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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

ERTS data user investigation to develop a multistage forest sampling inventory system

The author has identified the following significant results. A unique digital timber volume estimation system was developed for use with the MSS CCT tapes. The system was tested on a 64-square mile area in Northern California's Trinity Alps. The outcome of a systematic experiment, in which several possible combinations of bands 5 and 7 and a contrast measure were tried, showed that an estimated gain in precision of 50% can be obtained in a multistage sampling design. The difference between bands 5 and 7 proved to be of special importance for the estimation of biomass in the form of timber volume. In addition, an interpretation model for high flight U2 photographs was developed. A maximum multiple correlation coefficient of 0.74 was obtained for the regression model, explaining 55% of the variation in timber volume as estimated from aerial photos and ground measurments. An interpretation model for MSS color composites is in the testing stage.

Langley, P. G.↗
NASA NTRS1975

Evaluation of Skylab (EREP) data for forest and rangeland surveys

The author has identified the following significant results. Four widely separated sites (near Augusta, Georgia; Lead, South Dakota; Manitou, Colorado; and Redding, California) were selected as typical sites for forest inventory, forest stress, rangeland inventory, and atmospheric and solar measurements, respectively. Results indicated that Skylab S190B color photography is good for classification of Level 1 forest and nonforest land (90 to 95 percent correct) and could be used as a data base for sampling by small and medium scale photography using regression techniques. The accuracy of Level 2 forest and nonforest classes, however, varied from fair to poor. Results of plant community classification tests indicate that both visual and microdensitometric techniques can separate deciduous, conifirous, and grassland classes to the region level in the Ecoclass hierarchical classification system. There was no consistency in classifying tree categories at the series level by visual photointerpretation. The relationship between ground measurements and large scale photo measurements of foliar cover had a correlation coefficient of greater than 0.75. Some of the relationships, however, were site dependent.

Aldrich, R. C.↗
NASA NTRS1983

Corrosion fatigue of high strength fastener materials in seawater

Environmental effects which significantly reduce the fatigue life of metals are discussed. Corrosion fatigue is a major concern in the engineering application of high strength fasteners in marine environments. The corrosion fatigue failure of an AISI 41L4O high strength steel blade to hub attachment bolt at the MOD-OA 200 kW wind turbine generator was investigated. The reduction of fatigue strength of AISI 41L4O in marine environments and to obtain similar corrosion fatigue data for candidate replacement materials was studied. The AISI 4140, PH 13-8Mo stainless steel, alloy 718 and alloy MP-35N were tested in axial fatigue at a frequency of 20 Hz in dry air and natural seawater. The fatigue data are fitted by regression equations to allow determination of fatigue strength for a given number of cycles to failure.

Tipton, D. G.↗
NASA NTRS2005

Hypersonic Wind Tunnel Calibration Using the Modern Design of Experiments

A calibration of a hypersonic wind tunnel has been conducted using formal experiment design techniques and response surface modeling. Data from a compact, highly efficient experiment was used to create a regression model of the pitot pressure as a function of the facility operating conditions as well as the longitudinal location within the test section. The new calibration utilized far fewer design points than prior experiments, but covered a wider range of the facility s operating envelope while revealing interactions between factors not captured in previous calibrations. A series of points chosen randomly within the design space was used to verify the accuracy of the response model. The development of the experiment design is discussed along with tactics used in the execution of the experiment to defend against systematic variation in the results. Trends in the data are illustrated, and comparisons are made to earlier findings.

Rhode, Matthew N.↗
NASA NTRS2014

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

strain-gage balance↗
NASA NTRS2021

Rotorcraft Sound Quality Metric Test 1: Stimuli Generation and Supplemental Analyses

A psychoacoustic test was conducted at the NASA Langley Research Center Exterior Effects Room (EER) to assess annoyance to simulated helicopter sounds over a range of sound quality (SQ) metric values. Initial findings identified important SQ metrics as sharpness, tonality, and fluctuation strength. This document is a supplement to the initial findings in which the following are discussed: (i) a detailed treatment of the sound generation process, (ii) the impact of analyzing results with stimuli measured in the EER instead of the intended synthesized stimuli, (iii) an evaluation of annoyance responses with certification metrics, and (iv) adjunct analyses related to the test methodology.

