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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Monte Carlo Study of Imaging Plate Response to Laser-Driven Aluminum Ion Beams

We measured the response of BAS-TR imaging plate (IP) to energetic aluminum ions up to 222 MeV, and compared it with predictions from a Monte Carlo simulation code using two different IP response models. Energetic aluminum ions were produced with an intense laser pulse, and the response was evaluated from cross-calibration between CR-39 track detector and IP energy spectrometer. For the first time, we obtained the response function of the BAS-TR IP for aluminum ions with a kinetic energy as high as 222 MeV. On close examination of the two IP response models, we confirm that the exponential model fits our experimental data better. Moreover, we find that the IP sensitivity in the exponential model is nearly constant in this energy range, suggesting that the response function can be determined even with little experimental data.

Won, Junho↗
DOE OSTI2021

Passive method to measure strength of turbulence

Disclosed is a method to passively measure and calculate the strength of turbulence via the index of refraction structure constant Cn2 from video imagery gathered by an imaging device, such as a video camera. Processing may occur with any type computing device utilizing a processor executing machine executable code stored on memory. This method significantly simplifies instrumentation requirements, reduces cost, and provides rapid data output. This method combines an angle of arrival methodology, which provides scale factors, with a new spatial/temporal frequency domain method. As part of the development process, video imagery from high speed cameras was collected and analyzed. The data was decimated to video rates such that statistics could be computed and used to confirm that this passive method accurately characterizes the atmospheric turbulence. Cn2 accuracy from this method compared well with scintillometer data through two full orders of magnitude and more capability is expected beyond this verification.

O'Neill, Mary Morabito↗
DOE OSTI2022

Numerical Investigation of the Spark Discharge Process in a Crossflow

The present study numerically investigates the spark discharge process under crossflow conditions using a thermal equilibrium plasma solver that fully couples the electromagnetic physics and fluid dynamics in a computational framework. Numerical results are validated by the comparison with experimental data. Here, the spark discharge experiment is performed in a constant volume vessel using an inductive coil ignition system for automotive applications, and the evolution of the spark channel is measured using high-speed imaging. The crossflow in the gap between the spark-plug electrodes is generated by a rotating fan with two different fan speeds, and the flow velocity across the gap is characterized by particle image velocimetry (PIV) measurement. A computational fluid dynamics (CFD) solver is employed to simulate the crossflow and provide the flow field variables (velocity, pressure, temperature) to the plasma solver. The crossflow velocity predicted in the flow simulation agrees well with the PIV data in that the non-uniform velocity profiles at monitoring points are reproduced by the CFD code. With the crossflow initialization in the plasma solver, the simulated spark discharge process from the breakdown to spark discharge matches the experimental data, including the voltage and circuit waveforms and the high-speed images of the spark channel evolution. The stretch of spark channel captured by plasma simulations agrees with the measured data. The plasma simulation reveals that the mean temperature of the spark channel is maintained at 5000 K during the discharge phase, and the temperature varies along the spark channel so that the highest value is obtained at the spark root on the center electrode. Overall, the results presented in this paper are meant to provide valuable information about the properties of the plasma generated by the spark discharge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

In-situ strain behavior and BISON simulations of Zircaloy cladding subjected to temperature cycling separate-effects tests in a steam environment

Understanding fuel system performance during anticipated transients without scram (ATWSs) in boiling water reactors (BWRs) is necessary for refining current and future safety limits. High-fidelity material models and simulations are fundamental to rigorous assessment of zirconium-based cladding performance. However, experimental thermomechanical data during simulated ATWSs to validate these modes are limited. To provide relevant in-situ data, Zircaloy-4 cladding was subjected to cyclic heating in a steam environment to simulate an out-of-pile BWR ATWS. Digital image correlation was used to capture the cladding strain behavior in-situ for comparison against simulations using the BISON finite element code. Conventional high-temperature models were compared using multiple schemes to gain a better understanding of the applicability of three BISON models to BWR ATWS: (1) the default combination of creep models in BISON, (2) the high-temperature Erbacher model alone, and (3) the low-temperature Limback-Andersson model alone. The cases run with the Limback-Andersson model alone produced the lowest root mean square error (RMSE). The lowest RMSE for the Limback-Andersson model alone was 0.659%, and the highest RMSE reported was 4.22%. A data gap within the model in the temperature regime of interest was also identified, and to account for this gap, the current model in BISON is linearly interpolated between two separate datasets. In conclusion, this evaluation highlights the need to either develop a new model or to improve the existing model to capture transient creep effects resulting from a cyclic temperature transient.

