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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ultrafast time-resolved 2D imaging of laser-driven fast electron transport in solid density matter using an x-ray free electron laser

High-power, short-pulse laser-driven fast electrons can rapidly heat and ionize a high-density target before it hydrodynamically expands. The transport of such electrons within a solid target has been studied using two-dimensional (2D) imaging of electron-induced Kα radiation. However, it is currently limited to no or picosecond scale temporal resolutions. Here, we demonstrate femtosecond time-resolved 2D imaging of fast electron transport in a solid copper foil using the SACLA x-ray free electron laser (XFEL). An unfocused collimated x-ray beam produced transmission images with sub-micron and ~10 fs resolutions. The XFEL beam, tuned to its photon energy slightly above the Cu K-edge, enabled 2D imaging of transmission changes induced by electron isochoric heating. Time-resolved measurements obtained by varying the time delay between the x-ray probe and the optical laser show that the signature of the electron-heated region expands at ~25% of the speed of light in a picosecond duration. Time-integrated Cu Kα images support the electron energy and propagation distance observed with the transmission imaging. The x-ray near-edge transmission imaging with a tunable XFEL beam could be broadly applicable for imaging isochorically heated targets by laser-driven relativistic electrons, energetic protons, or an intense x-ray beam.

47 OTHER INSTRUMENTATION↗
NASA NTRS2012

Constructing a Database from Multiple 2D Images for Camera Pose Estimation and Robot Localization

The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose.

Wolf, Michael↗
DOE OSTI2023

2D-imaging of absolute OH and H 2 O 2 profiles in a He–H 2 O nanosecond pulsed dielectric barrier discharge by photo-fragmentation laser-induced fluorescence

We report pulsed dielectric barrier discharges (DBD) in He–H 2 O and He–H 2 O–O 2 mixtures are studied in near atmospheric conditions using temporally and spatially resolved quantitative 2D imaging of the hydroxyl radical (OH) and hydrogen peroxide (H 2 O 2 ). The primary goal was to detect and quantify the production of these strongly oxidative species in water-laden helium discharges in a DBD jet configuration, which is of interest for biomedical applications such as disinfection of surfaces and treatment of biological samples. Hydroxyl profiles are obtained by laser-induced fluorescence (LIF) measurements using 282 nm laser excitation. Hydrogen peroxide profiles are measured by photo-fragmentation LIF (PF-LIF), which involves photo-dissociating H 2 O 2 into OH with a 212.8 nm laser sheet and detecting the OH fragments by LIF. The H 2 O 2 profiles are calibrated by measuring PF-LIF profiles in a reference mixture of He seeded with a known amount of H 2 O 2 . OH profiles are calibrated by measuring OH-radical decay times and comparing these with predictions from a chemical kinetics model. Two different burst discharge modes with five and ten pulses per burst are studied, both with a burst repetition rate of 50 Hz. In both cases, dynamics of OH and H 2 O 2 distributions in the afterglow of the discharge are investigated. Gas temperatures determined from the OH-LIF spectra indicate that gas heating due to the plasma is insignificant. The addition of 5% O 2 in the He admixture decreases the OH densities and increases the H 2 O 2 densities. The increased coupled energy in the ten-pulse discharge increases OH and H 2 O 2 mole fractions, except for the H 2 O 2 in the He–H 2 O–O 2 mixture which is relatively insensitive to the additional pulses.

hydrogen peroxide↗
DOE OSTI2022

2D imaging of absolute methyl concentrations in nanosecond pulsed plasma by photo-fragmentation laser-induced fluorescence

The methyl radical plays a central role in plasma-assisted hydrocarbon chemistry but is challenging to detect due to its high reactivity and strongly pre-dissociative electronically excited states. In this work, we report the development of a photo-fragmentation laser-induced fluorescence (PF-LIF) diagnostic for quantitative 2D imaging of methyl profiles in a plasma. This technique provides temporally and spatially resolved measurements of local methyl distributions, including in near-surface regions that are important for plasma-surface interactions such as plasma-assisted catalysis. The technique relies on photo-dissociation of methyl by the fifth harmonic of a Nd:YAG laser at 212.8 nm to produce CH fragments. These photofragments are then detected with LIF imaging by exciting a transition in the B-X(0, 0) band of CH with a second laser at 390 nm. Fluorescence from the overlapping A-X(0, 0), A-X(1, 1), and B-X(0, 1) bands of CH is detected near 430 nm with the A-state populated by collisional B-A electronic energy transfer. This non-resonant detection scheme enables interrogation close to a surface. The PF-LIF diagnostic is calibrated by producing a known amount of methyl through photo-dissociation of acetone vapor in a calibration gas mixture. We demonstrate PF-LIF imaging of methyl production in methane-containing nanosecond pulsed plasmas impinging on dielectric surfaces. Absolute calibration of the diagnostic is demonstrated in a diffuse, plane-to-plane discharge. Measured profiles show a relatively uniform distribution of up to 30 ppm of methyl. Relative methyl measurements in a filamentary plane-to-plane discharge and a plasma jet reveal highly localized intense production of methyl. The utility of the PF-LIF technique is further demonstrated by combining methyl measurements with formaldehyde LIF imaging to capture spatiotemporal correlations between methyl and formaldehyde, which is an important intermediate species in plasma-assisted oxidative coupling of methane.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