Psychoacoustic test, psychoacoustics, sound qualit↗
NASA NTRS2022

Comparison of U.S. and Russian Slow Crack Growth Data and Models

Both the US and Russian space programs use similar predictive models for design of fused silica windows on the International space station. The Russian model can be derived from the power expression for slow crack growth (SCG) or “static fatigue.” The US uses both power and exponential models. Despite the similarity of models and data fitting approach (linear regression and right censoring), different SCG parameters have been derived by US and Russian parties for the same material (Russian fused silica) tested in a similar manner. The difference appears to be related to the use of short-term strength data along with the longer-term static fatigue data, with the power law parameter n being very sensitive to the conversion of strength data into equivalent static data. This hybrid approach is feasible if strength data is measured with a constant stress rate and is appropriately converted to a static equivalent. More research into the approach is needed. However, because of the nonlinear behavior of fused silica in log(v) – log(K(I) ) space and the sensitivity of parameter estimation to fit range, the exponential model is a better choice regardless of test method. Functions are given to convert parameters from the Russian model to those in the US model. However, accurate conversion is hampered by the lack of inert strength data. When the same test technique is used, US and Russian materials exhibit very similar parameters.

Silica, strength, impact, crack growth, windows, I↗
NASA NTRSDate not supplied

Analysis and Evaluation of NASA's MK40B Six-Component Task Balance

The MK40B balance is NASA's newest balance of Task design. Its load range was optimized for use in the NASA Ames 11-ft Transonic Wind Tunnel. The balance was calibrated in 2019 in Calspan's Automatic Balance Calibration System. The data analysis was performed at the Ames Balance Calibration Laboratory. First, bi-directional characteristics of the six gage outputs of the balance were assessed by applying a semi-empirical test to the calibration data. These tests indicated that four of the six gages have bi-directional characteristics. Therefore, the use of absolute value terms in the regression models of the calibration data is justified. Then, the machine calibration data was analyzed using both the Non-Iterative and the Iterative Method. Analysis results for the two methods were compared using the percent contributions, the calibration load residuals, the primary sensitivities, and the principle linear terms. These results confirmed that the two methods describe bi-directional characteristics of the balance gages correctly. In addition, it was concluded that the load prediction accuracies of the two methods are the same for all practical purposes.

wind tunnel balance↗
NASA NTRS2002

C-Coupon Studies of SiC/SiC Composites: Acoustic Emission Monitoring - Part 1

Modal acoustic emission (AE) was used to monitor the acoustic activity during room temperature and elevated temperature c-coupon tests for a variety of SiC/SiC systems including composites containing Sylramic (trademark), ZMI (trademark), or Hi-Nicalon (trademark) fibers with melt-infiltrated or polymer-infiltrated SiC matrices. Modal AE proved excellent at monitoring matrix cracking in the curved portion of the C-coupon specimen with increasing load. This included the load at which the first AE event occurred and the location of AE events during the test that were, presumably, caused by the formation and growth of interlaminar cracks and, at higher loads, transverse cracks. Graphical techniques were employed to estimate the load for first AE. It was determined that for this test with these material systems, the first AE could be estimated within the load range bounded by the load at which initial deviation from linearity of the load-displacement curve occurs and the load where the 98% offset of the linear regression fit intercepted the load-displacement curve. The calculation of interlaminar tensile (ILT) stress from the load for first AE was determined for all the systems. Ultimate ILT strength usually corresponded to ILT stress determined from the ultimate load to failure of the C-coupon test, which was considerably higher than the first cracking stress.

