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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗
NASA NTRS2021

Semi-Analytic Forecasts for JWST– V. AGN Luminosity Functions and Helium Reionization at z= 2–7

Active galactic nuclei (AGN) forming in the early universe are thought to be the pri-mary source of hard ionizing photons contributing to the reionization of intergalactic helium. However, the number density and spectral properties of high-redshift AGN remain largely unconstrained. In this work, we make use of physically-informed mod-els calibrated with a wide variety of available observations to provide estimates for the role of AGN throughout the Epoch of Reionization. We present AGN luminosity functions in various bands between z= 2 to 7 predicted by the well-established Santa Cruz semi-analytic model, which includes modelling of black hole accretion and AGN feedback. We then combine the predicted AGN populations with a physical spectral model for self-consistent estimates of ionizing photon production rates, which depend on the mass and accretion rate of the accreting supermassive black hole. We then couple the predicted comoving ionizing emissivity with an analytic model to compute the subsequent reionization history of intergalactic helium and hydrogen. This work demonstrates the potential of coupling physically motivated analytic or semi-analytic techniques to capture multi-scale physical processes across a vast range of scales (here, from AGN accretion disks to cosmological scales). Our physical model predicts an in-trinsic ionizing photon budget well above many of the estimates in the literature, meaning that helium reionization can comfortably be accomplished even with a rel-atively low escape fraction. We also make predictions for the AGN populations that are expected to be detected in future James Webb Space Telescope surveys

L Y Aaron Yung↗
DOE OSTI2023

An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.

58 GEOSCIENCES↗
DOE OSTI2025

Benchmarking and Fidelity Response Theory of High-Fidelity Rydberg Entangling Gates

The fidelity of entangling operations is a key figure of merit in quantum information processing, especially in the context of quantum error correction. High-fidelity entangling gates in neutral atoms have seen remarkable advancement recently. A full understanding of error sources and their respective contributions to gate infidelity will enable the prediction of fundamental limits on quantum gates in neutral atom platforms with realistic experimental constraints. In this work, we implement the time-optimal Rydberg controlled-Z (CZ) gate, design a circuit to benchmark its fidelity, and achieve a fidelity, averaged over symmetric input states, of 0.9971 ( 5 ) , downward corrected for leakage error, which together with our recent work [Nature 634, 321–327 (2024)] forms a new state of the art for neutral atoms. The remaining infidelity is explained by an error model, consistent with our experimental results over a range of gate speeds, with varying contributions from different error sources. Further, we develop a fidelity response theory to efficiently predict infidelity from laser noise with nontrivial power spectral densities and derive scaling laws of infidelity with gate speed. Besides its capability of predicting gate fidelity, we also utilize the fidelity response theory to compare and optimize gate protocols, to learn laser frequency noise, and to study the noise response for quantum simulation tasks. Finally, we predict that a CZ gate fidelity of ≳ 0.999 is feasible with realistic experimental upgrades. Published by the American Physical Society 2025

Tsai, Richard Bing-Shiun (ORCID:0000000286758677)↗
NASA NTRS1986

A comparison of SIR-B directional ocean wave spectra with aircraft scanning radar spectra

Directional ocean wave spectra derived from Shuttle Imaging Radar-B (SIR-B) L-band imagery collected off the coast of Southern Chile on 11 and 12 October 1984 were compared with independent spectral estimates from two airborne scanning radars. In sea states with significant wave heights ranging from 3 to 5 meters, the SIR-B-derived sspectra at 18 deg and 25 deg off nadir yielded reasonable estimates of wavelengths, directions, and spectral shapes for all wave systems encountered, including a purely azimuth-traveling system. A SIR-B image intensity variance spectrum containing predominantly range-traveling waves closely resembles an independent aircraft estimate of the slope variance spectrum. The prediction of a U.S. Navy global spectral ocean wave model on 11 October 1984 exhibited no significant bias in dominant wave number but contained a directional bias of about 30 deg with respect to the mean of the aircraft and spacecraft estimates.