NESC GN&C TDT Workshop on 2D Image Motion Optical Transfer Functions, Pointing Performance Analysis, and Requirements

This course was prepared by the author in support of the NASA GN&C Technical Discipline Team (TDT). The purpose of this two-day course is to inform practicing GN&C engineers, and other system and subsystem engineers, including payload engineers and mission analysts, of methodologies to analyze the pointing performance of spacecraft and to write unambiguous pointing requirements that are relevant to optical payload performance. It is hoped that the seminar will contribute to a best-practices manual and contribute to accepted and uniform means of requirements definition, validation, and verification. The course material is designed to address the needs of not only practicing GN&C engineers, but also system and subsystem engineers of other disciplines, payload engineers, mission analysts, and even astronomers who need to understand how they interface to a GN&C subsystem. Much revision is the direct result of active student participation during the presentations and from feedback obtained through course evaluation forms.

2D Image↗
NASA NTRSDate not supplied

NESC GN&C TDT Workshop on 2D Image Motion Optical Transfer Functions, Pointing Performance Analysis, and Requirements

What You Will Learn: The focus is on payload imaging performance due to pointing motion. Some historical background on pointing performance analysis is given. The Optical Transfer Function (OTF) and Modulation Transfer Function (MTF) are defined. The imaging performance due to pointing motion is measured by image motion optical transfer functions (IM OTF). IM OTFs are defined for displacement, smear, and jitter motions, which are all rigorously defined. Deterministic and Statistical IM OTFs are briefly derived and graphically illustrated and compared. The IM OTFs are parameterized by pointing error metrics(PEM), which are means and covariances of displacement, smear, and jitter. Emphasis is on procedures and algorithms to evaluate the image motion optical transfer functions and pointing error metrics. Three procedures are covered, which depend on whether the pointing error data is from time-domain simulation, frequency-domain analysis, or stochastic modeling. A method to evaluate the relative contribution of disturbance sources and to identify the most significant contributors is presented. The presentation includes pertinent discussion of flexible structures and control-structure interaction. No single book can adequately cover this subject, so a book is not required for the course. A list of selected articles, reports, documents, and books is provided for reference and further study. Mathis kept to the minimum necessary to convey principles; lengthy derivations are left to the reference material. Graphics are used to illustrate concepts. As with any such learning endeavor, the knowledge gained will be retained and strengthened through actual practice.c©2019–2021 Mark E. Pittelkau— 5

NASA Engineering and Safety Center (NESC)↗
DOE OSTI2021

Measurements of electron temperature in high-energy-density plasmas using gated x-ray pinhole imaging

We present measurements of spatially and temporally resolved electron temperature in high-energy-density plasmas using gated x-ray pinhole imagers. A 2D image of bremsstrahlung x-ray self-emission from laser-driven plasma plumes is detected at the same time through two pinholes covered with different filter materials. By comparing the attenuated signal through each filter, a spatially resolved electron temperature as low as 0.1 keV can be estimated. Measurements of the plasma plume taken from different directions indicate that imaging through extended plasmas has a negligible effect on the temperature estimates. Methods for estimating the expected signal, selecting filters, and incorporating the response of the detector are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

2D coherence imaging measurements of C 2+ ion temperatures in the divertor of Wendelstein 7-X

For the first time, 2D ion temperature values are derived from coherence imaging spectroscopy (CIS) fringe contrast measurements by taking Zeeman line broadening effects into account during the analysis procedure of a spatial-heterodyne CIS instrument. This allowed 2D images of C 2+ ion temperatures (T i ) across the 3D-shaped island divertor of the Wendelstein 7-X stellarator. Ion temperatures ranging from 10 to 20 eV are observed for the C 2+ impurity species in the region above the divertor targets. During the transition from the attached to the detached plasma state, the C 2+ radiation zone moves from close to the divertor target towards the last closed flux surface. Within this radiation zone, C 2+ temperature does not decrease significantly. Experimentally, the coherence imaging measurements were cross-calibrated at one poloidal cross-section using a high resolution Echelle spectrometer, that shared its sightlines with the coherence imaging diagnostic. The spectra demonstrated that, apart from Doppler broadening, the Zeeman effect significantly contributes to the spectral line broadening and cannot be neglected when analyzing the CIS contrast data for T i extraction in the edge and scrape-off-layer of Wendelstein 7-X (W7-X), due to the relatively low temperatures (T i < 100 eV) and high magnetic fields (B ≈ 2.5 T).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Synthesis‐Related Nanoscale Defects in Mo‐Based Janus Monolayers Revealed by Cross‐Correlated AFM and TERS Imaging

