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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 19 records

Identifying Light-Duty Vehicle Travel from Large-Scale Multimodal Wearable GPS Data with Novelty Detection Algorithms

Identifying travel mode within travel survey data sets, especially light-duty vehicle (LDV) travel, is foundational, though nontrivial, to travel behavior analysis and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. They are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the data requirements. This paper proposes an LDV travel mode detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique-one-class support vector machines (OCSVMs)-and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multimodal prediction.

47 OTHER INSTRUMENTATION↗

Light-Duty Vehicle Trip Classification Using One-Class Novelty Detection and Exhaustive Feature Extraction

Travel mode classification within travel survey data sets, especially light-duty vehicle (LDV) trips, is foundational, though nontrivial, to emerging mobility systems, travel behavior analysis, and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. The detection approaches are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the dataset requirements. This work proposes an LDV trip detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique - one-class support vector machines (OCSVMs) - and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size and feature selection, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multi-modal trip prediction.

33 ADVANCED PROPULSION SYSTEMS↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Estimating Travel Energy Consumption Uncertainty Based on Inferred Travel Mode and Sensed Travel Length

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 8%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Forward Modeling the Orbits of Companions to Pulsating Stars from Their Light Travel Time Variations

Mutual gravitation between a pulsating star and an orbital companion leads to a time-dependent variation in path length for starlight traveling to Earth. These variations can be used for coherently pulsating stars, such as the δ Scuti variables, to constrain the masses and orbits of their companions. Observing these variations for δ Scuti stars has previously relied on subdividing the light curve and measuring the average pulsation phase in equally sized subdivisions, which leads to undersampling near periapsis. We introduce a new approach that simultaneously forward models each sample in the light curve and show that this method improves upon current sensitivity limits—especially in the case of highly eccentric and short-period binaries. We find that this approach is sensitive enough to observe Jupiter mass planets around δ Scuti stars under ideal conditions, and use gravity-mode pulsations in the subdwarf B star KIC 7668647 to detect its companion without radial velocity data. We further provide robust detection limits as a function of the signal-to-noise ratio of the pulsation mode and determine that the minimum detectable light travel time amplitude for a typical Kepler δ Scuti is around 2 s. This new method significantly enhances the application of light travel time variations to detecting short-period binaries with pulsating components, and pulsating A-type exoplanet host stars, especially as a tool for eliminating false positives.

79 ASTRONOMY AND ASTROPHYSICS↗

Time-Distance Helioseismology with the MDI Instrument: Initial Results

In time-distance helioseismology, the travel time of acoustic waves is measured between various points on the solar surface. To some approximation, the waves can be considered to follow ray paths that depend only on a mean solar model, with the curvature of the ray paths being caused by the increasing sound speed with depth below the surface. The travel time is effected by various inhomogeneities along the ray path, including flows, temperature inhomogeneities, and magnetic fields. By measuring a large number of times between different locations and using an inversion method, it is possible to construct 3-dimensional maps of the subsurface inhomogeneities. The SOI/MDI experiment on SOHO has several unique capabilities for time-distance helioseismology. The great stability of the images observed without benefit of an intervening atmosphere is quite striking. It his made it possible for us to detect the travel time fo separations of points as small as 2.4 Mm in the high-resolution mode of MDI (0.6 arc sec 1/pixel). This has enabled the detection of the supergranulation flow. Coupled with the inversion technique, we can now study the 3-dimensional evolution of the flows near the solar surface.

Duvall, T. L., Jr.↗

Evaluation of asynchronous geiger-mode avalanche photodiode arrays for deep-space optical communications

The NASA Psyche mission is set to explore an asteroid located between Mars and Jupiter with a launch date in 2022. On-board the Psyche spacecraft is experimental demonstrator technology that will allow scientists to explore the capabilities of optical communications – a program called Deep Space Optical Communication (DSOC) led by Jet Propulsion Laboratory (JPL). DSOC seeks to improve communications performance by developing a space-based Flight Laser Transceiver (FLT) and a ground-based transceiver to enable photon-efficient communications with equipment in deep space. An integral part to this FLT system is a high-efficiency photon-counting camera (PCC) that is able to detect both the 1064nm uplink/beacon laser photons and 1550nm downlink laser photons with low background noise, and is capable of withstanding the rigors of space-travel. The paper details the characterization of several asynchronous Geiger-Mode Avalanche Photodiode (GmAPD) arrays developed by MIT Lincoln Laboratory for use in the PCC- specifically evaluating the temperature dependence of background noise, photon detection efficiency at 1064nm and 1550nm wavelengths, pixel lifetime testing, and angle of acceptance measurements. The results of this characterization are used to determine the nominal conditions for the device to operate in while in flight to maintain an efficient link with the ground-based transceiver.

