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At least 487 records · Page 27

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Predicting oxidation damage of ultra high-temperature carbide ceramics in extreme environments using machine learning

Determining the oxidation resistance of UHTC carbides in extreme environments is challenging theoretically and experimentally due to the high dimensional complexity of influencing variables and intricate testing setups. Herein we demonstrate the use of machine learning (ML) models trained with experimental literature data to predict the oxide thickness of UHTC carbides exposed to air based on composition, mean grain size, relative densification, holding time, and temperature. A multi-dimensional database with 76 occurrences is created containing experimental results of Hf, Zr, and Ta carbides plus additives. In this study, the preprocessed database is then used to train ML models to predict their oxidation behavior. The trained model predicts the oxidation damage in the form of an average oxide thickness in UHTC carbides with a Mean Absolute Error (MAE) of ±65.45 μm for samples in the testing set that developed thicknesses up to 1000 μm. The model successfully predicted oxidation damage for a recession rate lower than 60 μm/min. It is noticed that the ensemble method MAE is increased to ±134.34 μm while forecasting the oxidation of samples with a recession rate higher than the threshold. The unprecedented approach is a novel way to predict the damage through the oxidation of carbide compounds before processing for a smarter design with room for improvement.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning

Residual-based adaptive strategies are widely used in scientific machine learning yet remain largely heuristic. We introduce a variational framework that formalizes these methods through convex transformations of the residual, where different transformations correspond to distinct objective functionals. For instance, exponential weights target uniform error minimization, while linear weights recover quadratic error minimization. This perspective reveals adaptive weighting as a means of selecting sampling distributions that optimize a primal objective, directly linking discretization choices to error metrics. This principled approach yields three key benefits: it enables systematic design of adaptive schemes, reduces discretization error by lowering estimator variance, and enhances learning dynamics by improving gradient signal-to-noise ratio. Extending the framework to operator learning, we demonstrate substantial performance gains across diverse optimizers and architectures. Our results provide a theoretical perspective for residual-based adaptivity and establish a foundation for principled discretization and training.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Field validation of an actuated convergent-beam acoustic Doppler profiler for high resolution flow mapping

Abstract Energetic river and tidal flow environments feature complex hydrodynamic conditions. Conventional acoustic Doppler profiling instrumentation typically requires assumptions of flow homogeneity over the spatial scales of the divergent beam separation. This removes the ability to measure spatio-temporal variability within the flow. However, velocity variability within these spatial scales is often important in the design of structures and devices exposed to such flow, informing dynamic and peak hydrodynamic load predictions. The research presented outlines the development and testing of a flow measurement instrument consisting of multiple spatially-separated single beam acoustic Doppler profilers converging on a remote focal point, the location of which can be programmatically adjusted through actuation. This increases the spatial resolution at which remote field measurements can be made in energetic flow environments. Field testing of the instrument was conducted in a tidal channel at Sequim Bay Inlet, WA, USA. Results are compared with independent reference measurements made by a co-located, motion-corrected acoustic Doppler velocimeter. This comparison, across tidal velocities of 0.4–0.7 m s −1 , showed a mean velocity error of 0.5%–13.2% across nine sample locations within a 3.00 m × 2.25 m plane. To the authors’ knowledge, this is the first publication of flow velocity results from non-intrusive acoustic measurements at an off-axis, focal point location that features 3D positional control.

13 HYDRO ENERGY↗

DOE OSTI2022

Signal-Compensation-Based Adaptive PID Control for Fused Magnesia Smelting Processes

For fused magnesia smelting processes, the proportional-integral-derivative (PID) controller is difficult to regulate the smelting currents within desired ranges due to unexpected variations of the dynamics caused by material feeding operations. To solve this problem, we first proposed its dynamic model composed of a linear model and an uncertain nonlinear dynamic system that describes the unknown time-varying dynamics of nonlinearity and strong couplings among controlled variables. Then, using the accurately calculated value of the uncertain part at the previous sampling time instant and the tracking error that reflects the influence of its change rate, we developed a feedforward and a one-step optimal control to obtain two signal compensators to eliminate the impact of frequent variations of the uncertainties. For the compensators, we proposed a weight selection method to minimize the sum of the squared tracking error with ensured closed-loop stability. Based on the abovementioned modeling and control structure, we finally developed a novel adaptive PID controller augmented with signal compensators to control the whole process. Industrial applications have shown that the proposed method can always keep the tracking error and the control input within their targeted ranges, leading to a significantly reduced energy consumption per ton and increased fused magnesia production.

