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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multiple Explanations for the Single Transit of KIC 5951458 Based on Radial Velocity Measurements Extracted with a Novel Matched-template Technique

Planetary systems that show single-transit events are a critical pathway to increasing the yield of long-period exoplanets from transit surveys. From the primary Kepler mission, KIC 5951458 b (Kepler-456b) was thought to be a single-transit giant planet with an orbital period of 1310 days. However, radial velocity (RV) observations of KIC 5951458 from the HIRES instrument on the Keck telescope suggest that the system is far more complicated. To extract precise RVs for this V≈13 star, we develop a novel matched-template technique that takes advantage of a broad library of template spectra acquired with HIRES. We validate this technique and measure its noise floor to be 4–8 m s{sup −1} (in addition to internal RV error) for most stars that would be targeted for precision RVs. For KIC 5951458, we detect a long-term RV trend that suggests the existence of a stellar companion with an orbital period greater than a few thousand days. We also detect an additional signal in the RVs that is possibly caused by a planetary or brown dwarf companion with mass in the range of 0.6–82 M {sub Jup} and orbital period below a few thousand days. Curiously, from just the data on hand, it is not possible to determine which object caused the single “transit” event. We demonstrate how a modest set of RVs allows us to update the properties of this unusual system and predict the optimal timing for future observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Assessment of the associated particle technique with high-resolution gamma-ray spectroscopy for in-field identification of chemical warfare agents and explosives

In this work, high-resolution prompt γ-ray neutron activation analysis (PGNAA) is performed using the associated particle (AP) technique with a deuterium-tritium neutron generator and high-purity germanium detector. Although the time resolution is inferior compared to similar systems employing fast scintillation γ-ray detectors, the strong background suppression combined with the high γ-ray energy resolution provides an important boost in sensitivity to certain key elements, especially relevant to field measurements of complex chemicals encased within thick layers of metal, such as in the case of recovered chemical warfare (CW) munitions. Results for various CW and explosive simulants contained within mock munitions are presented and compared with results obtained from traditional PGNAA measurements without the aid of the AP technique. Significant improvements in identification and discrimination between certain chemicals are achieved with the high energy resolution AP technique.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Eddy Correlation Flux Measurement System (ECOR) Instrument Handbook

The eddy correlation (ECOR) flux measurement system provides in situ, half-hour measurements of the surface turbulent fluxes of momentum, sensible heat, latent heat, and carbon dioxide (CO 2 ) (and methane at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s North Slope of Alaska central facility [NSA Barrow], and at the ARM Mobile Facility (AMF) deployment at Oliktok Point). The fluxes are obtained with the eddy covariance technique, which involves correlation of the vertical wind component with the horizontal wind component, the air temperature, the water vapor density, and the CO 2 concentration. The instruments used are: a fast-response, three-dimensional (3D) wind sensor (sonic anemometer) to obtain the orthogonal wind components and the speed of sound (SOS) (used to derive the air temperature), an open-path infrared gas analyzer (IRGA) to obtain the water vapor density and the CO 2 concentration, and an open-path infrared gas analyzer (IRGA) to obtain methane density and methane flux at NSA Barrow and at the AMF deployment at Oliktok Point. The ECOR systems are deployed at the locations where other methods for surface flux measurements (e.g., energy balance Bowen ratio [EBBR] systems) are difficult to employ, primarily at the north edge of a field of crops. A surface energy balance system (SEBS) has been installed collocated with each deployed ECOR system in SGP, NSA, Tropical Western Pacific (TWP), and each of three ARM Mobile Facilities. The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. Finally, the SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

Edgecomb, Joseph↗
DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

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

Velocity reconstruction in the era of DESI and Rubin/LSST. II. Realistic samples on the light cone

Reconstructing the galaxy peculiar velocity field from the distribution of large-scale structure plays an important role in cosmology. On one hand, it gives us an insight into structure formation and gravity; on the other, it allows us to selectively extract the kinetic Sunyaev-Zel’dovich (kSZ) effect from cosmic microwave background maps. In this work, we employ high-accuracy synthetic galaxy catalogs on the light cone to investigate how well we can recover the velocity field when utilizing the three-dimensional spatial distribution of the galaxies in a modern large-scale structure experiment such as the Dark Energy Spectroscopic Instrument (DESI) and the Rubin Observatory Legacy Survey of Space and Time. In particular, we adopt the standard technique used in baryon acoustic oscillation analysis for reconstructing the Zel’dovich displacements of galaxies through the continuity equation, which yields a first-order approximation to their large-scale velocities. We investigate variations in the number density, bias, mask, area, redshift noise, and survey depth, as well as modifications to the settings of the standard reconstruction algorithm. Since our main goal is to provide guidance for planned kSZ analysis between DESI and the Atacama Cosmology Telescope, we apply velocity reconstruction to a faithful representation of DESI spectroscopic and photometric targets. We report the cross-correlation coefficient between the reconstructed and the true velocities along the line of sight. For the DESI Y1 spectroscopic survey, we expect the correlation coefficient to be r ≈ 0.64, while for a photometric survey with δ z /(1+z) = 0.02, as is approximately the case for the Legacy Survey used in the target selection of DESI galaxies, r shrinks by half to r ≈ 0.31. Here, we hope the results in this paper can be used to inform future kSZ stacking studies and other velocity reconstruction analyses planned with the next generation of cosmology experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Tunneling Spectroscopy at Megabar Pressures: Determination of the Superconducting Gap in Sulfur