Duerr, E.↗

Infrared helioseismology - Detection of the chromospheric mode

Time-series observations of an infrared solar OH absorption line profile have been obtained on two consecutive days using a laser heterodyne spectrometer to view a 2 arcsec portion of the quiet sun at disk center. A power spectrum of the line center velocity shows the well-known photospheric p-mode oscillations very prominently, but also shows a second feature near 4.3 mHz. A power spectrum of the line intensity shows only the 4.3 mHz feature, which is identified as the fundamental p-mode resonance of the solar chromosphere. The frequency of the mode is observed to be in substantial agreement with the eigenfrequency of current chromospheric models. A time series of two beam difference measurements shows that the mode is present only for horizontal wavelengths greater than 19 Mm. The period of a chromospheric p-mode resonance is directly related to the sound travel time across the chromosphere, which depends on the chromospheric temperature and geometric height. Thus, detection of this resonance will provide an important new constraint on chromospheric models.

Deming, D.↗

Non-Destructive Evaluation of Wire Insulation and Coatings

The present invention uses the generation and detection of acoustic guided waves to evaluate the condition of the insulation on electrical wiring. Low order axisymmetric and flexural acoustic modes are generated in the insulated wire and travel partially in the center conductor and partially in the outer insulation. The stiffness of the insulation and the insulation's condition affect the overall wave speed and amplitude of the guided wave. Analysis of the received signal provides information about the age or useful life of the wire insulation. In accordance with the present invention, signal transmission occurs at one location on the electrical wire to be evaluated, and detection occurs at one or more locations along the electrical wire. Additional receivers can be used to improve measurement accuracy. Either the transmission transducer or one or more receiver transducers may be angled at other than 90 degrees to the wire. Generation of the guided waves can be accomplished by imparting a pressure pulse on the wire. Alternative embodiments include generation via a laser, such as a Q-switched laser or a laser diode.

Eric I Madaras↗

Quantum Frequency Combs with Path Identity for Quantum Remote Sensing

Quantum sensing promises to revolutionize sensing applications by employing quantum states of light or matter as sensing probes. Photons are the clear choice as quantum probes for remote sensing because they can travel to and interact with a distant target. Existing schemes are mainly based on the quantum illumination framework, which requires quantum memory to store a single photon of an initially entangled pair until its twin reflects off a target and returns for final correlation measurements. Existing demonstrations are limited to tabletop experiments, and expanding the sensing range faces various roadblocks, including long-time quantum storage and photon loss and noise when transmitting quantum signals over long distances. We propose a novel quantum sensing framework that addresses these challenges using quantum frequency combs with path identity for remote sensing of signatures (“qCOMBPASS”). The combination of one key quantum phenomenon and two quantum resources—namely, quantum-induced coherence by path identity, quantum frequency combs, and two-mode squeezed light—allows for quantum remote sensing without requiring quantum memory. The proposed scheme is akin to a quantum radar based on entangled frequency-comb pairs that uses path identity to detect, range, or sense a remote target of interest by measuring pulses of one comb in the pair that never traveled to the target but that contains target information “teleported” by quantum-induced coherence by path identity from the other comb in the pair that traveled to the target but is not detected. We develop the basic qCOMBPASS theory, analyze the properties of the qCOMBPASS transceiver, and introduce the qCOMBPASS equation—a quantum analog of the well-known LIDAR equation in classical remote sensing. We also describe an experimental scheme to demonstrate the concept using two-mode squeezed quantum combs. qCOMBPASS can strongly impact various applications in remote quantum sensing, imaging, metrology, and communications. These applications include detection and ranging of low-reflectivity objects, measurement of small displacements of a remote target with precision beyond the standard quantum limit (SQL), standoff hyperspectral quantum imaging, discreet surveillance from space with low detection probability (detect without being detected), very-long-baseline interferometry, quantum Doppler sensing, quantum clock synchronization, and networks of distributed quantum sensors. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Magnetospheric electric fields and auroral oval

