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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Multi-resolution anisotropy studies of ultrahigh-energy cosmic rays detected at the Pierre Auger Observatory

Here, we report a multi-resolution search for anisotropies in the arrival directions of cosmic rays detected at the Pierre Auger Observatory with local zenith angles up to 80(o) and energies in excess of 4 EeV (4 × 10 18 eV). This search is conducted by measuring the angular power spectrum and performing a needlet wavelet analysis in two independent energy ranges. Both analyses are complementary since the angular power spectrum achieves a better performance in identifying large-scale patterns while the needlet wavelet analysis, considering the parameters used in this work, presents a higher efficiency in detecting smaller-scale anisotropies, potentially providing directional information on any observed anisotropies. No deviation from isotropy is observed on any angular scale in the energy range between 4 and 8 EeV. Above 8 EeV, an indication for a dipole moment is captured, while no other deviation from isotropy is observed for moments beyond the dipole one. The corresponding p-values obtained after accounting for searches blindly performed at several angular scales, are 1.3 × 10 -5 in the case of the angular power spectrum, and 2.5 × 10 -3 in the case of the needlet analysis. While these results are consistent with previous reports making use of the same data set, they provide extensions of the previous works through the thorough scans of the angular scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗
NASA NTRS1978

Critical fault patterns determination in fault-tolerant computer systems

The method proposed tries to enumerate all the critical fault-patterns (successive occurrences of failures) without analyzing every single possible fault. The conditions for the system to be operating in a given mode can be expressed in terms of the static states. Thus, one can find all the system states that correspond to a given critical mode of operation. The next step consists in analyzing the fault-detection mechanisms, the diagnosis algorithm and the process of switch control. From them, one can find all the possible system configurations that can result from a failure occurrence. Thus, one can list all the characteristics, with respect to detection, diagnosis, and switch control, that failures must have to constitute critical fault-patterns. Such an enumeration of the critical fault-patterns can be directly used to evaluate the overall system tolerance to failures. Present research is focused on how to efficiently make use of these system-level characteristics to enumerate all the failures that verify these characteristics.

Mccluskey, E. J.↗
NASA NTRSDate not supplied

Oculometric Detection and Characterization of Sub-Clinical Visual/Visuomotor Impairment

It has long been known that qualitative abnormalities in eye movements can be used to diagnose overt brain pathologies (Diefendorf & Dodge, 1908; Fox & Holmes, 1926; Leigh & Zee, 2015). Here, we will examine the use of a set of quantitative measures of the human behavioral response (oculometrics) in a 5-minute radial ocular tracking task (Krukowski & Stone, 2005) with sufficient temporal, spatial, and directional uncertainty to minimize the contribution of a priori prediction or anticipation, and to emphasize the use of a posteriori visual processing of the stimulus trajectory (Liston & Stone, 2014). The derived oculometrics provide a largely independent, reliable set of metrics that are sensitive enough to detect mild sub-clinical impairment across a range of possible neural loci (Stone et al., 2019) with the pattern of impairment across the set providing specificity as to its nature (Tyson et al., 2023). We will review our earlier findings where oculometrics have been used to detect mild impairment due to traumatic brain injury, sleep loss, and low-dose alcohol (Liston et al., 2017; Stone et al., 2019; Tyson et al., 2021). We will also report on a recent clinical study of asymptomatic patients at risk of retinal pathology (Leung et al., 2022) and show that oculometrics can detect and characterize substantive loss of visual function in the absence of clinical indicators of pathology. We conclude that oculometric testing could be used as a routine non-invasive ophthalmological or neurological tool to aid in the early detection and diagnosis of neural injury, toxicity, or disease.

eye movements↗
DOE OSTI2018

Topological Engineering of Interfacial Optical Tamm States for Highly Sensitive Near-Singular-Phase Optical Detection

Here, we developed planar multilayered photonic-plasmonic structures, which support topologically protected optical states on the interface between metal and dielectric materials, known as optical Tamm states. Coupling of incident light to the Tamm states can result in perfect absorption within one of several narrow frequency bands, which is accompanied by a singular behavior of the phase of electromagnetic field. In the case of near-perfect absorptance, very fast local variation of the phase can still be engineered. In this research, we theoretically and experimentally demonstrate how these drastic phase changes can improve sensitivity of optical sensors. A planar Tamm absorber was fabricated and used to demonstrate remote near-singular-phase temperature sensing with an over an order of magnitude improvement in sensor sensitivity and over two orders of magnitude improvement in the figure of merit over the standard approach of measuring shifts of resonant features in the reflectance spectra of the same absorber. Our experimentally demonstrated phase-to-amplitude detection sensitivity improvement nearly doubles that of state-of-the-art nano-patterned plasmonic singular-phase detectors, with further improvements possible via more precise fabrication. Tamm perfect absorbers form the basis for robust planar sensing platforms with tunable spectral characteristics, which do not rely on low-throughput nano-patterning techniques.

