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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs

Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data

The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. Here, we present a comprehensive search for correlations between high-energy (≳ 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (≳ 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directions and unresolved Fermi-LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. There was no significant correlation is found in any of the analyses performed, except a weak (≲ 2σ) hint of signal with the correlation function method on scales ~ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Revisiting the question: Does high-latitude solar activity lead low-latitude solar activity in time phase?

Cross-correlation analysis and wavelet transform methods are used to investigate whether high-latitude solar activity leads low-latitude solar activity in time phase or not, using the data of the Carte Synoptique solar filaments archive from 1919 March to 1989 December. From the cross-correlation analysis, high-latitude solar filaments have a time lead of 12 Carrington solar rotations with respect to low-latitude ones. Both the cross-wavelet transform and wavelet coherence indicate that high-latitude solar filaments lead low-latitude ones in time phase. Furthermore, low-latitude solar activity is better correlated with high-latitude solar activity of the previous cycle than with that of the following cycle, which is statistically significant. Thus, the present study confirms that high-latitude solar activity in the polar regions is indeed better correlated with the low-latitude solar activity of the following cycle than with that of the previous cycle, namely, leading in time phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Pattern Mining and Anomaly Detection based on the Power System Synchrophasor Measurements

Real-time monitoring of power system dynamics using phasor measurement units (PMUs) data improves situational awareness and system reliability and potentially can help prevent blackouts due to early anomaly detection. The study presented in the paper is based on the actual PMU measurements of the U.S. western interconnection system. Given the nonlinear and nonstationary PMUs data, we developed a robust anomaly detection framework. Wavelet-based multi-resolution analysis, combined with moving-window-based outlier detection and anomaly scoring, were deployed to identify potential PMU events. The candidate events were evaluated using spatiotemporal correlation analysis, and then classified for a better understanding of the event types. The results demonstrated successful anomaly detection and classification, compared with the recorded real-world events.

Ren, Huiying↗
NASA NTRS1983

Analysis and correlation of the test data from an advanced technology rotor system

Comparisons were made of the performance and blade vibratory loads characteristics for an advanced rotor system as predicted by analysis and as measured in a 1/5 scale model wind tunnel test, a full scale model wind tunnel test and flight test. The accuracy with which the various tools available at the various stages in the design/development process (analysis, model test etc.) could predict final characteristics as measured on the aircraft was determined. The accuracy of the analyses in predicting the effects of systematic tip planform variations investigated in the full scale wind tunnel test was evaluated.

Jepson, D.↗
DOE OSTI2017

Grain engineering: How nanoscale inhomogeneities can control charge collection in solar cells

Statistical and correlative analysis are increasingly important in the design and study of new materials, from semiconductors to metals. Non-destructive measurement techniques, with high spatial resolution, capable of correlating composition and/or structure with device properties, are few and far between. For the case of polycrystalline and inhomogeneous materials, the added challenge is that nanoscale resolution is in general not compatible with the large sampling areas necessary to have a statistical representation of the specimen under study. For the study of grain cores and grain boundaries in polycrystalline solar absorbers this is of particular importance since their dissimilar behavior and variability throughout the samples makes it difficult to draw conclusions and ultimately optimize the material. In this study, we present a nanoscale in-operando approach based on the multimodal utilization of synchrotron nano x-ray fluorescence and x-ray beam induced current collected for grain core and grain boundary areas and correlated pixel-by-pixel in fully operational Cu(In(1-x)Gax)Se2Cu(In(1-x)Gax)Se2 solar cells. We observe that low gallium cells have grain boundaries that over perform compared to the grain cores and high gallium cells have boundaries that under perform. These results demonstrate how nanoscale correlative X-ray microscopy can guide research pathways towards grain engineering low cost, high efficiency solar cells.

