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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Automatic Seismic Phase Picking Using Deep Learning for the EGS Collab project

Microseismic monitoring plays an important role in many energy-related and environmental industries.The microseismic event catalog and seismic structure of the subsurface are two of the primary outputsof the microseismic monitoring system. Though rough locations of microseismic events can be estimated automatically, obtaining high-resolution microseismic event locations requires a significant amount of human laborespecially on seismic phase picking. Unlike traditional automatic pickers that are usually less precise than human analysts, a fewrecently proposed algorithms based on deepneural networks(DNN)were able to match or surpass human performance for earthquake signals. Due to differences in the spatial scale of the study area, sensor sampling rate, and geometry of the monitoring system, it is not clear whether these deepneural networkmodels can be used to speed up microseismic data processing. In this paper, we adapted the DNN based technique for automatic phase picking of microseismic signals. We usedmicroseismic data recorded at the experiment 1 site of the enhancedgeothermal system (EGS) Collab project anddesigneda workflowthat we call transfer-learning aided double-difference tomography (TADT),thatcombines transfer learning and seismic tomography. We re-train an existing DNN with our data to obtain a newmodel using around 3500 seismogramsand associated manual phase picks. Thistransfer learnedmodel is able to reach human performance but muchfaster than human analysts. The transfer-learning-derived phase pickswereused to improve microseismic event locations and imagethesubsurface. The results are similar to or slightly better than those obtained with manual phase picks.

Chai, Chengping↗
DOE OSTI2022

An End-To-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning

Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine learning techniques. Here, in this study, we introduce a new end-to-end approach that improves overall earthquake detection accuracy by jointly optimizing each stage of the detection pipeline. We propose a neural network architecture for the task of multi-station processing of seismic waveforms recorded over a seismic network. This end-to-end architecture consists of three sub-networks: a backbone network that extracts features from raw waveforms, a phase picking sub-network that picks P- and S-wave arrivals based on these features, and an event detection sub-network that aggregates the features from multiple stations to associate and detect earthquakes across a seismic network. We use these sub-networks together with a shift-and-stack module based on back-projection that introduces kinematic constraints on arrival times, allowing the neural network model to generalize to different velocity models and to variable station geometry in seismic networks. We evaluate our proposed method on the STanford EArthquake Dataset (STEAD) and on the 2019 Ridgecrest, CA earthquake sequence. The results demonstrate that our end-to-end approach can effectively pick P- and S-wave arrivals and achieve earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.

58 GEOSCIENCES↗
DOE OSTI2026

Evaluating multistation phase picking algorithm phase neural operator (PhaseNO) on local seismic networks

Reliable automatic phase picking is important for many seismic applications. With the development of machine learning approaches, many algorithms are proposed, evaluated and applied to different areas. Many of these algorithms are single station based, while recent proposed methods start to combine surrounding stations into consideration in the problem of phase picking. Among these algorithms, the phase neural operator (PhaseNO) shows promising results on regional data sets comparing to existing algorithms. But there are many use cases for the local seismic networks in our community, therefore in this paper we evaluate the performance of PhaseNO on four different local data sets and compare the results to PhaseNet and EQTransformer. We used both individual phase picking metrics as well as association metrics to illustrate the performance of PhaseNO. By manually reviewing the newly detected events, we find that the PhaseNO model outperforms the single station-based approaches in the local-scale use cases due to its consideration of coherent signals from multiple stations. We also explored PhaseNO’s behaviours when only using one station, as well as gradually increasing the number of stations in the seismic network to better understand its behaviour. Overall, using the off-the-shelf machine learning based phase pickers, PhaseNO demonstrated its good performance on local-scale seismic networks.