Anticipated transient without SCRAM↗
DOE OSTI2021

AD_LTEM

This software uses AI tools for enhanced functional imaging using Lorentz transmission electron microscopy by retrieving phase shift at higher spatial resolution, and under noisy conditions. This is a companion code for a publication that is currently being submitted (APT # 164160).

PHATAK, CHARUDATTA↗
DOE OSTI2025

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗
DOE OSTI2024

Bulk reconstruction and non-isometry in the backwards-forwards holographic black hole map

The backwards-forwards map, introduced as a generalization of the non-isometric holographic maps of the black hole interior of Akers, Engelhardt, Harlow, Penington, and Vardhan to include non-trivial dynamics in the effective description, has two possible formulations differing in when the post-selection is performed. While these two forms are equivalent on the set of dynamically generated states — states formed from unitary time evolution acting on well-defined initial configurations of infalling matter — they differ on the generic set of states necessary to describe the apparent world of the infalling observer. We show that while both versions successfully reproduce the Page curve, the version involving post-selection as the final step, dubbed the backwards-forwards-post-selection (BFP) map, has the desirable properties of being non-isometric but isometric on average and providing state-dependent reconstruction of bulk operators, while the other version does not. Thus the BFP map is a suitable non-isometric code describing the black hole interior including interior interactions.

3-D Image Reconstruction↗
DOE OSTI2024

Beyond Binary: Automated PLC Memory Forensics through RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and the evolution of industrial control systems (ICS) to adopt Internet-based technologies enhanced productivity, but have inadvertently increased their vulnerability to cyber-based malicious attacks. When an ICS system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies to safeguard against future instances. Memory forensics is critical in the analysis process to ascertain what occurred. To date, approaches to analyze the persistent memory in ICS devices are limited, and almost nonexistent for volatile memory. This paper proposes an automated methodology, COMA, for PLC memory dump analysis using computer vision and deep learning techniques. Specifically, COMA converts the sequences of bytes in a PLC memory dump to RGB pixels and creates a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. COMA then uses the trained model to automatically segment new memory images and extract forensic artifacts. We evaluate COMA on a Schneider Electric Modicon M221 PLC involving two cyber-based attack scenarios: (i) code injection and (ii) code modification. The empirical results show that COMA can successfully detect attack artifacts in memory dumps in both scenarios.

Asmar Awad, Rima↗
DOE OSTI2023

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗
DOE OSTI2024

Data Visualization: Augmented Reality

In recent years, there has been an increasing interest in developing new technologies for automated characterization and visualization of condition monitoring data. Augmented Reality (AR) is a technology that is being developed to improve such data visualization. Augmented reality has been defined as a technology that merges virtual and physical components in real-time, and in three dimensions. Wearable, commercially-available AR devices allow onsite engineers and technicians to perform inspection tasks with significantly more available information such as comparisons of past and present sensor and imager data, onsite data analysis and result displays, and various forms of metadata including technical drawings, previous inspection reports and maintenance histories, operation manuals, codes and standards, and holograms representing data analysis results superimposed onto the in situ monitored system.

