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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Baryon Mapping Experiment (BMX), a 21cm intensity mapping pathfinder

The Baryon Mapping eXperiment (BMX) is an interferometric array designed as a pathfinder for a future post- reionization 21 cm intensity mapping survey. It consists of four 4-meter parabolic reflectors each having offset pyramidal horn feed, quad-ridge orthomode transducer, temperature-stabilized RF amplification and filtering, and pulsed noise injection diode. An undersampling readout scheme uses 8-bit digitizers running at 1.1 Gsamples/sec to provide access to signals from 1.1 - 1.55 GHz (third Nyquist zone), corresponding to HI emission from sources at redshift 0 < z < 0.3. An FX correlator is implemented in GPU and generates 28 GB/day of time-ordered visibility data. About 7,000 hours of data were collected from Jan. 2019 - May 2020, and we will present results on system performance including sensitivity, beam mapping studies, observations of bright celestial targets, and system electronics upgrades. BMX is a pathfinder for the proposed PUMA intensity mapping survey in the 2030s.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗
DOE OSTI2025

Current-Regulated Arc Modulator Optimization

n this study, the performance of a current-regulated arc modulator was investigated with a focus on its role in initiating and sustaining plasma discharge within the Magnetron Body of the LINAC system. The analysis centered on how switching components, circuit topology, and feedback loop architecture influence critical factors such as energy efficiency, discharge stability, and long-term plasma containment. Particular attention was given to variations in pulse termination behavior, as observed through oscilloscope traces, which revealed inconsistencies affecting the duty factor and cathode temperature. These fluctuations have downstream effects on the cesium-coated cathode surface, thereby impacting H⁻ ion production and beam reliability. Simulation-based testing in LTspice was used to evaluate noise suppression techniques and arc current regulation schemes, revealing how optimized snubber networks, improved pulse shaping, and feedback stability can mitigate modulator-induced noise. The results ide

Campos, Nathan↗
DOE OSTI2025

Development and Testing of a new Current-Regulated Arc Modulator for the LINAC

In this study, the performance of a current-regulated arc modulator was investigated with a focus on its role in initiating and sustaining plasma discharge within the Magnetron Body of the LINAC system. The analysis centered on how switching components, circuit topology, and feedback loop architecture influence critical factors such as energy efficiency, discharge stability, and long-term plasma containment. Particular attention was given to variations in pulse termination behavior, as observed through oscilloscope traces, which revealed inconsistencies affecting the duty factor and cathode temperature. These fluctuations have downstream effects on the cesium-coated cathode surface, thereby impacting H⁻ ion production and beam reliability. Simulation-based testing in LTspice was used to evaluate noise suppression techniques and arc current regulation schemes, revealing how optimized snubber networks, improved pulse shaping, and feedback stability can mitigate modulator-induced noise. The results identified hardware level parameters that significantly enhance discharge repeatability and improve overall plasma performance under operational conditions.

Campos, Nathan [Unlisted, US; Fermilab]↗
DOE OSTI2023

Concentration fluctuations and flammability of cryo-compressed hydrogen and methane jets

Compressed hydrogen stored at cryogenic temperatures has a much higher density than room-temperature storage, which enables large-scale hydrogen storage and transport. An understanding of the release of cryogenic hydrogen from pressurized vessels is needed to evaluate the risk and safety concerns with the use of this fuel. Here, the present work extends the analysis of previous experimental studies that measured the gas concentrations of cryo-compressed hydrogen jets and methane jets using a laser Raman scattering diagnostic system. Since the Raman signals are very small, a denoising algorithm was applied to significantly reduce the noise to enable statistical analysis of the data. The transient features of the turbulent jets were characterized by their concentration intermittencies and probability density functions (PDFs). A two-part PDF was developed to predict the bimodal features of the jet concentration distributions. Then, the flammability factors of the cryogenic jets were calculated based on the intermittency and the PDF.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗
DOE OSTI2024

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr 2 Ge 2 Te 6 , CuIr 2 S 4 , and CrCl 3 . In conclusion, our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Movable Thermometer System in ProtoDUNE