14 SOLAR ENERGY↗
NASA NTRS1974

Correaltion of full-scale drag predictions with flight measurements on the C-141A aircraft. Phase 2: Wind tunnel test, analysis, and prediction techniques. Volume 1: Drag predictions, wind tunnel data analysis and correlation

The degree of cruise drag correlation on the C-141A aircraft is determined between predictions based on wind tunnel test data, and flight test results. An analysis of wind tunnel tests on a 0.0275 scale model at Reynolds number up to 3.05 x 1 million/MAC is reported. Model support interference corrections are evaluated through a series of tests, and fully corrected model data are analyzed to provide details on model component interference factors. It is shown that predicted minimum profile drag for the complete configuration agrees within 0.75% of flight test data, using a wind tunnel extrapolation method based on flat plate skin friction and component shape factors. An alternative method of extrapolation, based on computed profile drag from a subsonic viscous theory, results in a prediction four percent lower than flight test data.

Macwilkinson, D. G.↗
DOE OSTI2016

Ultra-soft magnetic properties and correlated phase analysis by {sup 57}Fe Mössbauer spectroscopy of Fe{sub 74}Cu{sub 0.8}Nb{sub 2.7}Si{sub 15.5}B{sub 7} alloy

A detailed study of magnetic softness has been performed on FINEMENT type of ribbons by investigating the BH loop with maximum applied field of 960 A/m. The ribbon with the composition of Fe{sub 74}Cu{sub 0.8}Nb{sub 2.7}Si{sub 15.5}B{sub 7} was synthesized by rapid solidification technique and the compositions volume fraction was controlled by changing the annealing condition. Detail phase analysis was performed through X-ray diffraction (XRD), Differential scanning calorimetry (DSC), Vibrating sample magnetometer (VSM) and Mössbauer spectroscopy in order to correlate the ultrasoft magnetic properties with the volume fraction of amorphous and α-Fe(Si) soft nano composites. Bright (BF) and dark field (DF) image with selective area diffraction (SAD) patterns by the transmission electron microscopy (TEM) of the sample annealed for the optimized annealed condition at 853 K for 3 min reveals nanocrystals with an average size between 10-15 nm possessing the bcc structure which matches with the grain size revealed by the X-ray diffraction. Kinetics of crystallization of α-Fe(Si) phases has been determined by DSC curves. Extremely small coercivity of 30.9 A/m and core loss of 2.5 W/Kg for the sample annealed at 853 K for 3 min was found. Similar values for other crystalline conditions were determined by using BH loop tracer with a maximum applied field of around 960 A/m. Mössbauer spectroscopy was used to determine chemical shift, hyperfine field distribution (HFD), and peak width of different phases. The volume fractions of the relative amount of amorphous and crystalline phases are also determined by Mössbauer spectroscopy. High saturation magnetization along with ultrasoft magnetic properties exhibits very high potentials technological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evolution of Induced Fracture Networks Using Machine Learning Correlation Image Analysis

Enhanced geothermal systems (EGS) can enrich the Nation’s energy portfolio by increasing the amount of renewable baseload power available to the electrical grid. Microseismic activity, due to fluid resource injection and production, provides critical insight into the processes that occur within EGS subsurface fracture networks. To more precisely characterize these fracture networks, we leverage recent advances in deep neural network (DNN) image analysis techniques. Using seismic spectrogram data collected during a meso scale EGS field experiment as image inputs, we developed a new approach to correlate microseismic events. Our results indicate that our chosen DNN is able to estimate the correlation value between highly correlated events (i.e., cross-correlation coefficients greater than approximately 0.7), but has difficulty estimating correlation values between poorly correlated events. In physical systems however, the highly correlated microseismic events are the events of interest. Therefore, this data-driven method has shown potential for improving domestic Energy and Resource Security, advancing the current methods available to image subsurface EGS thermal reservoirs to enhance the availability of clean and reliable energy to the national electric grid.

58 GEOSCIENCES↗
DOE OSTI2025

Modelling the impact of quasar redshift errors on the full-shape analysis of correlations in the Lyman-α forest.