DC electric field variations in a synchronous orbit (GEOS 2) during four substorms in the time sector 19 to 01 LT were investigated. Simultaneously, the imaging photometer on board DE 1 provided auroral images that are also utilized. Substorm onset is defined here as a sudden appearance of large electric fields. During the growth phase, the orientation of the electric field begins to oscillate some 30 min prior to onset. About 10 min before the onset GEOS 2 starts moving into a more tenuous plasma, probably due to a thinning of the current sheet. The onset is followed by a period of 10 to 15 min during which large electric fields occur. This interval can be divided into two intervals. During the first interval, which lasts 4 to 8 min, very large fields of 8 to 20 mV/m are observed, while the second interval contains relatively large fields (2 to 5 mV/m). A few min after the onset, the spacecraft returns to a plasma region of higher electron fluxes which are usually larger than before substorm. Some 30 min after onset, enhanced activity, lasting about 10 min, appears in the electric field. One of the events selected offers a good opportunity to study the formation and development of the Westward Traveling Surge (WST). During the traversal of the leading edge of the WTS (approximately 8 min) a stable wave mode at 5.7 mHz is detected.

Laakso, Harri↗

AE (Acoustic Emission) for Flip-Chip CGA/FCBGA Defect Detection

C-mode scanning acoustic microscopy (C-SAM) is a nondestructive inspection technique that uses ultrasound to show the internal feature of a specimen. A very high or ultra-high-frequency ultrasound passes through a specimen to produce a visible acoustic microimage (AMI) of its inner features. As ultrasound travels into a specimen, the wave is absorbed, scattered or reflected. The response is highly sensitive to the elastic properties of the materials and is especially sensitive to air gaps. This specific characteristic makes AMI the preferred method for finding "air gaps" such as delamination, cracks, voids, and porosity. C-SAM analysis, which is a type of AMI, was widely used in the past for evaluation of plastic microelectronic circuits, especially for detecting delamination of direct die bonding. With the introduction of the flip-chip die attachment in a package; its use has been expanded to nondestructive characterization of the flip-chip solder bumps and underfill. Figure 1.1 compares visual and C-SAM inspection approaches for defect detection, especially for solder joint interconnections and hidden defects. C-SAM is specifically useful for package features like internal cracks and delamination. C-SAM not only allows for the visualization of the interior features, it has the ability to produce images on layer-by-layer basis. Visual inspection; however, is only superior to C-SAM for the exposed features including solder dewetting, microcracks, and contamination. Ideally, a combination of various inspection techniques - visual, optical and SEM microscopy, C-SAM, and X-ray - need to be performed in order to assure quality at part, package, and system levels. This reports presents evaluations performed on various advanced packages/assemblies, especially the flip-chip die version of ball grid array/column grid array (BGA/CGA) using C-SAM equipment. Both external and internal equipment was used for evaluation. The outside facility provided images of the key features that could be detected using the most advanced C-SAM equipment with a skilled operator. Investigation continued using in-house equipment with its limitations. For comparison, representative X-rays of the assemblies were also gathered to show key defect detection features of these non-destructive techniques. Key images gathered and compared are: Compared the images of 2D X-ray and C-SAM for a plastic LGA assembly showing features that could be detected by either NDE technique. For this specific case, X-ray was a clear winner. Evaluated flip-chip CGA and FCBGA assemblies with and without heat sink by C-SAM. Only the FCCGA package that had no heat sink could be fully analyzed for underfill and bump quality. Cross-sectional microscopy did not revealed peripheral delamination features detected by C-SAM. Analyzed a number of fine pitch PBGA assemblies by C-SAM. Even though the internal features of the package assemblies could be detected, C-SAM was unable to detect solder joint failure at either the package or board level. Twenty times touch ups by solder iron with 700degF tip temperature, each with about 5 second duration, did not induce defects to be detected by C-SAM images. Other techniques need to be considered to induce known defects for characterization. Given NASA's emphasis on the use of microelectronic packages and assemblies and quality assurance on workmanship defect detection, understanding key features of various inspection systems that detect defects in the early stages of package and assembly is critical to developing approaches that will minimize future failures. Additional specific, tailored non-destructive inspection approaches could enable low-risk insertion of these advanced electronic packages having hidden and fine features.

Ghaffarian, Reza↗

Whistlers observed by Voyager 1 - Detection of lightning on Jupiter

During the Voyager 1 encounter with Jupiter a number of discrete signals were identified in the wideband plasma wave data with characteristics similar to whistlers generated by lightning. In this paper we show that the calculated whistler-mode travel times from Jupiter to the spacecraft are in good agreement with the measured dispersion characteristics, thereby confirming that the signals are caused by lightning on Jupiter and substantiating the Voyager 1 photographic evidence for lightning on Jupiter. A quantitative estimate of the north-south thickness of the Io plasma torus is also obtained from the measured whistler dispersion.