Wang, Weizhou↗

DOE OSTI2022

RUScal : Software for the analysis of resonant ultrasound spectroscopy measurements

Resonant ultrasound spectroscopy is used to nondestructively measure the elastic resonances of small solids to elucidate the material's elastic properties or other qualities like size, shape, or composition. In this work, we introduce the software RUScal for the purpose of determining elastic properties by analyzing the eigenfrequencies of solid specimens with common shapes, such as rectangular parallelepipeds, cylinders (solid and hollow tube), ellipsoids, and octahedrons, as well as irregularly shaped ellipsoids that can be described analytically. All symmetry classes are supported, from isotropic to triclinic, along with the option to add or remove up to three orthogonal mirror planes as well as the ability to reorient the crystal axes with respect the sample edges via Euler angles. Additional features include tools to help find initial sets of elastic constants, including grid exploration and Monte Carlo methods, a tool to analyze frequencies as a function of sample length or crystal orientation, an error analysis tool to assess fit quality, and formatting of the input and output files for batch fitting, e.g., as a function of temperature. This software was validated with published resonant ultrasound spectroscopy data for various materials, shapes, and symmetries with noted improvements in calculation time compared to finite element methods.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

SpecDis: Value Added Distance Catalog for 4 Million Stars from DESI Year-1 Data

We present the SpecDis value-added stellar distance catalog accompanying DESI Data Release 1. SpecDis trains a feed-forward neural network (NN) with Gaia parallaxes and gets the distance estimates. To build up an unbiased training sample, we do not apply selections on parallax error or signal-to-noise (S/N) of the stellar spectra, and instead, we incorporate parallax error into the loss function. Moreover, we employ principal component analysis to reduce the noise and dimensionality of stellar spectra. Validated by independent external samples of member stars with precise distances from globular clusters, dwarf galaxies, stellar streams, combined with blue horizontal branch stars, we demonstrate that our distance measurements show no significant bias up to 100 kpc, and are much more precise than Gaia parallax beyond 7 kpc. The median distance uncertainties are 23%, 19%, 11%, and 7% for S/N < 20, 20 ≤ S/N < 60, 60 ≤ S/N < 100, and S/N ≥ 100. Selecting stars with ${\mathrm{log}}\,g\lt 3.8$ and distance uncertainties smaller than 25%, we have more than 74,000 giant candidates within 50 kpc of the Galactic center and 1500 candidates beyond this distance. Additionally, we develop a Gaussian mixture model to identify unresolvable equal-mass binaries by modeling the discrepancy between the NN-predicted and the geometric absolute magnitudes from Gaia parallaxes and identify 120,000 equal-mass binary candidates. Our final catalog provides distances and distance uncertainties for >4 million stars, offering a valuable resource for Galactic astronomy.

astronomy data analysis↗

NASA NTRS1973

Abundance of 17 trace elements in carbonaceous chondrites.

Seventeen trace elements (Ag, Au, Bi, Br, Cd, Cs, Ge, In, Ir, Rb, Re, Sb, Se, Te, Tl, U, and Zn) were measured by neutron activation analysis in eight C1 samples (1 Alais, 3 Ivuna, 4 Orgueil and in three C2 samples (one each of Mighei, Murchison, Murray). The results show far less scatter than earlier literature data. The standard deviation of a single measurement from the mean of eight C1 samples lies between 2 and 14%, except for the following four elements: Au, Ag, Rb, and Br. The first two probably reflect contamination and sample heterogeneity, the last two, analytical error. Apparently C1 chondrites have a far more uniform composition than some authors have claimed.