Beal, R. C.↗
NASA NTRS2001

Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

Vermillion, Stephanie C.↗
NASA NTRS2002

IRAS Low Resolution Spectra of Asteroids

Optical/near-infrared studies of asteroids are based on reflected sunlight and surface albedo variations create broad spectral features, suggestive of families of materials. There is a significant literature on these features, but there is very little work in the thermal infrared that directly probes the materials emitting on the surfaces of asteroids. We have searched for and extracted 534 thermal spectra of 245 asteroids from the original Dutch (Groningen) archive of spectra observed by the IRAS Low Resolution Spectrometer (LRS). We find that, in general, the observed shapes of the spectral continua are inconsistent with that predicted by the standard thermal model used by IRAS. Thermal models such as proposed by Harris (1998) and Harris et al.(1998) for the near-earth asteroids with the "beaming parameter" in the range of 1.0 to 1.2 best represent the observed spectral shapes. This implies that the IRAS Minor Planet Survey (IMPS, Tedesco, 1992) and the Supplementary IMPS (SIMPS, Tedesco, et al., 2002) derived asteroid diameters are systematically underestimated, and the albedos are overestimated. We have tentatively identified several spectral features that appear to be diagnostic of at least families of materials. The variation of spectral features with taxonomic class hints that thermal infrared spectra can be a valuable tool for taxonomic classification of asteroids.

Cohen, Martin↗
NASA NTRS2009

SHJAR Jet Noise Data and Power Spectral Laws

High quality jet noise spectral data measured at the Aeroacoustic Propulsion Laboratory at the NASA Glenn Research Center is used to examine a number of jet noise scaling laws. Configurations considered in the present study consist of convergent and convergent-divergent axisymmetric nozzles. The measured spectral data are shown in narrow band and cover 8193 equally spaced points in a typical Strouhal number range of 0.0 to 10.0. The measured data are reported as lossless (i.e., atmospheric attenuation is added to measurements), and at 24 equally spaced angles (50deg to 165deg) on a 100-diameter (200-in.) arc. Following the work of Viswanathan, velocity power factors are evaluated using a least squares fit on spectral power density as a function of jet temperature and observer angle. The goodness of the fit and the confidence margins for the two regression parameters are studied at each angle, and alternative relationships are proposed to improve the spectral collapse when certain conditions are met. As an immediate application of the velocity power laws, spectral density in shockcontaining jets are decomposed into components attributed to jet mixing noise and shock noise. From this analysis, jet noise prediction tools can be developed with different spectral components derived from different physics.

Khavaran, Abbas↗
NASA NTRS1999

Synthetic Scene Generation of the Stennis V and V Target Range for the Calibration of Remote Sensing Systems

The verification and validation (V&V) target range developed at Stennis Space Center is a useful test site for the calibration of remote sensing systems. In this paper, we present a simple algorithm for generating synthetic radiance scenes or digital models of this target range. The radiation propagation for the target in the solar reflective and thermal infrared spectral regions is modeled using the atmospheric radiative transfer code MODTRAN 4. The at-sensor, in-band radiance and spectral radiance for a given sensor at a given altitude is predicted. Software is developed to generate scenes with different spatial and spectral resolutions using the simulated at-sensor radiance values. The radiometric accuracy of the simulation is evaluated by comparing simulated with AVIRIS acquired radiance values. The results show that in general there is a good match between AVIRIS sensor measured and MODTRAN predicted radiance values for the target despite the fact that some anomalies exist. Synthetic scenes provide a cost-effective way for in-flight validation of the spatial and radiometric accuracy of the data. Other applications include mission planning, sensor simulation, and trade-off analysis in sensor design.

Cao, Chang-Yong↗
DOE OSTI2024

Insights into Tetravalent Np Speciation in HNO 3 through Spectroelectrochemistry and Multivariate Analysis

In situ optical spectroscopy, spectropotentiometry, and multivariate analysis were applied to the Np(IV) nitrate system to better understand speciation and quantify HNO 3 concentration. Thin-layer spectropotentiometry, or spectroelectrochemistry, was leveraged to isolate and stabilize Np(IV) without compromising the solution conditions and generate representative Vis-NIR absorption spectra from 0.5 to 10 M HNO 3 and benchmark the corresponding Np(IV) molar absorptivity coefficients. Spectra were described with principal component analysis (PCA) to identify the purest Np(IV) absorbance spectra among other oxidation states [e.g., Np(V/VI)] at each acid concentration and then to identify the primary sources of variance within each Np(IV) spectrum with respect to Np(IV) nitrate complexes. Then, partial least-squares regression (PLSR) and support vector regression (SVR) models were built to predict HNO 3 concentration from the Np(IV) spectral data. The nonlinear SVR model outperformed the linear PLSR model for the HNO 3 concentration predictions. Finally, the inclusion of spectra collected in edge and center point HNO 3 concentrations in the calibration set was determined to be crucial for producing models with strong predictive capabilities. The multivariate approach used in this study makes it possible to quantify HNO 3 concentration solely based on Np(IV) absorption spectra, which is essential to quantifying processing streams in various online monitoring applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2010