Morscher, Gregory N.↗
DOE OSTI2024

CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2002

Smooth Pursuit Saccade Amplitude Modulation During Exposure to Microgravity

Russian investigators have reported changes in pursuit tracking of a vertically moving point stimulus during space flight. Early in microgravity, changes were manifested by decreased eye movement amplitude (undershooting) and the appearance of correction saccades. As the flight progressed, pursuit of the moving point stimulus deteriorated while associated saccadic movements were unchanged. Immediately postflight there was an improved execution of active head movements indicating that the deficiencies in pursuit function noted in microgravity may be of central origin. In contrast, tests of two cosmonauts showed that horizontal and vertical smooth pursuit were unchanged inflight. However, results of corresponding saccadic tasks showed a tendency toward the overshooting of a horizontal target early inflight with high accuracy developing later inflight, accompanied by an increased saccade velocity and a trend toward decreased saccade latency. Based on these equivocal results, we have further investigated the effects of space flight on the smooth pursuit mechanism during and after short duration flight, and postflight on returning MIR crewmembers. Sinusoidal target movement was presented horizontally at frequencies of 0.33 and 1.0 Hz. Subjects were asked to perform two trials for each stimulus combination: (1) moving eyes-only (EO) and (2) moving eyes and head (EH) with the target motion. Peak amplitude was 30 deg for 0.33 Hz trials and 15 deg for the 1.0 Hz trials. The relationship between saccade amplitude and peak velocity were plotted as a main sequence for each phase of flight, and linear regression analysis allowed us to determine the slope of each main sequence plot. The linear slopes were then combined for each flight phase for each individual subject. The main sequence for both EO and EH trials at both the 0.33 and 1.0 Hz frequencies during flight for the short duration flyers showed a reduction in saccade velocity and amplitude when compared to the preflight main sequence . This difference in the regression slopes between flight phase, head/eye condition (EO or EH), and pursuit target frequency was observed across all subjects (statistically significant at the p<0.02, df= 2). It is interesting to note that postflight for the short duration flyers there was an immediate recovery to the preflight main sequence across all trials. There were no significant differences observed between the preflight slopes for either head movement condition (EO vs. EH). When the immediate postflight (R+O) regression slopes were compared with the preflight slopes, there was a tendency (not significant) for both saccade amplitude and peak velocity to increase during the postflight testing. This tendency had vanished by R+ 1. Of particular interest was the redistribution of saccades during the latter stages of the flight and immediately postflight in the EO condition. At the 1.0 Hz frequency the saccades tended to be clustered near the lowest target velocity. It was also interesting to note that gaze performance (eye in skull + head in space) was consistently better during the EH condition; a finding also observed by our Russian colleagues. As the results of the long duration flight become available we expect that they will not only show that postflight effects will be similar to those observed during the short duration flights, but will also last for a greater period of time following flight. It is not clear what mechanism is responsible for the decreased peak saccadic velocity during flight unless the change is related to the control of retinal slip. For example, it is possible that saccades will tend to initially undershoot their targets by a small percentage and these saccades are then followed, if vision is available, by a small augmenting corrective saccade. It has been postulated that the functional significance of this undershooting tendency is to maintain the spatial representation of the target on the same side of the fovea (as opposedo racing across the fovea) and hence in the same cerebral hemisphere that initiated the primary saccade thus minimizing delays caused by an intra-hemispheric transfer of information . One could also speculate that with saccade velocities greater than normal, additional corrective saccades would be required to bring the target back on the fovea. A less plausible explanation of our findings could be fatigue. Yet it seems unlikely that our subjects would show lower velocities on all inflight test days while showing increased saccade velocities immediately following space flight where fatigue is usually the greatest. Finally, the redistribution effect noted late inflight is likely caused by adaptive changes. Overall, corrective saccades appeared to be used in maintaining gaze on target; reducing retinal slip and assisting space travelers in maintaining clear vision throughout the different phases of the space flight.

