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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

High-speed (20 kHz) digital in-line holography for transient particle tracking and sizing in multiphase flows

High-speed (20 kHz) digital in-line holography (DIH) is applied for 3D quantification of the size and velocity of fragments formed from the impact of a single water drop onto a thin film of water and burning aluminum particles from the combustion of a solid rocket propellant. To address the depth-of-focus problem in DIH, a regression-based multiframe tracking algorithm is employed, and out-of-plane experimental displacement accuracy is shown to be improved by an order-of-magnitude. Comparison of the results with previous DIH measurements using low-speed recording shows improved positional accuracy with the added advantage of detailed resolution of transient dynamics from single experimental realizations. Furthermore, the method is shown to be particularly advantageous for quantification of particle mass flow rates. For the investigated particle fields, the mass flows rates, which have been automatically measured from single experimental realizations, are found to be within 8% of the expected values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Phase conjugate digital inline holography (PCDIH)

We report digital inline holography (DIH) provides instantaneous three-dimensional (3D) measurements of diffracting objects; however, phase disturbances in the beam path can distort the imaging. In this Letter, a phase conjugate digital inline holography (PCDIH) configuration is proposed for removal of phase disturbances. Brillouin-enhanced four-wave mixing produces a phase conjugate signal that back propagates along the DIH beam path. Finally, the results demonstrate the removal of distortions caused by gas-phase shocks to recover 3D images of diffracting objects.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fiber-Optic Sensing for Earthquake Hazards Research, Monitoring, and Early Warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

58 GEOSCIENCES↗
DOE OSTI2016

Neutrino physics at Drexel

Final technical report for work performed on the reactor neutrino experiments (Double Chooz, PROSPECT) and DUNE beamline monitoring.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

An Overview of the Los Alamos Inertial Confinement Fusion and High-Energy-Density Physics Research Programs

The Los Alamos Inertial Confinement Fusion and Science Programs engage in a vigorous array of experiments, theory, and modeling. We use the three major High Energy Density facilities, NIF, Omega, and Z to perform experiments. These include opacity, radiation transport, hydrodynamics, ignition science, and burn experiments to aid the ICF and Science campaigns in reaching their stewardship goals. The ICF program operates two nuclear diagnostics at NIF, the neutron imaging system and the gamma reaction history instruments. Both systems are being expanded with significant capability enhancements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

2016 Research Final Presentation

These are slides which show an example of research at Los Alamos National Laboratory done by E.C. Koskelo to show college professors in the hopes of earning a research position or fellowship position. In summary, this researcher developed a new in-situ technique for the inspection of additively manufactured parts, created an algorithm which can correct "skewed" scans of angular parts/taken at oblique angles, and used AWS to detect hidden defects and thickness changes in aerospace composites.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Transportable, Low-Dose Active Fast-Neutron Imaging

This document contains a description of the method of transportable, low-dose active fast-neutron imaging as developed by ORNL. The discussion begins with the technique and instrumentation and continues with the image reconstruction and analysis. The analysis discussion includes an example of how a gap smaller than the neutron production spot size and detector size can be detected and characterized depending upon the measurement time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Spotlight SAR Data Collection Geometry from ECEF Coordinates

High-performance spotlight Synthetic Aperture Radar (SAR) requires measurement of the radars motion during the synthetic aperture. A convenient coordinate frame for motion measurement is often not the convenient coordinate frame for motion compensation during the SAR data generation and image formation processing. A convenient frame for radar motion measurement is the Earth-Centered Earth-Fixed (ECEF) coordinate frame, whereas spotlight SAR processing typically require s polar coordinates from a selected Scene Reference Point (SRP). This report presents the conversion from ECEF coordinates to appropriate parameters for SAR processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

The Tiny Heater: Creating Heat with Hybrid Nano-Antennas [LDRD HQ Highlights Article]

SRNL scientists demonstrate that an electromagnetic field, either as a light or magnetic field, is selectively coupled to shape-selective hybrid nano-antennas for efficient thermal processes. Localized heating occurs extremely fast, reducing the ‘wasted' thermal load on the environment. Being non-contact, efficient, and highly selective, the required input energy is greatly diminished. By strategically placing nano-antennas at desired locations, heat can be controlled at the nano-level. The location for nano-antennas, and the subsequent energy deposition, may be fine-tuned through specific chemical, steric, or magnetic interactions. The nano-antennas, composed of combinations of plasmonic, magnetic, and hydride components, are used for controlled release of hydrogen isotopes, chemotherapy drugs, environmental contaminants, enhanced catalytic processes, (bio)imaging and therapeutics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗
DOE OSTI2022

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this project, we used UAV-based multispectral imagery collected from MicaSense RedEdge-M on a DJI Matrice 600 Pro for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. The raw images were processed with Pix4D Mapper to create the reflectance data, and vegetation indices were calculated from a UAV-based multispectral camera. Statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potential for multiple traits associated with sustainable production of switchgrass. One statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait.