Kraehenbuehl, U.↗

NASA NTRS1974

Study of isotopic composition of helium in the fine fraction of Luna 16 lunar surface material

The content of He isotopes is measured in two samples of the lunar surface material returned by the Luna 16 automatic station. Both samples consist of a fine fraction of lunar surface material and were samples from zone A (sample 3-2k) and from zone V (sample 9-1r). The value of He4/He3 and the concentration of the He isotopes are identical for both samples, within the limits of experimental error.

Boltenkov, B. S.↗

NASA NTRS1976

The measurement of carbon monoxide and methane in the national capital air quality control region. III - Correlation interferometer results

Two types of experiments were performed with a correlation interferometer on-board a Bell Jet Ranger 206 Helicopter. The first consisted of simultaneous ground- and air-truth measurements as the instrumented helicopter passed over the Cheverly site. The second consisted of several measurement flights in and around the national capital air quality control region (Washington, D.C.). The correlation interferometer data, the infrared Fourier spectrometer data, and the integrated altitude sampling data showed agreement within the errors of the individual measurements. High values for CO were found from the D.C. flight data to be reproducible and concentrated in areas of stop-and-go traffic. It is concluded, that pollutants at low altitudes are detectable from an air-borne platform by remote correlation interferometry and that the correlation interferometer measurements agree with ground- and air-truth data.

Goldstein, H. W.↗

NASA NTRS1977

Feature discrimination and detection probability in synthetic aperture radar imaging system

Images obtained using synthetic aperture radar (SAR) systems can only represent the intensities of resolution cells in the scene of interest probabilistically since radar receiver noise and Rayleigh scattering of the transmitted radiation are always present. Consequently, when features to be identified differ only by their contribution to the mean power of the radar return, discrimination can be treated by detection theory. In this paper, we develop a 'sufficient statistic' for discriminating between competing features and compare it with some suboptimal methods frequently used. Discrimination is measured by probability of detection error and depends on number of samples or 'looks', signal-to-noise ratio (SNR), and ratio of mean power returns from the competing features. Our results show discrimination and image quality rapidly saturate with SNR (very small improvement for SNR not less than 10 dB) but continue to improve with increasing number of looks.

Lipes, R. G.↗

NASA NTRS1979

Optical properties of solid CO2 - Application to Mars

Using a special low-temperature cell, thick layers of solid CO2 are grown on an infrared-transparent window. The transmission spectra of solid CO2 is measured from 4000 to 360 kaysers (2.5-27.8 microns). The complex index of refraction is derived for samples of different thicknesses. Scattering in the samples is the major source of error. Away from the major absorption bands the imaginary index is very low. The absorption coefficient is of the order of 1 kayser. The emissivity in the Viking IRTM 20-micron band of a solid surface of CO2 is estimated at 0.72 + 0.17 or -0.10. Snowlike deposits have similar or lower emissivity. The results of this paper relieve the need for exceptional meteorology to explain Martian brightness temperatures below the CO2 frost point.

Ditteon, R.↗

NASA NTRS1981

Irrigated lands assessment for water management: Technique test

A procedure for estimating irrigated land using full frame LANDSAT imagery was demonstrated. Relatively inexpensive interpretation of multidate LANDSAT photographic enlargements was used to produce a map of irrigated land in California. The LANDSAT and ground maps were then linked by regression equations to enable precise estimation of irrigated land area by county, basin, and statewide. Land irrigated at least once in California in 1979 was estimated to be 9.86 million acres, with an expected error of less than 1.75% at the 99% level of confidence. To achieve the same level of error with a ground-only sample would have required 3 to 5 times as many ground sample units statewide. A procedure for relatively inexpensive computer classification of LANDSAT digital data to irrigated land categories was also developed. This procedure is based on ratios of MSS band 7 and 5, and gave good results for several counties in the Central Valley.