Reschke, M. F.↗
DOE OSTI2024

Ensemble methods for quantification of potassium oxide in ChemCam Mars and laboratory spectra

In this paper we test new approaches for predicting the amount of element oxides in rock samples from the ChemCam instrument suite onboard the NASA Curiosity rover by focusing on K 2 O. Using the expanded dataset compiled by Gasda et al. (2021) with and without the Earth to Mars (E2M and NoE2M) transformation discussed in Clegg et al. (2017) we trained blended submodels using the “double blending” technique and compared these to ensemble methods (Random Forest, ExtraTrees, and Gradient Boosting Regression). We found that ensemble methods performed similar to blended submodels when looking at RMSE-P on the laboratory spectra and provided significant advantages when looking at spectra coming from Mars. For the full model, blended submodels achieved an RMSE-P of 0.62 and 0.60 (E2M and NoE2M respectively) while Gradient Boosting Regression resulted in a slightly improved RMSE-P of 0.59 and 0.60. More importantly, by employing a local RMSE-P estimation technique where model performance is evaluated based on nearby test samples we found that using ensemble methods can lower the quantification limit for K 2 O from the current value of ≈0.6 wt% to ≈0.08 wt% using Extra Trees and Random Forest. This would allow for a much larger range of K 2 O values to be quantified on Mars with greater certainty given that most targets seen on Mars tend to have <1 wt% K2O. Finally, we used both Mean Decrease in Impurity (MDI) and permutation importance techniques to investigate the wavelengths used by the ensemble methods and found that they correspond to known potassium emission lines. This suggests that ensemble methods can provide an easier to train and improved alternative to blended submodels for predicting potassium compositions from Laser Induced Breakdown Spectroscopy (LIBS) data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Recalibration of missing low-frequency variability and trends in the North Atlantic Oscillation

Abstract Multi-decadal trends in the wintertime North Atlantic Oscillation (NAO) are under-represented by coupled general circulation models (CGCMs), consistent with a lack of autocorrelation in their NAO index series. This study proposes and tests two simple “reddening” approaches for correcting this problem in simulated indices based on simple one parameter short-term (AR; Auto-Regressive order 1) and long-term (FD; Fractional-Difference) time series filters. Using CGCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the FD filter successfully improves the autocorrelation structure of the NAO, and in turn the simulation of extreme trends, while the AR filter is less successful. The 1963–1993 NAO trend is the maximum 31-year trend in the historical period. Raw CGCMs underestimate the likelihood of this trend by a factor of ten but this discrepancy is corrected after reddening. CMIP6 future projections show that long-term (2024–2094) NAO ensemble mean trends systematically increase with the magnitude of radiative forcing: -2.4 to 3.5 hPa/century for low-to-high forcing after reddening (more than double the range using raw output). The related likelihood of future maximum 31year trends comparable to 1963–1993 ranges from 3 to 7% whereas none of these CMIP6 projections simulate this without reddening. Near-term projections of the next 31 years (2024–2054) are less sensitive than long term trends to the future scenario, showing weak-to-no forced trend. However, reddening increases the ensemble range by 74% (to +/-1 standard deviation/decade), which could increase/decrease regional climate change signals in the Northern Hemisphere by magnitudes that are underestimated when using raw CGCM output.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyse this dependence using multiple machine learning methods and a dataset of >200 000 nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence in diverse non-axisymmetric geometries. The dataset is generated using a large collection of both optimised and randomly generated stellarator equilibria. At fixed gradients and other input parameters, the turbulent heat flux varies between geometries by several orders of magnitude. Trends are apparent among the configurations with particularly high or particularly low heat flux. Regression and classification techniques from machine learning are then applied to extract patterns in the dataset. Due to a symmetry of the gyrokinetic equation, the heat flux and regressions thereof should be invariant to translations of the raw features in the parallel coordinate, similar to translation invariance in computer vision applications. Multiple regression models including convolutional neural networks (CNNs) and decision trees can achieve reasonable predictive power for the heat flux in held-out test configurations, with highest accuracy for the CNNs. Using Spearman correlation, sequential feature selection and Shapley values to measure feature importance, it is consistently found that the most important geometric lever on the heat flux is the flux surface compression in regions of bad curvature. The second most important geometric feature relates to the magnitude of geodesic curvature. These two features align remarkably with surrogates that have been proposed based on theory, while the methods here allow a natural extension to more features for increased accuracy. The dataset, released with this publication, may also be used to test other proposed surrogates, and we find that many previously published proxies do correlate well with both the heat flux and stability boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1974