58 GEOSCIENCES↗
DOE OSTI2023

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗
DOE OSTI2025

Reducing the Parameter Dependency of Phase-Picking Neural Networks with Dice Loss

Training a neural network for picking seismic phase arrivals has been commonly posed as a segmentation problem. It is a highly imbalanced segmentation problem in the sense that the background vastly dominates the foreground because we are trying to pick the optimal single sample point that represents the arrival of a seismic phase in a many seconds long time window. Here, we test the Dice loss, which is a preferred loss function for highly imbalanced image segmentation problems. We show that phase-picking neural networks trained on the Dice loss behave in a binary fashion for which the prediction output is almost always either nearly 1 or nearly 0. This feature removes the strong dependence of data processing workflows on the prediction score threshold, which is an otherwise critical parameter to determine when using neural networks trained on the cross-entropy loss. When strategically used, models trained on the Dice loss can reduce the parameter dependency of machine learning-based seismic monitoring.

58 GEOSCIENCES↗
DOE OSTI2024

The study of high-frequency pick-ups for electron beam position measurements in the AWAKE common beamline

The common beamline of the AWAKE experiment at CERN involves the co-propagation of two particle beams: protons with 48 nC bunch charge and 250 ps bunch length, and electrons with up to 600 pC bunch charge and approximately 4 ps bunch length. The existing operational beam position monitors at AWAKE cannot measure the electron bunches whilst the more-intense proton bunches are present, due to their low operating frequency. In order to try to address this challenge, two different types of high-frequency pick-ups were studied, a conical-shaped button pick-up and a Cherenkov diffraction radiation-based pick-up designed to operate at around 30 GHz. Both devices were installed at AWAKE and were connected to two identical read-out systems designed by TRIUMF. This contribution presents and discusses the results obtained from beam-based measurements during the current experimental year.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Rock Valley Accelerated Weight Drop Seismic Data Processing and Picking of P-wave and S-wave Arrival Times

Rock Valley, in the southern end of the Nevada National Security Site, hosts a fault system that was responsible for a shallow (< 3 km below surface ) magnitude 3.7 earthquake in May 1993. In order to better understand this system, seismic properties of the shallow subsurface need to be better constrained. In April and May of 2021, accelerated weight drop (AWD) active-source seismic data were recorded in order to measure P- and S-wave travel-times for the area. This report describes the processing and phase picking of the recorded seismic waveforms. In total, we picked 7,982 P-wave arrivals at offsets up to ~2500 m, and 4,369 S-wave arrivals at offsets up to ~2200 m. These travel-time picks can be inverted for shallow P-wave and S-wave velocity structure in future studies.

58 GEOSCIENCES↗
NASA NTRS1986

ICE plasma wave measurements in the ion pick-up region of Comet Halley

In late March 1986 the plasma wave instrument on the International Cometary Explorer (ICE) detected sporadic bursts of strong plasma turbulence with average wave characteristics very similar to those detected six months earlier, during the ICE traversal of the Comet Giacobini-Zinner (G-Z) heavy ion pick-up region. In both cases the observations of enhanced wave levels were generally correlated with simultaneous detection of energetic ions. The 1986 activity is interpreted in terms of plasma instabilities associated with solar wind pick-up of ions produced by heavy neutrals from Comet Halley. On March 25, when the distance between Comet Halley and ICE was 28.1 million kilometers, the ICE-to-comet range was about six times greater than the distance that marked the measured outer boundary of the turbulent heavy ion pick-up region of G-Z. Based on comparison with G-Z data and with earlier Halley observations, plausible arguments suggest that in late March, Halley should have produced detectable levels of energetic ions and associated plasma turbulence in a region with a spatial extent of 30-40 million kilometers.

Scarf, F. L.↗
NASA NTRS1989

Plasma wave, magnetic field and energetic ion observations in the ion pick-up region of Comet Giacobini-Zinner

Simultaneous plasma wave, magnetic field, and energetic ion observations made by the ICE spacecraft in the extended ion pick-up region surrounding comet Giacobini-Zinner are examined to determine the conditions under which two characteristic wave emissions, electrostatic waves at a few kHz, and electromagnetic waves at a few tens of Hz, are generated. The data are consistent with the view that the kHz electrostatic emissions result from an instability of the pick-up photoelectron 'beam' produced when the angle alpha between the magnetic field and the solar wind velocity vector is less than about 60 deg, while the behavior of the tens of Hz electromagnetic waves suggests that they are generated by the pick-up ion 'ring' which is present when alpha exceeds about 60 deg.