In preparation for the first cosmological measurements from the full shape of the Lyman-α (Lyα) forest from DESI, we must carefully model all relevant systematics that might bias our analysis. It was shown in Youles et al. (2022) that random quasar redshift errors produce a smoothing effect on the mean quasar continuum in the Lyα forest region. This, in turn, gives rise to spurious features in the Lyα autocorrelation and its cross-correlation with quasars. Using synthetic data sets based on the DESI survey, we confirm that the impact on BAO measurements is small, but that a bias is introduced to parameters which depend on the full shape of our correlations. We combine a model of this contamination in the cross-correlation (Youles et al. 2022) with a new model we introduce here for the auto-correlation. These are parametrised by 3 parameters, which, when included in a joint fit to both correlation functions, successfully eliminate any impact of redshift errors on our full-shape constraints. We also present a strategy for removing this contamination from real data, by removing ∼0.3% of correlating pairs.

cosmology↗
DOE OSTI2020

Divergent responses of spring phenology to daytime and nighttime warming

Spring phenology (i.e., start of season, SOS) has shifted earlier in response to warmer temperatures. However, the respective influences of daytime and nighttime temperatures on SOS changes remain poorly understood. Here we characterized the responses of satellite-derived SOS to minimum temperature (Tmin) and maximum temperature (Tmax) across Appalachian Trail regions in the Eastern United States during 2000-2013. We found SOS responded differently to Tmin and Tmax at 81.5% of the study area. Furthermore, the SOS responses to Tmin and Tmax both changed across space, and specifically, these two responses showed significant divergent trends from cold to warm regions (P<0.001). We propose a new framework utilizing both Tmin and Tmax, instead of daily average temperature, in modeling phenology. This study, for the first time, disentangled phenological responses to daytime temperature from nighttime temperature across a wide range of temperatures. The findings suggest that model projections of future phenological changes should incorporate the divergent phenology responses to daytime and nighttime temperatures, in order to improve the representation of land-atmosphere interactions in Earth system models in light of asymmetric diurnal warming.

asymmetric warming, temperature sensitivity, Appal↗
NASA NTRS1994

Diffuse continuum gamma rays from the Galaxy observed by COMPTEL

The diffuse Galactic continuum gamma-ray emission has been studied using the full Sky Survey from COMPTEL on the Compton Observatory CGRO. The diffuse emission appears to be visible in the whole 0.75-30 MeV range covered by the instrument, although a considerable contribution from unresolved point sources cannot be excluded. A correlation analysis using HI and CO surveys of the Galaxy is used to derive the Galactic emissivity spectrum, and this is consistent with a smooth continuation to the spectrum at higher energies derived by a similar analysis of COS-B data. The apparent conversion factor from integrated CO temperature to molecular hydrogen column density can also be determined from the correlation analysis. The value obtained is consistent with results from COS-B and other non-gamma-ray methods. Calculations of the emissivity spectrum from bremsstrahlung from a cosmic-ray electron spectrum based on propagation models are compared with the observations.

Strong, A. W.↗
DOE OSTI2019

Microvascular invasion and grading in hepatocellular carcinoma: correlation with major and ancillary features according to LIRADS

Purpose: To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC. Materials and methods: In this retrospective study, we assessed 62 patients (14 women–48 men; mean age, 63 years; range 38–80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected. Results: No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV. Conclusion: Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2018