The movable temperature profiler is a 7 m vertical array of 24 sensors that measures cryogenic temperatures with a precision of a few mK. This precision is necessary to monitor the efficiency of re-circulation and purification of liquid-argon inside large liquid-argon based neutrino detectors. Liquid argon temperature impacts electron (signal) drift velocity, flow, purity distribution and thus the overall energy calibration. The temperature profiler is motorized and moves vertically, while in the detector, and cross-calibrates neighboring sensors. The temperature offsets between each sensor cancel the effects of electromagnetic noise. This poster reports on the temperature measurements and such in-situ cross-calibrations at ProtoDUNE (single phase) at CERN.}

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

GaN-based W-band receiver chip development for fusion plasma diagnostics

Millimeter-wave diagnostics have proven effective on various magnetic fusion devices worldwide, yet the formidable challenges posed by the harsh environments of future burning plasma devices, characterized by extreme temperatures, pressures, and radiation levels, remain a significant hurdle. To address these challenges, the utilization of wide bandgap Gallium Nitride (GaN)-based millimeter-wave diagnostics is a most promising solution for fusion reactor safety monitoring and control. A noteworthy W-band GaN-based system-on-chip receiver has been the demonstrated by employing HRL T3 40 nm GaN technology. This receiver chip, compactly designed with dimensions of 3 × 5 mm 2 , incorporates essential components such as the 75–110 GHz RF Low-Noise Amplifier (LNA), mixer, Intermediate Frequency (IF) amplifier, and Local Oscillator (LO) chain. This receiver chip will be packaged as a millimeter-wave receiver module and applied on the DIII-D National Fusion Facility, for fusion plasma edge shape monitoring for operational safety and dangerous disruption prediction. The laboratory measurement results have demonstrated suitable performance. Furthermore, this advancement is pivotal for accurate analysis of plasma behavior in the extreme conditions of burning plasma devices, driving progress in fusion research and technology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Image processing methods for Rayleigh scattering measurements of diesel spray mixing at high repetition rate

This work describes the diagnostic implementation and image processing methods to quantitatively measure diesel spray mixing injected into a high-pressure, high-temperature environment. We used a high-repetition-rate pulse-burst laser developed in-house, a high-speed CMOS camera, and optimized the optical configuration to capture Rayleigh scattering images of the vaporized fuel jets inside a constant volume chamber. The experimental installation was modified to reduce reflections and flare levels to maximize the images’ signal-to-noise ratios by anti-reflection coatings on windows and surfaces, as well as series of optical baffles. Because of the specificities of the high-speed system, several image processing techniques had to be developed and implemented to provide quantitative fuel concentration measurements. We find that these methods involve various correction procedures such as camera linearity, laser intensity fluctuation, dynamic background flare, as well as beam-steering effects. Image inpainting was also applied to correct the Rayleigh scattering signal from large scatterers (e.g. particulates). The experiments demonstrate that applying planar laser Rayleigh scattering at high repetition rate to quantitatively resolve the mixing of fuel and ambient gases in diesel jets is challenging, but possible. The thorough analysis of the experimental uncertainty and comparisons to past data prove that such measurements can be accurate, whilst providing valuable information about the mixing processes of high-pressure diesel jets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Feasibility study of a high spatial and time resolution beam emission spectroscopy diagnostic for localized density fluctuation measurements in Lithium Tokamak eXperiment-β (LTX-β)

Trapped electron mode (TEM) is the main source of turbulence predicted for the unique operation regime of a flat temperature profile under low-recycling conditions in the LTX-β tokamak, while ion temperature gradient driven turbulence may also occur with gas fueling from the edge. To investigate mainly TEM scale density fluctuations, a high spatial and time resolution 2D beam emission spectroscopy (BES) diagnostic is being developed. Apart from spatially localized density turbulence measurement, BES can provide turbulence flow and flow shear dynamics. This BES system will be realized using an avalanche photodiode-based camera and narrow band interference filter. The system can acquire data at 2 MHz. Simulations with the Simulation of Spectra (SOS) code indicate that a high signal to noise ratio can be achieved with the proposed system. This will enable sampling the density fluctuations at this high time resolution. Finally, the design considerations and system optimization using the SOS code are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Scanning SQUID microscopy in a cryogen-free dilution refrigerator