Richardson, I. G.↗
NASA NTRS1989

Test particle calculations of pick-up ions in the vicinity of Comet Giacobini-Zinner

Ionization of cometary neutral molecules produces ions which are picked-up by the solar wind. The cometary ion pick-up process for Comet Giacobini-Zinner is studied using a test particle method in which trajectories are numerically calculated for several thousand ions whose initial locations were chosen randomly with probability proportional to the neutral density. The cometary ion distribution function was calculated at several locations upstream of the bow shock. Several types of magnetic fluctuations were included. Circularly and linearly polarized monochromatic waves result in less pitch-angle scattering of pick-up ions than turbulent fluctuations which have about the same amplitude. Some anisotropy remains in the distribution function just upstream of the shock, even for the turbulent fluctuations.

Cravens, T. E.↗
NASA NTRS1992

Detection of singly ionized energetic lunar pick-up ions upstream of earth's bow shock

Singly ionized suprathermal ions upstream of the earth's bow shock have been detected by using the time-of-flight spectrometer SULEICA on the AMPTE/IRM satellite. The data were collected between August and December 1985. The flux of the ions in the mass range between 23 and 37 amu is highly anisotropic towards the earth. The ions are observed with a period of about 29 days around new moon (+/- 3 days). The correlation of the energy of the ions with the solar wind speed and the interplanetary magnetic field orientation indicates the relation to the pick-up process. We conclude that the source of these pick-up ions is the moon. We argue that due to the impinging solar wind, atoms are sputtered off the lunar surface, ionized in the sputtering process or by ensuing photoionization and picked up by the solar wind.

Hilchenbach, M.↗
DOE OSTI2025

Pick-and-Place Transfer of Arbitrary-Metal Electrodes for van der Waals Device Fabrication

Van der Waals electrode integration is a promising strategy to create nearly perfect interfaces between metals and 2D materials, with advantages such as eliminating Fermi-level pinning and reducing contact resistance. However, the lack of a simple, generalizable pick-and-place transfer technology has greatly hampered the wide use of this technique. Here, we demonstrate the pick-and-place transfer of prefabricated electrodes from reusable polished hydrogenated diamond substrates without the use of any sacrificial layers due to the inherent low-energy and dangling-bond-free nature of the hydrogenated diamond surface. The technique enables transfer of arbitrary-metal electrodes and an electrode array, as demonstrated by successful transfer of eight different elemental metals with work functions ranging from 4.22 to 5.65 eV. We also demonstrate the electrode array transfer for large-scale device fabrication. The mechanical transfer of metal electrodes from diamond to van der Waals materials creates atomically smooth interfaces with no interstitial impurities or disorder, as observed with cross-section high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. As a demonstration of its device application, we use the diamond transfer technique to create metal contacts to monolayer transition metal dichalcogenide semiconductors with high-work-function Pd, low-work-function Ti, and semimetal Bi to create n- and p-type field-effect transistors with low Schottky barrier heights. We also extend this technology to air-sensitive materials (trilayer 1T’ WTe 2 ) and other applications such as ambipolar transistors, Schottky diodes, and optoelectronics. This highly reliable and reproducible technology paves the way for new device architectures and high-performance devices.

2D materials↗
DOE OSTI2026

Phase Picking Beyond Local Distances: Where Waveform Filtering Still Matters for Deep Learning Models

Waveform filtering is a standard step in traditional seismic phase picking but often receives little attention in deep learning workflows, where models are typically trained on raw or minimally processed waveforms. Although this strategy performs well for local events, we show that performance can degrade substantially at regional distances. To address this limitation, we introduce two ways to incorporate multiband-filtered waveforms into deep learning phase pickers. The stacking approach concatenates filtered inputs along the channel dimension, while the branching approach processes each frequency band through a dedicated network branch before feature fusion. Both approaches can substantially improve performance across epicentral distances of 0° to 20°, but their effectiveness depends strongly on the selected frequency bands. Tests with multiple filter banks show that filter-bank design should be treated as part of model optimization rather than as a fixed preprocessing choice. Grad-CAM analysis of the branching model indicates that band importance varies among waveform samples and across training realizations, with only a weak overall preference for the 0.25 to 0.5 Hz band. These results show that no single filter band is consistently optimal and demonstrate that explicit feature engineering remains valuable for robust deep learning-based seismic phase picking.