42 ENGINEERING↗
DOE OSTI2021

The Anatomy of an Unusual Edge-on Protoplanetary Disk. I. Dust Settling in a Cold Disk

As the earliest stage of planet formation, massive, optically thick, and gas-rich protoplanetary disks provide key insights into the physics of star and planet formation. When viewed edge-on, high-resolution images offer a unique opportunity to study both the radial and vertical structures of these disks and relate this to vertical settling, radial drift, grain growth, and changes in the midplane temperatures. In this work, we present multi-epoch Hubble Space Telescope and Keck scattered light images, and an Atacama Large Millimeter/submillimeter Array 1.3 mm continuum map for the remarkably flat edge-on protoplanetary disk SSTC2DJ163131.2–242627, a young solar-type star in ρ Ophiuchus. We model the 0.8 μm and 1.3 mm images in separate Markov Chain Monte Carlo (MCMC) runs to investigate the geometry and dust properties of the disk using the MCFOST radiative transfer code. In scattered light, we are sensitive to the smaller dust grains in the surface layers of the disk, while the submillimeter dust continuum observations probe larger grains closer to the disk midplane. An MCMC run combining both data sets using a covariance-based log-likelihood estimation was marginally successful, implying insufficient complexity in our disk model. The disk is well characterized by a flared disk model with an exponentially tapered outer edge viewed nearly edge-on, though some degree of dust settling is required to reproduce the vertically thin profile and lack of apparent flaring. A colder than expected disk midplane, evidence for dust settling, and residual radial substructures all point to a more complex radial density profile to be probed with future, higher-resolution observations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Water chemistry in flume channel and hyporheic zone (i.e., porewater) associated with: “Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry”

Dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), molecular data for organic matter, and biochemical reactions for surface water and porewater (i.e., hyporheic zone) collected from a water recirculating flume located at the University of Texas, Austin. The flume contained real river water from Lower Colorado River(Austin, TX) and clean sand. Hyporheic exchange in the flume was induced through The study aims to understand relationships between aerobic metabolism of organic matter and molecular characteristics of organic matter, such as thermodynamic signature and nitrogen content, through the extent of the hyporheic zone at 10 cm- resolution, and through time. During the experiment, organic matter (dry leaves) was added to the flume and removed after 24 hours. The water samples were collected before the addition of leaves, at the time of removal of leaves, and at hour 72. The water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and total organic carbon (TOC) and total nitrogen (TN) analysis. Dissolved oxygen content throughout the surface water and the hyporheic zone of the flume was measured with a large planar optode. This data package is associated with the publication ’ Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry’ published in Environmental Science and Technology (Turețcaia et al., 2023 https://doi.org/10.1021/acs.est.3c04765). The dataset is comprised of five folders (1) Diss_O2_pic, (2) input_files (3) output_files; (4) python_code; and (5) R_code . Diss_O2_pic contains siximages of dissolved oxygen distribution in a bedform at hours 0, 24, and 72 of the experiment conducted in a large recirculation flume. Images are in separate R and G channels (i.e., RGB). The input_files contains (1) a csv file with FTICR peaks identified within each sample, (2) a csv file with molecular information pertinent to FTICR data with Gibbs free energy calculations adjusted for environmental temperature, (3) a csv file containing concentrations of non-purgeable organic carbon measured throughout the experiment , (4) a csv file containing concentrations of total nitrogen measured throughout the experiment, (5) a csv file containing total biochemical reactions (i.e., transformations) identified in the dataset, (6) a csv containing transformation profiles, and (7) a csv file containing transformations with formulas, and (8) a jpg file with schematic representation of locations for sample collection. The output_files contains (1) and xlsx file containing percent biochemical reactions containing nitrogen identified across all 39 sample, (2) a csv file of merged FTICR data and molecular information files, (3) a csv files containing average Gibbs free energy within sampling domains and at each sampling location, (4) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 0, (5) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 24, (6) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 72, (7) a csv file with percent chemical classes identified across sampling locations at hour 0, (8) a csv file with percent chemical classes identified across sampling locations at hour 24, (9) a csv file with percent chemical classes identified across sampling locations at hour 72, and (10) a csv file containing percent nitrogen containing biochemical reactions identified across sampling locations at hours 0, 24, and 72. The python_code contains seven ipynb files which are Jupyter Notebooks used for data analysis and figures generation. The R_code contains 3 R files with R code used for data analysis and figures generation. This data package contains the processed data used in the associated manuscript. This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Current advances on Talbot–Lau x-ray imaging diagnostics for high energy density experiments (invited)