42 ENGINEERING↗
DOE OSTI2015

Detection of nanoscale embedded layers using laboratory specular X-ray diffraction

Unusual specular X-ray diffraction patterns have been observed from certain thin film intergrowths of metal monochalcogenide (MX) and transition metal dichalcogenide (TX{sub 2}) structures. These patterns exhibit selective “splitting” or broadening of selected (00l) diffraction peaks, while other (00l) reflections remain relatively unaffected [Atkins et al., Chem. Mater. 24, 4594 (2012)]. Using a simplified optical model in the kinematic approximation, we illustrate that these peculiar and somewhat counterintuitive diffraction features can be understood in terms of additional layers of one of the intergrowth components, MX or TX{sub 2}, interleaved between otherwise “ideal” regions of MX-TX{sub 2} intergrowth. The interpretation is in agreement with scanning transmission electron microscope imaging, which reveals the presence of such stacking “defects” in films prepared from non-ideal precursors. In principle, the effect can be employed as a simple, non-destructive laboratory probe to detect and characterize ultrathin layers of one material, e.g., 2-dimensional crystals, embedded between two slabs of a second material, effectively using the two slabs as a highly sensitive interferometer of their separation distance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1998

Multiplex titration RT-PCR: rapid determination of gene expression patterns for a large number of genes

We have developed an improved method for determination of gene expression levels with RT-PCR. The procedure is rapid and does not require extensive optimization or densitometric analysis. Since the detection of individual transcripts is PCR-based, small amounts of tissue samples are sufficient for the analysis of expression patterns in large gene families. Using this method, we were able to rapidly screen nine members of the Aux/IAA family of auxin-responsive genes and identify those genes which vary in message abundance in a tissue- and light-specific manner. While not offering the accuracy of conventional semi-quantitative or competitive RT-PCR, our method allows quick screening of large numbers of genes in a wide range of RNA samples with just a thermal cycler and standard gel analysis equipment.

Non-NASA Center↗
NASA NTRS1994

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Litt, Jonathan↗
NASA NTRS2018

Bar Code Events in the Juno-UVS Data: Signature ~10 MeV Electron Microbursts at Jupiter

One of the most intriguing discoveries of Juno is the quasi-systematic detection of upgoing electrons above the auroral regions. Here we discuss a by-product of the most energetic component of this population: a contamination resembling bar codes in the Juno-UVS images. This pattern is likely caused by bursts of ∼10 MeV electrons penetrating the instrument. These events are mostly detected when Juno’s magnetic footprint is located poleward of the main emission relative to the magnetic pole. The signal is not periodic, but the bursts are typically 0.1–1 s apart. They are essentially detected when Juno-UVS is oriented toward Jupiter, indicating that the signal is due to upgoing electrons. The event detections occur between 1 and 7 Jovian radii above the 1-bar level, suggesting that the electron acceleration takes place close to Jupiter and is thus both strong and brief.

Microbursts↗
NASA NTRS2000

A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays

Recently, quantitative models based on signal detection theory have been successfully applied to the prediction of human accuracy in visual search for a target that differs from distractors along a single attribute (feature search). The present paper extends these models for visual search accuracy to multidimensional search displays in which the target differs from the distractors along more than one feature dimension (conjunction, disjunction, and triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature dimensions. The observer combines the representations across feature dimensions to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experimental data on visual search accuracy in conjunctions and disjunctions of contrast and orientation. The model accounts for performance degradation without resorting to a limited-capacity spatially localized and temporally serial mechanism by which to bind information across feature dimensions.

Non-NASA Center↗
DOE OSTI2015

Statistical Techniques For Real-time Anomaly Detection Using Spark Over Multi-source VMware Performance Data

Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. As a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.

Apache Spark↗
NASA NTRS2015

Transmission X-ray Diffraction (XRD) Patterns Relevant to the MSL Chemin Amorphous Component: Sulfates And Silicates

