provides crucial tools that bridge analytic modeling on large scales with simulations on small scales, enabling field-level inference from Ly-𝛼 forest data and simulation-based priors for cosmological analyses. Furthermore, this is especially timely for realizing the full scientific potential of the Ly-𝛼 forest measurements by the dark energy spectroscopic instrument.

Cosmological parameters↗
NASA NTRS1998

Transient cavities in liquids and the nature of the hydrophobic effect

The size distributions of transient cavities in water and organic liquids, obtained from computer simulations, have provided a new means to analyze the nature of the hydrophobic effect and to evaluate the adequacy of different analytical models of this effect. The poor solubility of non-polar solutes in water is attributed to a low probability of finding in water cavities of atomic and molecular size. It has been shown that water applies more force per unit area of cavity surface than do hydrocarbon liquids. Models that successfully capture the main characteristics of the hydrophobic effect must at least include information about the density and the radial distribution of oxygen atoms in liquid water. One such model, quantitatively accurate for molecular solutes of arbitrary shape, is presented.

NASA Center ARC↗
NASA NTRS2001

Linear and Order Statistics Combiners for Pattern Classification

Several researchers have experimentally shown that substantial improvements can be obtained in difficult pattern recognition problems by combining or integrating the outputs of multiple classifiers. This chapter provides an analytical framework to quantify the improvements in classification results due to combining. The results apply to both linear combiners and order statistics combiners. We first show that to a first order approximation, the error rate obtained over and above the Bayes error rate, is directly proportional to the variance of the actual decision boundaries around the Bayes optimum boundary. Combining classifiers in output space reduces this variance, and hence reduces the 'added' error. If N unbiased classifiers are combined by simple averaging. the added error rate can be reduced by a factor of N if the individual errors in approximating the decision boundaries are uncorrelated. Expressions are then derived for linear combiners which are biased or correlated, and the effect of output correlations on ensemble performance is quantified. For order statistics based non-linear combiners, we derive expressions that indicate how much the median, the maximum and in general the i-th order statistic can improve classifier performance. The analysis presented here facilitates the understanding of the relationships among error rates, classifier boundary distributions, and combining in output space. Experimental results on several public domain data sets are provided to illustrate the benefits of combining and to support the analytical results.

Tumer, Kagan↗
NASA NTRS1984

Large deflection, large amplitude vibrations and random response of symmetrically laminated rectangular plates

An analytical method is presented for determining large-deflection static bending, large-amplitude free and forced vibrations, and large-amplitude random response of a clamped, symmetrically laminated, rectangular, thin plate subjected to a uniformly distributed transverse loading. Both movable and immovable inplane boundary conditions are considered. Numerical results for bending deflections and strains, frequency ratios, mean-square center deflections and mean-square maximum strains are presented showing the parametric effects of plate length-to-width ratio, orientation of layers, and intensities of applied force for both the linear and nonlinear cases. The analytical results for large-deflection random response are verified through comparison with experimental data.

Gray, C. E., Jr.↗
NASA NTRS2005

Experimental and Analytical Determination of the Geometric Far Field for Round Jets

An investigation was conducted at the NASA Glenn Research Center using a set of three round jets operating under unheated subsonic conditions to address the question: "How close is too close?" Although sound sources are distributed at various distances throughout a jet plume downstream of the nozzle exit, at great distances from the nozzle the sound will appear to emanate from a point and the inverse-square law can be properly applied. Examination of normalized sound spectra at different distances from a jet, from experiments and from computational tools, established the required minimum distance for valid far-field measurements of the sound from subsonic round jets. Experimental data were acquired in the Aeroacoustic Propulsion Laboratory at the NASA Glenn Research Center. The WIND computer program solved the Reynolds-Averaged Navier-Stokes equations for aerodynamic computations; the MGBK jet-noise prediction computer code was used to predict the sound pressure levels. Results from both the experiments and the analytical exercises indicated that while the shortest measurement arc (with radius approximately 8 nozzle diameters) was already in the geometric far field for high-frequency sound (Strouhal number >5), low-frequency sound (Strouhal number <0.2) reached the geometric far field at a measurement radius of at least 50 nozzle diameters because of its extended source distribution.