2D Janus transition metal dichalcogenides (TMDs) are promising candidates for various applications including non-linear optics, energy harvesting, and catalysis. These materials are usually synthesized via chemical conversion of pristine TMDs. Nanometer-scale characterization of the obtained Janus materials’ morphology and local composition is crucial for both the synthesis optimization and the future device applications. In this work, we present the results of cross-correlated atomic force microscopy (AFM) and tip-enhanced Raman spectroscopy (TERS) study of Janus monolayers synthesized by the hydrogen plasma-assisted chemical conversion of MoSe 2 and MoS 2 . We demonstrate that the choice of both the growth substrate and the starting TMD influences the residual strain, thereby shaping the nanoscale morphology of the resulting Janus material. Furthermore, by employing TERS imaging, we show the presence of nanoscale islands (≈20 nm across) of MoSe 2 - ${\mathrm{Mo}}_{{\mathrm{Se}}}^{\mathrm{S}}$ (MoS 2 -${\mathrm{Mo}}_{\mathrm{S}}^{{\mathrm{Se}}}$) vertical heterostructures originating from the bilayer nanoislands in the precursor monolayer crystals. The understanding of the origins of nanoscale defects in Janus TMDs revealed in this study can help with further optimization of the Janus conversion process towards uniform and wrinkle-/crack-free Janus materials. Moreover, this work shows that cross-correlated AFM and TERS imaging is a powerful and accessible method for studying nanoscale composition and defects in Janus TMD monolayers.

2D materials↗
NASA NTRS2009

Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images

VESGEN is a newly automated, user-interactive program that maps and quantifies the effects of vascular therapeutics and regulators on microvascular form and function. VESGEN analyzes two-dimensional, black and white vascular images by measuring important vessel morphology parameters. This software guides the user through each required step of the analysis process via a concise graphical user interface (GUI). Primary applications of the VESGEN code are 2D vascular images acquired as clinical diagnostic images of the human retina and as experimental studies of the effects of vascular regulators and therapeutics on vessel remodeling.

Parsons-Wingerter, Patricia↗
DOE OSTI2021

2D-to-3D image translation of complex nanoporous volumes using generative networks

Image-based characterization offers a powerful approach to studying geological porous media at the nanoscale and images are critical to understanding reactive transport mechanisms in reservoirs relevant to energy and sustainability technologies such as carbon sequestration, subsurface hydrogen storage, and natural gas recovery. Nanoimaging presents a trade off, however, between higher-contrast sample-destructive and lower-contrast sample-preserving imaging modalities. Furthermore, high-contrast imaging modalities often acquire only 2D images, while 3D volumes are needed to characterize fully a source rock sample. In this work, we present deep learning image translation models to predict high-contrast focused ion beam-scanning electron microscopy (FIB-SEM) image volumes from transmission X-ray microscopy (TXM) images when only 2D paired training data is available. We introduce a regularization method for improving 3D volume generation from 2D-to-2D deep learning image models and apply this approach to translate 3D TXM volumes to FIB-SEM fidelity. We then segment a predicted FIB-SEM volume into a flow simulation domain and calculate the sample apparent permeability using a lattice Boltzmann method (LBM) technique. Results show that our image translation approach produces simulation domains suitable for flow visualization and allows for accurate characterization of petrophysical properties from non-destructive imaging data.

58 GEOSCIENCES↗
DOE OSTI2022

Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage

An automatic threat recognition (ATR) system is disclosed for scanning an article to recognize contraband items or items of interest contained within the article. The ATR system uses a CAT scanner to obtain a CT image scan of objects within the article, representing a plurality of 2D image slices of the article and its contents. Each 2D image slice includes information forming a plurality of voxels. The ATR system includes a computer and determines which voxels have a likelihood of representing materials of interest. It then aggregates those voxels to produce detected objects. The detected objects are further classified as items of interest vs. not of interest. The ATR system is based on learned parameters for a novel interaction of global and object context mechanisms. ATR system performance may be optimized by using jointly optimal global and object context parameters learned during training. The global context parameters may apply to the article as a whole and facilitate object detection. The object context parameters may apply to the individual object detections.

Paglieroni, David W.↗
DOE OSTI2025

professor

Professor is a tool to help you study complicated physical phenomena by providing tools to 1) fit machine learning models to 2D image arrays from simulations and 2) interactively explore these machine learning models in real time. Professor is most useful when studying ensembles of simulations. A typically workflow would look like: 1. A user is interested in how parameters A, B, C, & D influence some complicated physics 2. User setups up parameterized simulations to study ABCD and the results of these simulations to be image arrays (a 2d matrix of float32 values) 3. User runs an ensemble of simulations studying ABCD creating a dataset of image arrays 4. User runs `prof-trainer` to fit a machine learning model to learn the mapping from [A,B,C,D] to the image arrays 5. User then uses `prov-vis` to interactively explore the machine learning model in real time, gaining their insight into how those parameters influence the physics 6. Go profess your idea about ABCD!

Collis, HenryH [Lawrence Livermore National Labora↗