We report a scanning superconducting quantum interference device (SQUID) microscope in a cryogen-free dilution refrigerator with a base temperature at the sample stage of at least 30 mK. The microscope is rigidly mounted to the mixing chamber plate to optimize thermal anchoring of the sample. The microscope housing fits into the bore of a superconducting vector magnet, and our design accommodates a large number of wires connecting the sample and sensor. Through a combination of vibration isolation in the cryostat and a rigid microscope housing, we achieve relative vibrations between the SQUID and the sample that allow us to image with micrometer resolution over a 150 μm range while the sample stage temperature remains at base temperature. To demonstrate the capabilities of our system, we show images acquired simultaneously of the static magnetic field, magnetic susceptibility, and magnetic fields produced by a current above a superconducting micrometer-scale device.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Boosting SNR of cascaded FBGs in a sapphire fiber through a rapid heat treatment

This Letter reports the performance of femtosecond (fs) laser-written distributed fiber Bragg gratings (FBGs) under high-temperature conditions up to 1600°C and explores the impact of rapid heat treatment on signal-to-noise ratio (SNR) enhancement. FBGs are essential for reliable optical sensing in extreme temperature environments. Comprehensive tests demonstrate the remarkable performance and resilience of FBGs at temperatures up to 1600°C, confirming their suitability for deployment in such conditions. Here, the study also reveals significant fringe visibility improvements of up to ∼10 dB on a 1-m-long sapphire optical fiber through rapid heat treatment, representing a first-time achievement to the best of our knowledge. These enhancements are vital for improving the SNR and overall performance of optical fiber systems in extreme temperatures. Furthermore, the research attains long-term stability for the cascaded FBGs over a 24-hr period at 1600°C. This research expands our understanding of the FBG behavior in high-temperature environments and opens avenues for developing robust optical fiber systems for energy, aerospace, oil and gas, and high-temperature distributed sensing applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

CROCUS Sodar Measurements of Lower Atmospheric Wind Profiles at Argonne Testbed for Multiscale Observational Science (ATMOS) Site

The Scintec MFAS Sodar (Multiple-Frequency Acoustic Sounder) is an autonomous, ground-based acoustic remote sensing system designed to measure vertical profiles of horizontal wind speed, wind direction, and vertical velocity in the lower atmosphere. The instrument transmits sequences of acoustic pulses and detects the Doppler-shifted sound waves backscattered by small-scale temperature and velocity fluctuations caused by atmospheric turbulence. From these Doppler shifts, the system derives three-dimensional wind vectors by combining radial velocities from multiple beam orientations.The MFAS Sodar operates with a first usable range gate beginning at approximately 30 m above ground level and a configurable vertical resolution of 10 m. Under favorable acoustic conditions, the system provides wind profiles extending up to 600 m above ground level. Measurements are processed into 15-minute averaged profiles containing wind speed, direction, vertical velocity, and diagnostic quantities such as signal-to-noise ratio and echo strength.This dataset was collected at the Argonne Testbed for Multiscale Observational Science (ATMOS) facility in Lemont, Illinois, as part of DOE's CROCUS Urban Integrated Field Laboratory (UIFL) initiative. The purpose of these observations is to characterize the vertical wind structure and boundary-layer evolution across the urban–suburban gradient of the greater Chicago region. In particular, these data are intended to improve understanding of how local meteorology, such as lake-breeze penetration, nocturnal jets, and daytime mixing, varies between the densely built urban core and the suburban periphery. The MFAS observations provide critical context for evaluating high-resolution model simulations and for integrating with complementary lidar, radar, and in-situ meteorological measurements within the broader CROCUS UIFL network.All data are archived in NetCDF (Network Common Data Form) format and include wind and diagnostic parameters. The files can be accessed and analyzed using standard software that supports NetCDF, such as Python (e.g., xarray, netCDF4), MATLAB, R (e.g., ncdf4, raster), or Panoply (NASA’s NetCDF visualization application).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Global decline in ocean memory over the 21st century