The recent discovery of high-temperature, high-pressure superconductors, such as hydrides and nickelates, has opened exciting avenues in studying high-temperature superconductivity. The primary superconducting properties of these materials are well characterized by measuring various electrical and magnetic properties, despite the challenges posed by the high-pressure environment. Experimental microscopic insight into the pairing mechanism of these superconductors is even more challenging, due to the lack of direct probes of the superconducting gap structures at high pressure conditions. Here, we have developed a planar tunnel junction technique for diamond anvil cells and present ground-breaking tunneling spectroscopy measurements at megabar pressures. We determined the superconducting gap of elemental sulfur at 160 GPa, a key constituent of the high-temperature superconductor H 3 S . High quality tunneling spectra indicate that β -Po phase sulfur is a type II superconductor with a single s -wave gap with a gap value 2 Δ ( 0 ) = 5.6 meV . This technique is compatible with superconducting compounds synthesized in diamond anvil cells and provides insight into the pairing mechanism in novel superconductors under high-pressure conditions. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2023

Analysis of Uncertainty Impacts on Emissions and Fuel Economy Evaluation for Chassis Dynamometer Testing

This study illustrates a methodology for quantifying the uncertainties encountered in the measurement of tailpipe emissions and in the fuel consumption measurements for light-duty conventional vehicles tested on a four-wheel drive chassis dynamometer. The study leverages high-fidelity experimental data collected over three standard drive cycles, UDDS, HWY and US06, intended to simulate a wide range of operating conditions. Here, a method is developed to estimate the measurement uncertainties in fuel consumption for a test cycle, which occur due to the accumulation of measurement uncertainties propagated through the system. The uncertainty determination model uses statistical analysis and standard propagation techniques to evaluate and combine the uncertainties introduced from various sources (including the vehicle, chassis dynamometer, driver, and instrumentation). The analysis also examines three different experimental methods for determining the fuel consumption: 1) carbon mass balance, 2) volumetric fuel scale and 3) gravimetric fuel scale, and takes into consideration the properties of the instrumentation used. The results show that the most significant influence on the determination of the emissions comes from the concentration measurement, and similarly the biggest impact on the total fuel consumption uncertainty comes from the uncertainty in the determination of the carbon dioxide mass, due to the large presence of this pollutant in the overall emissions. It was found that the fuel consumption uncertainties are in the range of ±1-2% for all three methods analyzed, with the lowest values being obtained for measurements performed using the gravimetric method for all three drive cycles considered.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Self-Supervised Cloud Classification

Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive understanding of cloud morphology is critical for continued improvement of our atmospheric modeling and prediction capabilities moving forward. Deep learning has recently accelerated our ability to study clouds using satellite remote sensing, and machine learning classifiers have enabled detailed studies of cloud morphology. A major limitation of deep learning approaches to this problem, however, is the large number of hand-labeled samples that are required for training. This work applies a recently developed self-supervised learning scheme to train a deep convolutional neural network (CNN) to map marine cloud imagery to vector embeddings that capture information about mesoscale cloud morphology and can be used for satellite image classification. The model is evaluated against existing cloud classification datasets and several use cases are demonstrated, including training cloud classifiers with very few labeled samples, interrogation of the CNN’s learned internal feature representations, cross-instrument application, and resilience against sensor calibration drift and changing scene brightness. The self-supervised approach learns meaningful internal representations of cloud structures and achieves comparable classification accuracy to supervised deep learning methods without the expense of creating large hand-annotated training datasets. Significance Statement Marine clouds heavily influence Earth’s weather and climate, and improved understanding of marine clouds is required to improve our atmospheric modeling capabilities and physical understanding of the atmosphere. Recently, deep learning has emerged as a powerful research tool that can be used to identify and study specific marine cloud types in the vast number of images collected by Earth-observing satellites. While powerful, these approaches require hand-labeling of training data, which is prohibitively time intensive. This study evaluates a recently developed self-supervised deep learning method that does not require human-labeled training data for processing images of clouds. We show that the trained algorithm performs competitively with algorithms trained on hand-labeled data for image classification tasks. We also discuss potential downstream uses and demonstrate some exciting features of the approach including application to multiple satellite instruments, resilience against changing image brightness, and its learned internal representations of cloud types. The self-supervised technique removes one of the major hurdles for applying deep learning to very large atmospheric datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Current Status of Developing Ultrafast Mega-electron-volt Electron Microsope

Recent studies of ultrafast electron microscopy (UEM) techniques show the use of short bunches of relativistic electrons is promising for the development of a new instrument for imaging various materials. Compared to conventional electron microscopes, the main advantage of UEMs with the electron energy of a few MeV is the possibility to study thick samples. We will discuss the progress of UEM design to date, the principal challenges on the way to a high resolution, and possible methods for their mitigation including the design of low-aberration magnetic optics, RF and mechanical subsystems with high stability, and precise collimation of electrons scattered in the samples.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