58 GEOSCIENCES↗
NASA NTRS1981

Baseline studies on the feasibility of detecting a coal/shale interface with a self-powered sensitized pick

The feasibility of utilizing a sensitized pick to discriminate between cutting coal and roof material during the longwall mining process was investigated. A conventional longwall mining pick was instrumented and cutting force magnitudes were determined for a variety of materials, including Illinois #6 coal, shale type materials, and synthetic coal/shale materials.

Anderson, G. R., II↗
NASA NTRS1985

Modular Pick-and-Bucket Mining Machine

Concept for improved conventional pick-and-bucket mining machine offered as backup for hydrojet-jaw mining machine. Picks on chain dislodge coal and buckets on chain scoop it up. Depending on width cut, unit composed of only two end modules or end modules plus one, two, or three incremental modules. Folding curved shields protect sides of miner from falling coal and rock. Two side stabilizers - extendable hydraulic members - anchor miner against lateral drift. Unlike conventional machines, new version tilts cutters vertically and skews them horizontally to changing floor slopes and seam heights.

Gangal, M. D.↗
NASA NTRS1986

In-situ observations of cometary pick-up ions greater than 0.2 AU upstream of Comet Halley - ICE observations

Burst-like enhancements of energetic ions were observed by the EPAS instrument on the International Cometary Explorer (ICE) during its closest approach to (28 x 10 to the 6th km upstream of) Comet P/Halley, in late March 1986. The ion intensity was modulated by the varying solar wind speed (the latter reaching maxima of around 600 km/s), as was found to be the case for heavy cometary ions accelerated by pick-up in the solar wind flow, during the ICE encounter with Comet P/Giacobini-Zinner (G-Z). Therefore it is concluded that the observed pick-up ions (most probably greater than or equal to 65 keV oxygen ions) are produced by heavy neutrals from Comet Halley. The observations of energetic ions at such large distances suggest the presence, in the neutral atmosphere surrounding the nucleus, of a component with an ionization scale length of 5-10 million km, resulting from a relatively high expansion speed of a few km/s and/or an ionization time scale of a few times 10 to the 6ths.

Wenzel, K.-P.↗
NASA NTRS1987

Pick-up ions at Comet P/Halley's bow shock - Observations with the IIS spectrometer on Giotto

Gaseous material expanding from the nucleus of Comet Halley into space forms the neutral coma around the comet. Ionization in the solar UV radiation removes particles from the coma and injects them into the solar wind plasma. These freshly created ions are accelerated by the interplanetary electric field on cycloidal trajectories with gyrocenters moving with the speed of the magnetic field lines. In the solar wind frame of reference these particles move along the magnetic field lines with a fixed pitch angle. Pitch-angle scattering and energy diffusion reduce quickly the initial energy anisotropy which is associated with the narrow pick-up structures. First observations of heavy cometary pick-up ions (water group ions) at the bow shock are presented. The evolution of the distribution function in the vicinity of the shock and radial density profiles are discussed.

Wilken, B.↗
NASA NTRS1987

Visual enhancements in pick-and-place tasks - Human operators controlling a simulated cylindrical manipulator

A teleoperation simulator has been constructed with vector display system, joysticks, and a simulated cylindrical manipulator, in order to quantitatively evaluate various display conditions. The first of two experiments thus conducted investigated the effects of perspective parameter variations on human operators' pick-and-place performance, using a monoscopic perspective display. The second experiment involved visual enhancements of the monoscopic perspective display, by adding a grid and reference lines, by comparison with visual enhancements of a stereoscopic display; results indicate that stereoscopy generally permits superior pick-and-place performance, but that monoscopy nevertheless allows equivalent performance when defined with appropriate perspective parameter values and adequate visual enhancements.

Kim, Won S.↗