The Mars Science Laboratory (MSL) CheMin instrument on the Curiosity rover is a transmission X-ray diffractometer (Co-Kalpha radiation source and a approx.5deg to approx.52deg 2theta range) where the analyzed powder samples are constrained to have discrete particle diameters <150 microns by a sieve. To date, diffraction patterns have been obtained for one basaltic soil (Rocknest (RN)) and four drill fines of coherent rock (John Klein (JK), Cumberland (CB), Windjana (WJ), and Confidence Hills (CH)). The CheMin instrument has detected and quantified the abundance of both primary igneous (e.g., feldspar, olivine, and pyroxene) and secondary (e.g., Ca-sulfates, hematite, akaganeite, and Fe-saponite) minerals. The diffraction patterns of all CheMin samples are also characterized by a broad diffraction band centered near 30deg 2theta and by increasing diffraction intensity (scattering continuum) from approx.15deg to approx.5deg, the 2theta minimum. Both the broad band and the scattering continuum are attributed to the presence of an XRD amorphous component. Estimates of amorphous component abundance, based on the XRD data itself and on mass-balance calculations using APXS data crystalline component chemistry derived from XRD data, martian meteorites, and/or stoichiometry [e.g., 6-9], range from approx.20 wt.% to approx.50 wt.% of bulk sample. The APXSbased calculations show that the amorphous component is rich in volatile elements (esp. SO3) and is not simply primary basaltic glass, which was used as a surrogate to model the broad band in the RN CheMin pattern. For RN, the entire volatile inventory (except minor anhydrite) is assigned to the amorphous component because no volatile-bearing crystalline phases were reported within detection limits [2]. For JK and CB, Fesaponite, basanite, and akaganeite are volatile-bearing crystalline components. Here we report transmission XRD patterns for sulfate and silicate phases relevant to interpretation of MSL-CheMin XRD amorphous components.

Morris, R. V.↗
NASA NTRSDate not supplied

Detecting Risk and Anomalies in Airplane Dynamics Through Entropic Analysis of Time Series Data

Despite recent efforts to move away from traditional threshold exceedance detection methods for aircraft state monitoring, modern aircraft still rely on safety thresholds to communicate to pilots the identification of an anomaly in the aircraft when a threshold is surpassed. Current anomaly detection methods mainly depend on uninterpretable machine learning models to learn complex patterns and relationships contained in the time series data of aircraft. Although these methods are capable of identifying known anomalies, their deficiency in interpretability presents a challenge when translating them to different aircraft. To overcome this deficiency, entropic analysis of aircraft dynamics seeks to characterize the complexity, or lack thereof, of the aircraft dynamics prior to the development of a risk scenario. This complexity characterization provides a more straightforward summary of state changes in the dynamics of flight variables. To build a foundation for entropic analysis, we analyzed the complexity of unstable approaches, an anomalous event present in many of today’s aviation accidents. The analysis revealed a statistically significant difference in the complexity distribution of flight variables under a stable approach versus an unstable approach. These differences in complexity were especially notable minutes before an approach was identified as unstable. Moreover, the multiscale entropic analysis revealed the presence of signal complexity at multiple time scales across multiple time windows before landing. By capturing state changes and corrections in the aircraft dynamics using entropy, advanced, yet still interpretable, sensor systems based on entropic frameworks from this study can be constructed in the future using classical machine learning approaches.

Risk detection↗
NASA NTRS1977

Investigations of spectral separability of small grains, early season wheat detection, and multicrop inventory planning

The author has identified the following significant results. LANDSAT data from seven 5 by 6 segments having crop type information were analyzed to determine the potential for spectral separation of spring wheat from other small grains as an alternative to the primary LACIE procedure for estimating spring wheat acreage. Within segment field-center, classification accuracies for spring wheat vs. barley tended to be best in mid-July when crop color changes were in progress. When correlations were made for differences in atmospheric haze, data from several segments could be aggregated, and results that approached within segment accuracies were obtained for selected dates. LACIE field measurement spectral reflectance data provided information on both wheat development patterns and the importance of various agronomic factors on wheat reflectance, the most important being availability of soil moisture. To investigate early season detection for winter wheat, reflectance of developing wheat patterns was simulated through reflectance modeling and was analyzed along with field measured reflectance from a Kansas site. The green component development of the wheat field was analyzed as a function of data throughout the season. A selected threshold was not crossed by all fields until mid-April. These reflectance data were shown to be consistent actual LANDSAT data.

Nalepka, R. F.↗
DOE OSTI2023

Confident detection of doubly ionized thorium in the extreme Ap star CPD-62° 2717