The Dark Energy Survey Six-Year Calibration Star Catalog

This Technical Note presents a catalog of calibrated reference stars that was generated by the Forward Calibration Method (FGCM) pipeline (arXiv:1706.01542) as part of the FGCM photometric calibration of the full Dark Energy Survey (DES) 6-Year data set (Y6). This catalog provides DES grizY magnitudes for 17 million stars with i-band magnitudes mostly in the range 16 < i < 21 spread over the full DES footprint covering 5000 square degrees over the Southern Galactic Cap at galactic latitudes b < -20 degrees (plus a few outlying fields disconnected from the main survey footprint). These stars are calibrated to a uniformity of better than 1.8 milli-mag (0.18%) RMS over the survey area. The absolute calibration of the catalog is computed with reference to the STISNIC.007 spectrum of the Hubble Space Telescope CalSpec standard star C26202; including systematic errors, the absolute flux system is known at the approximately 1% level. As such, these stars provide a useful reference catalog for calibrating grizY-band or grizY-like band photometry in the Southern Hemisphere, particularly for observations within the DES footprint.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Automating Sensor Characterization with Bayesian Optimization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Cuevas-Zepeda, Julian [Chicago U., KICP; Chicago U↗
DOE OSTI2024

Utilizing 3D Mechanical Earth Models for Calibration and Validation in a Large-Scale Carbon Capture and Storage Project in North Dakota

Conference paper presented at 17th International Conference on Greenhouse Gas Control Technologies (GHGT-17), Calgary, Alberta, Canada, October 20–24, 2024. Three-dimensional (3D) mechanical earth models (MEMs) are pivotal in assessing geological sites for carbon dioxide (CO 2 ) storage and mitigating potential risks associated with storage and injection. The Energy & Environmental Research Center is exploring innovative carbon storage monitoring techniques at a CO 2 storage site near Beulah, North Dakota. These methods aim to provide lower-impact, faster feedback for commercial carbon capture and storage (CCS) projects. The research includes monitoring CO 2 injection using various approaches: 1) an automated, integrated modular monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance; 4) time-lapse seismic techniques; and 5) advanced wellbore monitoring.

02 PETROLEUM↗
DOE OSTI2021

Determining the electrical conductivity of metals using the 2 MA Thor pulsed power driver

We present the development of a pulsed power experimental technique to infer the electrical conductivity of metals from ambient to high energy density conditions. The method is implemented on Thor, a moderate scale (1–2 MA) pulsed power driver. The electrical conductivity of copper at elevated temperature (>4000 K) and pressure (>10 GPa) is determined, and a new tabular material model is developed, guided by density functional theory, which preserves agreement with existing experimental data. Minor modifications (<10%) are found to be necessary to the previous Lee–More–Desjarlais model isotherms in the vicinity of the melt transition in order to account for observed discrepancies with the new experimental data. An analytical model for magnetic direct drive flyer acceleration and Joule heating induced vaporization based on the Tsiolkovsky “rocket equation” is presented to assess sensitivity of the method to minor changes in electrical conductivity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The Tianlai dish pathfinder array: design, operation, and performance of a prototype transit radio interferometer

ABSTRACT The Tianlai Dish Pathfinder Array is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization universe as a means for measuring large-scale cosmic structure. It performs drift scans of the sky at constant declination. We describe the design, calibration, noise level, and stability of this instrument based on the analysis of about 5% of 6200 h of on-sky observations through 2019 October. Beam pattern determinations using drones and the transit of bright sources are in good agreement, and compatible with electromagnetic simulations. Combining all the baselines, we make maps around bright sources and show that the array behaves as expected. A few hundred hours of observations at different declinations have been used to study the array geometry and pointing imperfections, as well as the instrument noise behaviour. We show that the system temperature is below 80 K for most feed antennas and that noise fluctuations decrease as expected with integration time, at least up to a few hundred seconds. Analysis of long integrations, from 10 nights of observations of the North Celestial Pole (NCP), yielded visibilities with amplitudes of 20–30 mK, consistent with the expected signal from the NCP radio sky with ${\lt}10\,$ mK precision for 1 MHz × 1 min binning. Hi-pass filtering the spectra to remove smooth spectrum signal yields a residual consistent with zero signal at the $0.5\,$ mK level.

(cosmology:) large-scale structure of the Universe↗
DOE OSTI2022

Squeeze Film Damper Experimental and Numerical Correlation: Test Setup Description and Parameter Identification of Dry System

The process of characterizing a damper involves both experimental techniques and model simulation. Experiments characterize dynamic behavior of a system through empirical modal analysis using impact and shaker testing. The layout of the test setup is crucial for a low-mass, nonlinear system. Physical arrangement, orientation of the system, and instrumentation affect the results that are discussed in this paper. These results can be used to validate a numerical simulation of the same system. With a validated model, important physical input parameters and modeling techniques can be determined and implemented in future designs. In other words, this modeling can be used with confidence to design alternative dampers that may be difficult, costly, and time-consuming to characterize experimentally.

Cook, Jason↗