Gurnett, D. A.↗

Quasi-periodic Fast-mode Wave Trains Within a Global EUV Wave and Sequential Transverse Oscillations Detected by SDO-AIA

We present the first unambiguous detection of quasi-periodic wave trains within the broad pulse of a global EUV wave (so-called EIT wave) occurring on the limb. These wave trains, running ahead of the lateral coronal mass ejection (CME) front of 2-4 times slower, coherently travel to distances greater than approximately solar radius/2 along the solar surface, with initial velocities up to 1400 kilometers per second decelerating to approximately 650 kilometers per second. The rapid expansion of the CME initiated at an elevated height of 110 Mm produces a strong downward and lateral compression, which may play an important role in driving the primary EUV wave and shaping its front forwardly inclined toward the solar surface. The wave trains have a dominant 2 minute periodicity that matches the X-ray flare pulsations, suggesting a causal connection. The arrival of the leading EUV wave front at increasing distances produces an uninterrupted chain sequence of deflections and/or transverse (likely fast kink mode) oscillations of local structures, including a flux-rope coronal cavity and its embedded filament with delayed onsets consistent with the wave travel time at an elevated (by approximately 50%) velocity within it. This suggests that the EUV wave penetrates through a topological separatrix surface into the cavity, unexpected from CME-caused magnetic reconfiguration. These observations, when taken together, provide compelling evidence of the fast-mode MHD wave nature of the primary (outer) fast component of a global EUV wave, running ahead of the secondary (inner) slow component of CME-caused restructuring.

Solar Corona↗

Monitoring of corrosion effects in pipes with multi-mode acoustic signals

Current commercial long-range guided wave inspection and monitoring technologies for pipes usually require establishment of certain specific acoustic modes for wave propagation and use a large number of sensors in a certain geometric arrangement (for example, uniformly-spaced arrays of sensors on a collar, placed around a pipe). This paper, in contrast, presents a long-range corrosion detection method in pipes based on multi-mode guided acoustic waves, generated and received using simple, single-element sensors. In this technique, available guided wave modes in any interrogated zone of the structure are automatically down-selected by the medium, and changes in energy distribution over the selected modes are analyzed through signal processing to monitor material loss or addition. Here, to investigate the feasibility of the proposed method, we have performed both experimental and numerical simulation studies on 50.8-mm (2-in)-diameter schedule-40 carbon steel pipes. In these studies, a linear chirp signal is injected in compression mode, perpendicular to the surface of the pipe, generating multi-mode, multi-directional guided waves that travel within the pipe wall. Corrosion effects in the pipes are simulated numerically and experimentally. To reduce errors in the measurement technique due to changes in the local or global temperature of the measured media, a universal temperature compensation algorithm is introduced. The experimental results show good agreement with simulation results, indicating that the proposed multi-mode wave generation and detection in a pipe could be used for long-range detection and monitoring of corrosion effects, such as pipe wall losses or solid material deposits.

36 MATERIALS SCIENCE↗

Acoustic absorption by sunspots

The paper presents the initial results of a series of observations designed to probe the nature of sunspots by detecting their influence on high-degree p-mode oscillations in the surrounding photosphere. The analysis decomposes the observed oscillations into radially propagating waves described by Hankel functions in a cylindrical coordinate system centered on the sunspot. From measurements of the differences in power between waves traveling outward and inward, it is demonstrated that sunspots appear to absorb as much as 50 percent of the incoming acoustic waves. It is found that for all three sunspots observed, the amount of absorption increases linearly with horizontal wavenumber. The effect is present in p-mode oscillations with wavelengths both significantly larger and smaller than the diameter of the sunspot umbrae. Actual absorption of acoustic energy of the magnitude observed may produce measurable decreases in the power and lifetimes of high-degree p-mode oscillations during periods of high solar activity.

Braun, D. C.↗

Molecular Modes of Attosecond Charge Migration

Here, first-principles calculations are employed to elucidate the modes of attosecond charge migration (CM) in halogenated hydrocarbon chains. We use constrained density functional theory (DFT) to emulate the creation of a localized hole on the halogen and follow the subsequent dynamics via time-dependent DFT. We find low-frequency CM modes (~ 1 eV) that propagate across the molecule and study their dependence on length, bond order, and halogenation. We observe that the CM speed (~ 4Å/ fs) is largely independent of molecule length, but is lower for triple-bonded versus double-bonded molecules. Additionally, as the halogen mass increases, the hole travels in a more particlelike manner as it moves across the molecule. These heuristics will be useful in identifying molecules and optimal CM detection methods for future experiments, especially for halogenated hydrocarbons which are promising targets for ionization-triggered CM.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