Koch, L. Danielle↗
DOE OSTI2021

Analytical solution for the cumulative wake of wind turbines in wind farms

This paper solves an approximate form of conservation of mass and momentum for a turbine in a wind farm array. The solution is a fairly simple explicit relationship that predicts the streamwise velocity distribution within a wind farm with an arbitrary layout. As this model is obtained by solving flow-governing equations directly for a turbine that is subject to upwind turbine wakes, no ad hoc superposition technique is needed to predict wind farm flows. A suite of large-eddy simulations (LES) of wind farm arrays is used to examine self-similarity as well as validity of the so-called conservation of momentum deficit for turbine wakes in wind farms. The simulations are performed with and without the presence of some specific turbines in the wind farm. This allows us to systematically study some of the assumptions made to develop the analytical model. A modified version of the conservation of momentum deficit is also proposed to provide slightly better results at short downwind distances, as well as in the far wake of turbines deep inside a wind farm. Model predictions are validated against the LES data for turbines in both full-wake and partial-wake conditions. While our results highlight the limitation in capturing the flow speed-up between adjacent turbine columns, the model is overall able to acceptably predict flow distributions for a moderately sized wind farm. Finally, the paper employs the new model to provide insights on the accuracy of common wake superposition methods.

17 WIND ENERGY↗
DOE OSTI2023

Reversible Electrochemical Lithium Cycling in a Vanadium(IV)- and Niobium(V)-Based Wadsley–Roth Phase

Fast charging remains one of the greatest safety challenges in Li-ion batteries due to Li-dendrite growth occurring on graphite anodes if they are lithiated too quickly. The search for high-rate anodes has highlighted materials in the Wadsley–Roth (WR) shear phase family. The relative abundance of V compared with traditional WR compositions of Nb and W makes V-based phases attractive. However, the high voltage and poor reversibility typically associated with V redox have made V-rich WR phases less studied than Nb- and W-rich phases. Here, we show that a new V-rich Wadsley–Roth phase, V 7 Nb 6 O 29 , achieves excellent rate capability and 80% capacity retention after 228 cycles with a relatively low average voltage of 1.76 V vs Li/Li + compared with other V-rich WR phases. Single-crystal X-ray diffraction reveals a P4/m space group with repeating 2 × 2 × ∞ and 3 × 3 × ∞ blocks of V 4+ and Nb 5+ octahedra. Finally, combined neutron pair distribution function analysis, X-ray absorption spectroscopy, and density functional theory calculations show that V redox is the primary source of capacity and that cycling stability is provided by the stable octahedral coordination adopted by V 4+ in the material.

25 ENERGY STORAGE↗
DOE OSTI2023

Determination of distribution coefficients of 41 elements in nitric and hydrochloric acids for actinide resin

The distribution coefficients of 41 elements were determined on Eichrom’s Actinide resin in HCl and HNO 3 solutions of molarities between 0.01 M and 9 M. Herein a separation scheme for these 41 elements was designed utilizing these distribution coefficients that combines the Actinide resin with Eichrom’s TRU resin. Overall, these values improve the ability to create separations targeting specific analytes utilizing Actinide resin.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

A comparison of carbon impurities in pre- and post-melt uranium Part 1: Scanning electron microscopy analysis

Although C impurities in U have been studied for decades, fundamental questions regarding their incorporation, migration, and overall transformation during metal processing still exist. In two written Parts, we compare the chemical speciation, distribution, crystallography, and morphologies (size, shape, etc.) of carbon-containing impurities in U metal both before and after melting using high resolution analytical electron microscopy (AEM). This first Part demonstrates the variability of carbide inclusions in depleted U (DU) metal with respect to their chemical phases and morphologies as observed by scanning electron microscopy (SEM). Here, a variety of inclusion types, such as the pill-shaped U monocarbide (UC), previously only hypothesized, are summarized. Additionally, delineation between hopper-shaped U carbonitride U(C,N) and dendritic UC inclusions is discussed in relationship to archived literature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulation and measurement of beam-induced heating of ceramic vacuum chambers

In this article, we summarize recent theoretical and experimental studies of the impedance and beam-induced heating of titanium-coated ceramic vacuum chambers used in the NSLS-II injection kickers. The impedance was calculated using the field matching theory assuming planar approximation and compared with the mpedanceake2 code. For the coating thickness of a few microns, we demonstrated that the beam-induced power is dissipated in the titanium coating and that the longitudinally averaged two-dimensional power density is approximated by an analytical expression, thus allowing the use of a simplified model of the power density as input for the code to simulate the temperature distribution with realistic nonuniform thickness of the Ti coating. For a few values of the NSLS-II beam current, we measured the beam-induced heating of two ceramic chambers using thermal sensors installed along the chamber and compared the measurement results with the simulations. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