Wall, S. L.↗

NASA NTRS1982

A Poisson process approximation for generalized K-5 confidence regions

One-sided confidence regions for continuous cumulative distribution functions are constructed using empirical cumulative distribution functions and the generalized Kolmogorov-Smirnov distance. The band width of such regions becomes narrower in the right or left tail of the distribution. To avoid tedious computation of confidence levels and critical values, an approximation based on the Poisson process is introduced. This aproximation provides a conservative confidence region; moreover, the approximation error decreases monotonically to 0 as sample size increases. Critical values necessary for implementation are given. Applications are made to the areas of risk analysis, investment modeling, reliability assessment, and analysis of fault tolerant systems.

Arsham, H.↗

NASA NTRS1984

Radar analyses of mesoscale meteorological phenomena during the AVE/VAS correlation field experiment

Radar data were collected during the selected critical times of the field experiment and subsequently analyzed for specific items. The analyses of the radar data for the AVE/VAS experiment provided statistically significant values for each of the 10 Km by 10 Km grids within radar range. The resulting information for correlation with satellite data included the following derived items that were averaged for each grid area: (1) rainfall rate in mm/hr; (2) dBZ (reflectivity) values; (3) accumulated rainfall values per hour; (4) accumulated rainfall values for a 6-hour period; (5) vertically integrated liquid water content per square meter; and (6) vertical height of the radar axis at the midpoint of each grid. Additional products derived from radar data are being investigated. An example of one such product is the derivation of the errors in integrated rainfall with different sampling periods. This is of significance for correlation with satellite data in that normally a step-function type of rainfall rate is used to derive the total rainfall over a period.

Huebner, G. L.↗

NASA NTRS1984

A rapid method for obtaining frequency-response functions for multiple input photogrammetric data

A two-digital-camera photogrammetric technique for measuring the motion of a vibrating spacecraft structure or wing surface and an applicable data-reduction algorithm are presented. The 3D frequency-response functions are obtained by coordinate transformation from averaged cross and autopower spectra derived from the 4D camera coordinates by Fourier transformation. Error sources are investigated analytically, and sample results are shown in graphs.

Kroen, M. L.↗

NASA NTRS1983

The effects of digitizing rate and phase distortion errors on the shock response spectrum

Some of the methods used for acquisition and digitization of high-frequency transients in the analysis of pyrotechnic events, such as explosive bolts for spacecraft separation, are discussed with respect to the reduction of errors in the computed shock response spectrum. Equations are given for maximum error as a function of the sampling rate, phase distortion, and slew rate, and the effects of the characteristics of the filter used are analyzed. A filter is noted to exhibit good passband amplitude, phase response, and response to a step function is a compromise between the flat passband of the elliptic filter and the phase response of the Bessel filter; it is suggested that it be used with a sampling rate of 10f (5 percent).

Wise, J. H.↗

NASA NTRS1986

Space infrared telescope pointing control system. Infrared telescope tracking in the presence of target motion

The use of charge-coupled-devices, or CCD's, has been documented by a number of sources as an effective means of providing a measurement of spacecraft attitude with respect to the stars. A method exists of defocussing and interpolation of the resulting shape of a star image over a small subsection of a large CCD array. This yields an increase in the accuracy of the device by better than an order of magnitude over the case when the star image is focussed upon a single CCD pixel. This research examines the effect that image motion has upon the overall precision of this star sensor when applied to an orbiting infrared observatory. While CCD's collect energy within the visible spectrum of light, the targets of scientific interest may well have no appreciable visible emissions. Image motion has the effect of smearing the image of the star in the direction of motion during a particular sampling interval. The presence of image motion is incorporated into a Kalman filter for the system, and it is shown that the addition of a gyro command term is adequate to compensate for the effect of image motion in the measurement. The updated gyro model is included in this analysis, but has natural frequencies faster than the projected star tracker sample rate for dim stars. The system state equations are reduced by modelling gyro drift as a white noise process. There exists a tradeoff in selected star tracker sample time between the CCD, which has improved noise characteristics as sample time increases, and the gyro, which will potentially drift further between long attitude updates. A sample time which minimizes pointing estimation error exists for the random drift gyro model as well as for a random walk gyro model.

Powell, J. D.↗