Despite the Universe containing primordial thorium (Th) of sufficient abundance to appear in stellar spectra, detection of Th has to date been tentative and based on just a few weak and blended lines. Here, we present convincing evidence not only for the first Th detection in a magnetic chemically peculiar Ap star but also for the first detection of Th iii in a stellar spectrum. CPD-62° 2717 was initially recognized as a highly magnetized Ap star due to resolved magnetically split lines captured in H-band spectra from the SDSS/APOGEE survey. The star was subsequently pinpointed as extraordinarily peculiar when careful inspection of the H-band line content revealed the presence of five lines of Th iii, none of which are detected in the other ∼1500 APOGEE-observed Ap stars. Follow-up with the VLT + UVES confirmed a similarly peculiar optical spectrum featuring dozens of Th iii lines, among other peculiarities. Unlike past claims of Th detection, and owing to high-resolution observations of the strong (∼8–12 kG) magnetic field of CPD-62° 2717, the detection of Th iii can in this case be supported by matches between the observed and theoretical magnetic splitting patterns. Comparison of CPD-62° 2717 to stars for which Th overabundances have been previously reported (e.g. Przybylski’s Star) indicates that only for CPD-62° 2717 is the Th detection certain. Along with the focus on Th iii, we use time series measurements of the magnetic field modulus to constrain the rotation period of CPD-62° 2717 to ∼4.8 yr, thus establishing it as a new example of a superslowly rotating Ap star.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quantitative stable isotope probing (qSIP) and cross-domain networks reveal bacterial-fungal interactions in the hyphosphere

Interactions between fungi and bacteria have the potential to substantially influence soil carbon dynamics in soil, but we have yet to fully identify these interactions and partners in their natural environment. In this study, we stacked two powerful methods, 13 C quantitative stable isotope probing (qSIP) and cross-domain co-occurrence network, to identify interacting fungi and bacteria in a California grassland soil. We used in-field whole plant 13 CO 2 labeling along with sand-filled ingrowth bags (that trap fungi and hyphae-associated bacteria) to amplify the signal of fungal-bacterial interactions, separate from the bulk soil background. We found a total of 54 bacterial ASVs and 9 fungal OTUs that were significantly 13 C-enriched. These were saprotrophic and biotrophic fungi, and motile, sometimes predatory bacteria. Among these, 70% of all 13 C-enriched bacteria identified were motile. Notably, we detected fungal-bacterial network links between a fungal OTU of the genus Alternaria and several bacterial ASVs of the genera Bacteriovorax, Mucilaginibacter, and Flavobacterium, providing empirical evidence of their direct interactions through C exchange. We observed a strong positive co-occurrence pattern between predatory bacteria of the phylum Bdellovibrionota and fungal OTUs, suggesting the transfer of C across the soil food web. To date, our ability to associate microbial co-occurrence network patterns with biological interactions is limited, but the incorporation of qSIP allowed us to more precisely detect interacting partners by narrowing in on the taxa that were actively incorporating plant-fixed, fungal-transported labeled substrates. Together, these approaches can help build a mechanistic understanding of the complex nature of fungal-bacterial interactions in soil.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

pattern identification↗
NASA NTRS1999

Characterization of Climate Change and Variability with GPS

We compared zonal mean specific humidity derived from the 21 June-4 July 1995 Global Positioning System (GPS)/MET occultation observations with that derived from the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The GPS/MET results indicate a drier troposphere, especially near the subtropical tradewind inversion. A small, moist bias in the GPS/MET upper northern-hemisphere troposphere compared to ECMWF may be due to a small radiosonde temperature bias. A diagram shows the difference (g/kg) between the GPS/MET zonal mean specific humidity and that for June-August derived from 1963-1973 radiosondes. Although the observing period is short, GPS and ECMWF results both indicate a significantly wetter boundary layer at most latitudes consistent with decadal trends observed in radiosonde data. GPS/MET results exhibit higher tropical convective available potential energy (CAPE), suggesting a more vigorous tropical Hadley circulation. Drier, free troposphere air in the descending branches of the Hadley circulation is due in part to a moist radiosonde bias but may also reflect some negative moisture feedback. Using 1992-1997 ground GPS observations and recent advancements in GPS technology, we removed an apparent altimetric drift (-1.2 +/- 0.4 mm/yr) due to columnar water vapor from the Topography (Ocean) Experiment (TOPEX) microwave radiometer, which brought the TOPEX mean sea level change estimates into better agreement with historical tide gauge records, suggesting global mean sea level is rising at a rate of 1.5-2.0 mm/yr. We can also discern a statistically significant increase of 0.2 +/- 0.1 kg/square m/yr in mean columnar water vapor over the ocean from 1992-1997. Optimal fingerprinting can be used for the detection and attribution of tropospheric warming due to an anthropogenic greenhouse. Optimal fingerprinting distinguishes between different types of signals according to their spatial and temporal patterns, while minimizing the influence of natural climate variability. S. Leroy concludes that the signal-to-noise ratio of global warming detection increases by unity approximately every 10 years if a single oceanic region is chosen. Less time for detection is likely when many global regions are considered simultaneously. GPS occultation constellations allow the possibility of detecting small changes in upper air temperature with inconsequential calibration errors, making occultation an ideal data type for global warming detection studies. Our initial study of a 22-GHz satellite-satellite occultation system predicts upper troposphere moisture sensitivities of 3-5 ppmv and 1-2 percent in the middle and lower troposphere. Additional information contained in original.

Kursinski, R.↗