Ocean memory, the persistence of ocean conditions, is a major source of predictability in the climate system beyond weather time scales. We show that ocean memory, as measured by the year-to-year persistence of sea surface temperature anomalies, is projected to steadily decline in the coming decades over much of the globe. This global decline in ocean memory is predominantly driven by shoaling of the upper-ocean mixed layer depth in response to global surface warming, while thermodynamic and dynamic feedbacks can contribute substantially regionally. As the mixed layer depth shoals, stochastic forcing becomes more effective in driving sea surface temperature anomalies, increasing high-frequency noise at the expense of persistent signals. Reduced ocean memory results in shorter lead times of skillful persistence-based predictions of sea surface thermal conditions, which may present previously unknown challenges for predicting climate extremes and managing marine biological resources under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Intrinsic and induced quantum quenches for enhancing qubit-based quantum noise spectroscopy

Quantum sensing protocols that exploit the dephasing of a probe qubit are powerful and ubiquitous methods for interrogating an unknown environment. They have a variety of applications, ranging from noise mitigation in quantum processors, to the study of correlated electron states. Here, we discuss a simple strategy for enhancing these methods, based on the fact that they often give rise to an inadvertent quench of the probed system: there is an effective sudden change in the environmental Hamiltonian at the start of the sensing protocol. These quenches are extremely sensitive to the initial environmental state, and lead to observable changes in the sensor qubit evolution. We show how these new features give access to environmental response properties. This enables methods for direct measurement of bath temperature, and for detecting non-thermal equilibrium states. We also discuss how to deliberately control and modulate this quench physics, which enables reconstruction of the bath spectral function. Extensions to non-Gaussian quantum baths are also discussed, as is the application of our ideas to a range of sensing platforms (e.g., nitrogen-vacancy (NV) centers in diamond, semiconductor quantum dots, and superconducting circuits).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A characterization of quantum Kerr optical frequency combs

Quantum Kerr optical frequency combs are generated by pumping a high-Q microresonator with a continuous wave resonant laser. Below threshold, two pump photons are symmetrically up- and down-converted as twin photons via spontaneous four-wave mixing, thereby generating up to a hundred paired channels. Furthermore, these chipscale, high-dimensional and room-temperature systems are expected to play a major role in quantum engineering. However, their theoretical description is still unclear. Here, we present an explicit description of this quantum system via a frequency-bin state and its density operator, and explore the properties of the eigenkets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Doppler Lidar Motion-Correction Wind Profiles (DLMCPROF-WIND) Value-Added Product Report

Wind speed and direction, together with pressure, temperature, and relative humidity, are the most fundamental atmospheric state parameters. Accurate measurement of these parameters is crucial for numerical weather prediction. Vertically resolved wind measurements in the atmospheric boundary layer are particularly important for modeling pollutant and aerosol transport. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility currently operates several scanning coherent Doppler lidar (DL) systems that provide accurate height-resolved measurements of wind speed and direction. These instruments operate in the near infrared (IR;1.5 microns) and provide range-resolved measurements of radial velocity, attenuated aerosol backscatter, and signal-to-noise ratio (SNR). The systems are operated using a fixed scan schedule consisting of plan position indicator (PPI) or Doppler Beam-Swing (DBS) scans. PPI scans are performed by scanning the beam in azimuth while maintaining a fixed elevation angle, and DBS scans are similar but typically also include a vertical beam. Radial velocity data from these scans are processed to yield profiles of wind speed direction. For stationary ground-based deployments, the Doppler Lidar Horizontal Wind Profiles (DLPROF-WIND) Value-Added-Product (VAP) provides height- and time-resolved measurements of the winds (Newsom and Krishnamurthy 2022). For operation on a moving platform, modifications to the existing DLPROF-WIND VAP are required to compensate for the effects of the platform motion. This report describes a parallel VAP, DLMCPROF-WIND, that was developed for computing motion-compensated wind profiles from ARM Doppler lidar data acquired during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign, when the lidar was deployed on the German icebreaker Polarstern.

54 ENVIRONMENTAL SCIENCES↗