Ares I-X Launch Abort System, Crew Module, and Upper Stage Simulator Vibroacoustic Flight Data Evaluation, Comparison to Predictions, and Recommendations for Adjustments to Prediction Methodology and Assumptions

The National Aeronautics and Space Administration (NASA) Constellation Program (CxP) has identified a series of tests to provide insight into the design and development of the Crew Launch Vehicle (CLV) and Crew Exploration Vehicle (CEV). Ares I-X was selected as the first suborbital development flight test to help meet CxP objectives. The Ares I-X flight test vehicle (FTV) is an early operational model of CLV, with specific emphasis on CLV and ground operation characteristics necessary to meet Ares I-X flight test objectives. The in-flight part of the test includes a trajectory to simulate maximum dynamic pressure during flight and perform a stage separation of the Upper Stage Simulator (USS) from the First Stage (FS). The in-flight test also includes recovery of the FS. The random vibration response from the ARES 1-X flight will be reconstructed for a few specific locations that were instrumented with accelerometers. This recorded data will be helpful in validating and refining vibration prediction tools and methodology. Measured vibroacoustic environments associated with lift off and ascent phases of the Ares I-X mission will be compared with pre-flight vibration predictions. The measured flight data was given as time histories which will be converted into power spectral density plots for comparison with the maximum predicted environments. The maximum predicted environments are documented in the Vibroacoustics and Shock Environment Data Book, AI1-SYS-ACOv4.10 Vibration predictions made using statistical energy analysis (SEA) VAOne computer program will also be incorporated in the comparisons. Ascent and lift off measured acoustics will also be compared to predictions to assess whether any discrepancies between the predicted vibration levels and measured vibration levels are attributable to inaccurate acoustic predictions. These comparisons will also be helpful in assessing whether adjustments to prediction methodologies are needed to improve agreement between the predicted and measured flight data. Future assessment will incorporate hybrid methods in VAOne analysis (i.e., boundary element methods, BEM and finite element methods, FEM). These hybrid methods will enable the ability to import NASTRAN models providing much more detailed modeling of the underlying beams and support structure of the ARES 1-X test vehicle. Measured acoustic data will be incorporated into these analyses to improve correlation for additional post flight analysis.

Smith, Andrew↗
NASA NTRS1993

Near-IR imaging of moderate redshift galaxy clusters

We have obtained near-IR imaging of 3 moderate-z clusters on the 1.3 m at KPNO with SQIID, a new camera offering wide-field (5.5 arcmin) simultaneous JHK band imaging. Our photometry on a sample of approximately 100 likely member galaxies in one of the clusters, Abell 370 at z = 0.37, shows that we can obtain magnitudes good to 20 percent down to K = 18, considerably below the estimated K* = 16.5 at this redshift. These data indicate that there are no systematic problems in obtaining photometry at faint levels with SQIID. With the development of larger arrays, the field is open to progress. The resulting J, H, and K data for three clusters are combined with previously obtained multiband optical photometry. We present an investigation of the spectral properties and evolution of the dominant cold stellar populations by comparing optical-to-IR colors and color-magnitude diagrams to predictions from population synthesis models and galaxy spectral evolution codes.

Stanford, S. A.↗
DOE OSTI2024

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

An Early Prediction of the Amplitude of Solar Cycle 25

A “Solar Dynamo” (SODA) Index prediction of the amplitude of Solar Cycle 25 is described. The SODA Index combines values of the solar polar magnetic field and the solar spectral irradiance at 10.7 cm to create a precursor of future solar activity. The result is an envelope of solar activity that minimizes the 11-year period of the sunspot cycle. We show that the variation in time of the SODA Index is similar to several wavelet transforms of the solar spectral irradiance at 10.7 cm. Polar field predictions for Solar Cycles 21 – 24 are used to show the success of the polar field precursor in previous sunspot cycles. Using the present value of the SODA index, we estimate that the next cycle’s smoothed peak activity will be about 140 ± 30 solar flux units for the 10.7 cm radio flux and a Version 2 sunspot number of 135 ± 25. This suggests that Solar Cycle 25 will be comparable to Solar Cycle 24. The estimated peak is expected to occur near 2025.2 ± 1.5 year. Because the current approach uses data prior to solar minimum, these estimates may improve as the upcoming solar minimum draws closer.