Determination of Ballistic Limit for IM7/8552 Using Peridynamics

Significant testing is required to design and certify primary aircraft structure subject to High Energy Dynamic Impact (HEDI) events; current work under the NASA Advanced Composites Consortium (ACC) HEDI Project seeks to determine the state-of-the-art of dynamic fracture simulations for composite structures in these events. This paper discusses one of four Progressive Damage Analysis (PDA) methods selected for this project: peridynamics, through EMU implementation. A brief discussion of peridynamic theory is provided, followed by an outline of ballistic impact testing performed for model development and assessment. Detailed modeling approach and test-analysis correlation for a single open test case are presented, followed by the results of a series of blind predictions made prior to testing and test-analysis correlation performed with measured NASA test results. Specifically, we present simulation results for the ballistic limit (V50) of IM7/8552 composite panels ballistically tested with an impactor representative of a high-velocity fan-blade-out condition. In particular, force and displacement history and the damage state determined analytically are compared to measured results. Ultimately, peridynamics has the ability to predict damage patterns, impact force and deflections during a high energy dynamic impact event on composite panels of different layups using two different types of impactors. Blind predictions were promising and increased confidence in the model for impact simulation. There are open questions regarding the fidelity of the test fixture idealization in regards to stiffness and damping which will need to be addressed in future work.

Cuenca, Fernando↗
NASA NTRS1974

Data correlation and analysis of arc tunnel and wind tunnel tests of RSI joints and gaps. Volume 1: Technical report

Heat transfer data measured in gaps typical of those under consideration for joints in space shuttle reusable surface insulation protection systems have been assimilated, analyzed and correlated. The data were obtained in four NASA facilities. Several types of gaps were investigated with emphasis on simple butt joints. Gap widths ranged from 0.07 to 0.7 cm and depths ranged from 1 to 6 cm. Laminar, transitional and turbulent boundary layer flows over the gap opening were investigated. Three-dimensional heating variations were observed within gaps in the absence of external flow pressure gradients. Heat transfer correlation equations were obtained for several of the tests. Thermal protection system performance with and without gaps was compared for a representative shuttle entry trajectory.

Christensen, H. E.↗
DOE OSTI2019

Regional and correlative sweat analysis using high-throughput microfluidic sensing patches toward decoding sweat

Recent technological advancements in wearable sensors have made it easier to detect sweat components, but our limited understanding of sweat restricts its application. A critical bottleneck for temporal and regional sweat analysis is achieving uniform, high-throughput fabrication of sweat sensor components, including microfluidic chip and sensing electrodes. To overcome this challenge, we introduce microfluidic sensing patches mass fabricated via roll-to-roll (R2R) processes. The patch allows sweat capture within a spiral microfluidic for real-time measurement of sweat parameters including [Na + ], [K + ], [glucose], and sweat rate in exercise and chemically induced sweat. The patch is demonstrated for investigating regional sweat composition, predicting whole-body fluid/electrolyte loss during exercise, uncovering relationships between sweat metrics, and tracking glucose dynamics to explore sweat-to-blood correlations in healthy and diabetic individuals. By enabling a comprehensive sweat analysis, the presented device is a crucial tool for advancing sweat testing beyond the research stage for point-of-care medical and athletic applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Machine Learning for Thermal Transport Analysis of Aluminum Alloys with Precipitate Morphology

A large number of microstructural parameters and a wide range of transport physics impose challenges on thermal transport analysis of alloy. Herein, modern data science techniques are employed to overcome the challenges, pursuing effective calculation of thermal transport properties. This emerging approach is tested for precipitate-hardened aluminum (Al) alloy with consideration of precipitate morphology. The finite element method (FEM) is employed to create a database of effective thermal conductivity of hypothetical Al alloys with varying precipitate morphological and thermal transport features. Using the FEM-generated data sets, the correlation analysis is conducted to qualitatively evaluate the importance of various precipitate features. The correlation analysis identifies the surface area, average diameter, and volume fraction of precipitates as the most descriptive features for determining the thermal conductivity of alloys. Afterward machine learning (ML) models are trained to accurately predict the effective thermal conductivity. Comparing the ML predictions with effective thermal conductivity and microstructural information from experiments, precipitate thermal transport properties can be calculated, such as interfacial conductance between Al matrix and precipitate, without atomistic simulations. This research demonstrates the feasibility of data-driven approaches for effective thermal transport calculation and the promise of the FEM-generated data analysis for more comprehensive evaluation of metallic alloys.

36 MATERIALS SCIENCE↗