CBI↗
DOE OSTI2023

Sharing leaky-integrate-and-fire neurons for memory-efficient spiking neural networks

Spiking Neural Networks (SNNs) have gained increasing attention as energy-efficient neural networks owing to their binary and asynchronous computation. However, their non-linear activation, that is Leaky-Integrate-and-Fire (LIF) neuron, requires additional memory to store a membrane voltage to capture the temporal dynamics of spikes. Although the required memory cost for LIF neurons significantly increases as the input dimension goes larger, a technique to reduce memory for LIF neurons has not been explored so far. To address this, we propose a simple and effective solution, EfficientLIF-Net, which shares the LIF neurons across different layers and channels. Our EfficientLIF-Net achieves comparable accuracy with the standard SNNs while bringing up to ~4.3× forward memory efficiency and ~21.9× backward memory efficiency for LIF neurons. We conduct experiments on various datasets including CIFAR10, CIFAR100, TinyImageNet, ImageNet-100, and N-Caltech101. Furthermore, we show that our approach also offers advantages on Human Activity Recognition (HAR) datasets, which heavily rely on temporal information. The code has been released at https://github.com/Intelligent-Computing-Lab-Yale/EfficientLIF-Net.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Digital Miniature Cathode Ray Magnetometer

In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of operating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which then emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only records the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innovation lies in the combination of electron beam projection, CMOS imager scintillation-based detection, and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device’s utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe’s performance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.

Turqueti, Marcos↗
DOE OSTI2020

On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source

As work continues in neutron computed tomography, at Los Alamos Neutron Science Center (LANSCE) and other locations, source reliability over the long imaging times is an issue of increasing importance. Moreover, given the time commitment involved in a single neutron image, it is impractical to simply discard a scan and restart in the event of beam instability. In order to mitigate the cost and time associated with these options, strategies are presented in the current work to produce a successful reconstruction of computed tomography data from an unstable source. The present work uses a high energy neutron tomography dataset from a simulated munition collected at LANSCE to demonstrate the method, which is general enough to be of use in conjunction with unstable X-ray computed tomography sources as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Gold Nanoparticles AuNP Decorated on Fused Graphene-like Materials for Application in a Hydrogen Generation

The search for a sustainable, alternative fuel source to replace fossil fuels has led to an increased interest in hydrogen fuel. This combustible gas is not only clean-burning but can readily be produced via the hydrolysis of sodium borohydride. The main drawback of this reaction is that the reaction occurs relatively slowly and requires a catalyst to improve efficiency. This study explored a novel composite material made by combining gold nanoparticles and fused graphene-like materials (AuFGLM) as a catalyst for generating hydrogen via sodium borohydride. The novel fused graphene-like material (FGLM) was made with a sustainable dextrose solution and by using a pressure-processing method. Imaging techniques showed that FGLM appears to be an effective support template for nanoparticles. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and Raman spectroscopy were used to characterize and determine the size, shape, and structure of nanoparticles and composites. The TEM study characterized the fused carbon backbone as it began to take on a rounder shape. The TEM images also revealed that the average diameter of the gold nanoparticle was roughly 23 nm. The FTIR study confirmed O-H, C-C, and C=O as functional groups in the materials. The EDS analysis showed that the composite contained approximately 6.3% gold by weight. The crystal structures of FGLM and AuFGLM were identified via P-XRD analysis. Various reaction conditions were used to test the catalytic ability of AuFGLM, including various solution pHs, temperatures, and doses of NaBH 4 . It was observed that optimal reaction conditions included high temperature, an acidic solution pH, and a higher dose of NaBH 4 . The activation energy of the reaction was determined to be 45.5 kJ mol -1 , and it was found that the catalyst could be used multiple times in a row with an increased volume of hydrogen produced in ensuing trials. The activation energy of this novel catalyst is competitive compared to similar catalysts and its ability to produce hydrogen over multiple uses makes the material an exciting choice for catalyzing the hydrolysis of NaBH 4 for use as a hydrogen fuel source.

08 HYDROGEN↗