Solar Cycle Predictions↗
DOE OSTI2021

Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models

We present four unique prediction techniques, combined with multiple data pre-processing methods, utilizing a wide range of both oil types and oil peroxide values (PV) as well as incorporating natural aging for peroxide creation. Samples were PV assayed using a standard starch titration method, AOCS Method Cd 8-53, and used as a verified reference method for PV determination. Near-infrared (NIR) spectra were collected from each sample in two unique optical pathlengths (OPLs), 2 and 24 mm, then fused into a third distinct set. All three sets were used in partial least squares (PLS) regression, ridge regression, LASSO regression, and elastic net regression model calculation. While no individual regression model was established as the best, global models for each regression type and pre-processing method show good agreement between all regression types when performed in their optimal scenarios. Furthermore, small spectral window size boxcar averaging shows prediction accuracy improvements for edible oil PVs. Best-performing models for each regression type are: PLS regression, 25 point boxcar window fused OPL spectral information RMSEP = 2.50; ridge regression, 5 point boxcar window, 24 mm OPL, RMSEP = 2.20; LASSO raw spectral information, 24 mm OPL, RMSEP = 1.80; and elastic net, 10 point boxcar window, 24 mm OPL, RMSEP = 1.91. The results show promising advancements in the development of a full global model for PV determination of edible oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Particle injection and acceleration at earth's bow shock - Comparison of upstream and downstream events

The injection and acceleration of thermal solar wind ions at the quasi-parallel earth's bow shock during radial interplanetary magnetic field conditions is investigated. Active Magnetospheric Particle Tracer Explorers/Ion Release Module satellite observations of complete proton spectra, and of heavy ion spectra above 10 keV/Q, made on September 12, 1984 near the nose of the shock, are presented and compared to the predictions of a Monte Carlo shock simulation which includes diffusive shock acceleration. It is found that the spectral observations are in good agreement with the predictions of the simulation when it is assumed that all accelerated ions originate in the solar wind and are injected into the acceleration mechanism by thermal leakage from the downstream plasma. The efficiency, which is determined directly from the downstream observations, is high, with at least 15 percent of the solar wind energy flux going into accelerated particles. The comparisons allow constraints to be placed on the rigidity dependence of the scattering mean free path and suggest that the upstream solar wind must be slowed substantially by backstreaming accelerated ions prior to undergoing a sharp transition in the viscous subshock.

Ellison, Donald C.↗
NASA NTRS2011

Solar UV Variations During the Decline of Cycle 23

Characterization of temporal and spectral variations in solar ultraviolet irradiance over a solar cycle is essential for understanding the forcing of Earth's atmosphere and climate. Satellite measurements of solar UV variability for solar cycles 21, 22, and 23 show consistent solar cycle irradiance changes at key wavelengths (e.g. 205 nm, 250 nm) within instrumental uncertainties. All historical data sets also show the same relative spectral dependence for both short-term (rotational) and long-term (solar cycle) variations. Empirical solar irradiance models also produce long-term solar UV variations that agree well with observational data. Recent UV irradiance data from the Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) instruments covering the declining phase of Cycle 23 present a different picture oflong-term solar variations from previous results. Time series of SIM and SOLSTICE spectral irradiance data between 2003 and 2007 show solar variations that greatly exceed both previous measurements and predicted irradiance changes over this period, and the spectral dependence of the SIM and SOLSTICE variations during these years do not show features expected from solar physics theory. The use of SORCE irradiance variations in atmospheric models yields substantially different middle atmosphere ozone responses in both magnitude and vertical structure. However, short-term solar variability derived from SIM and SOLSTICE UV irradiance data is consistent with concurrent solar UV measurements from other instruments, as well as previous results, suggesting no change in solar physics. Our analysis of short-term solar variability is much less sensitive to residual instrument response changes than the observations of long-term variations. The SORCE long-term UV results can be explained by under-correction of instrument response changes during the first few years of measurements, rather than requiring an unexpected change in the physical behavior of the Sun.

DeLand, Matthew, T.↗
NASA NTRS1990

Statistical properties of ideal three-dimensional magnetohydrodynamics

Classical Gibbs ensemble methods are used to study the spectral structure of three-dimensional ideal MHD in periodic geometry. In this paper the equilibrium ensemble incorporates constraints of total energy, magnetic helicity, and cross helicity. Several new results are proven for ensemble averages, including the constraint that magnetic energy equal or exceed kinetic energy, and that cross helicity represents a constant fraction of magnetic energy across the spectral domain, for arbitrary size systems. Two zero-temperature limits are considered in detail, emphasizing the role of complete and partial condensaiton of spectral quantities to the longest wavelength states. The ensemble predictions are compared to direct numerical solution using a low-order truncation Galerkin spectral code. Implications for spectral transfer of nonequilibrium, dissipative turbulent MHD systems are discussed.

Stribling, T.↗