Remote sensing techniques for mapping range sites and estimating range yield

Image interpretation procedures for determining range yield and for extrapolating range information were investigated for an area of the Pine Ridge Indian Reservation in southwestern South Dakota. Soil and vegetative data collected in the field utilizing a grid sampling design and digital film data from color infrared film and black and white films were analyzed statistically using correlation and regression techniques. The pattern recognition techniques used were K-class, mode seeking, and thresholding. The herbage yield equation derived for the detailed test site was used to predict yield for an adjacent similar field. The herbage yield estimate for the adjacent field was 1744 lbs. of dry matter per acre and was favorably compared to the mean yield of 1830 lbs. of dry matter per acre based upon ground observations. Also an inverse relationship was observed between vegetative cover and the ratio of MSS 5 to MSS 7 of ERTS-1 imagery.

Benson, L. A.↗
NASA NTRS1981

Evaluation of multiband, multitemporal, and transformed LANDSAT MSS data for land cover area estimation

Sample segments of ground-verified land cover data collected in conjunction with the USDA/ESS June Enumerative Survey were merged with LANDSAT data and served as a focus for unsupervised spectral class development and accuracy assessment. Multitemporal data sets were created from single-date LANDSAT MSS acquisitions from a nominal scene covering an eleven-county area in north central Missouri. Classification accuracies for the four land cover types predominant in the test site showed significant improvement in going from unitemporal to multitemporal data sets. Transformed LANDSAT data sets did not significantly improve classification accuracies. Regression estimators yielded mixed results for different land covers. Misregistration of two LANDSAT data sets by as much and one half pixels did not significantly alter overall classification accuracies. Existing algorithms for scene-to scene overlay proved adequate for multitemporal data analysis as long as statistical class development and accuracy assessment were restricted to field interior pixels.

Stoner, E. R.↗
DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗
NASA NTRS2008

In-Situ Measurement of Hall Thruster Erosion Using a Fiber Optic Regression Probe

One potential life-limiting mechanism in a Hall thruster is the erosion of the ceramic material comprising the discharge channel. This is especially true for missions that require long thrusting periods and can be problematic for lifetime qualification, especially when attempting to qualify a thruster by analysis rather than a test lasting the full duration of the mission. In addition to lifetime, several analytical and numerical models include electrode erosion as a mechanism contributing to enhanced transport properties. However, there is still a great deal of dispute over the importance of erosion to transport in Hall thrusters. The capability to perform an in-situ measurement of discharge channel erosion is useful in addressing both the lifetime and transport concerns. An in-situ measurement would allow for real-time data regarding the erosion rates at different operating points, providing a quick method for empirically anchoring any analysis geared towards lifetime qualification. Erosion rate data over a thruster's operating envelope would also be useful in the modeling of the detailed physics inside the discharge chamber. A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor was tested using a linear Hall thruster geometry, which served as a means of producing plasma erosion of a ceramic discharge chamber. The mass flow rate, discharge voltage, and applied magnetic field strength could be varied, allowing for erosion measurements over a broad thruster operating envelope. Results are presented demonstrating the ability of the REAST sensor to capture not only the insulator erosion rates but also changes in these rates as a function of the discharge parameters.

Polzink, Kurt A.↗