Talbot–Lau x-ray interferometry is a refraction-based diagnostic that can map electron density gradients through phase-contrast methods. The Talbot–Lau x-ray deflectometry (TXD) diagnostics have been deployed in several high energy density experiments. To improve diagnostic performance, a monochromatic TXD was implemented on the Multi-Tera Watt (MTW) laser using 8 keV multilayer mirrors (Δθ/θ = 4.5%-5.6%). Copper foil and wire targets were irradiated at 10 14 –10 15 W/cm 2 . Laser pulse length (~10 to 80 ps) and backlighter target configurations were explored in the context of Moiré fringe contrast and spatial resolution. Foil and wire targets delivered increased contrast <30%. The best spatial resolution (<6 μm) was measured for foils irradiated 80° from the surface. Further TXD diagnostic capability enhancement was achieved through the development of advanced data postprocessing tools. The Talbot Interferometry Analysis (TIA) code enabled x-ray refraction measurements from the MTW monochromatic TXD. Additionally, phase, attenuation, and dark-field maps of an ablating x-pinch load were retrieved through TXD. The images show a dense wire core of ~60 μm diameter surrounded by low-density material of ~40 μm thickness with an outer diameter ratio of ~2.3. Attenuation at 8 keV was measured at ~20% for the dense core and ~10% for the low-density material. Instrumental and experimental limitations for monochromatic TXD diagnostics are presented. Enhanced postprocessing capabilities enabled by TIA are demonstrated in the context of high-intensity laser and pulsed power experimental data analysis. Significant advances in TXD diagnostic capabilities are presented. Furthermore, these results inform future diagnostic technique upgrades that will improve the accuracy of plasma characterization through TXD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Final Report DE-FE0031785 Mohsen Ahmadian, Ph.D. Demonstration of Proof of Concept of a Multiphysics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks

Hydraulic fracturing has evolved into a multistep process with varying flow rates, carrier fluids (e.g., gel or slickwater), proppant loadings, and proppant grain sizes. As a result, primary recovery from a hydraulically fractured tight-oil reservoir is often a tiny fraction of the original oil in place, ranging between 5 and 10%. As stated in the FOA1990, “part of this problem is due to the inability of current well completion processes to effectively stimulate the entire reservoir volume in contact with the wellbore. Innovative technologies are needed that can help improve the effectiveness of reservoir completion methods, maximize stimulated reservoir volumes, and optimize recovery over the entire producing life span of a well”. We first need to enhance the current fracture diagnostic techniques to improve a well-completion design. However, detecting and delineating a subsurface hydraulic fracture is extremely difficult because the induced fracture network is only fractionally propped, and these propped fractures are generally very thin. Microseismic and tiltmeter monitoring techniques can provide information on the fracture extent but provide little or no information on the movement and final distribution of proppant or production fluids. On the other hand, electromagnetic (EM) imaging has shown the capability to monitor proppant distribution throughout the fracture area, especially in the presence of Electrically Active Proppants (EAPs). A previous EM survey of hydraulic fracturing at the Devine Fracture Pilot Site (DFPS) and subsequent EM code developments demonstrated this survey as a robust technique to remotely interrogate the extent of the EAP-filled hydraulic fracture during its propagation. The objectives of the project were threefold: (1) to capitalize on the material properties of an EAP to demonstrate remote monitoring of relative changes in pressure, pressure, and flow that are commonly encountered during production from a hydraulically fractured reservoir; (2) to evaluate EM imaging tools, to achieve Objective 1 in near real-time; and (3) to develop a multi-physics joint inversion approach to precisely predict flow patterns and physiochemical changes within an EAP-filled fracture network. This research project was built upon our previous work at the Devine Test Site managed by the Bureau of Economic Geology (BEG) at The University of Texas at Austin (UT-Austin). It also leveraged a significant investment from the Advanced Energy Consortium (AEC) to address the DOE's interest in subsurface flow, containment, and characterization by multiple signals. This three-year and three-month project succeeded in demonstrating the feasibility of a real-time dynamic fluid flow mapping technique at Technology Readiness Level 5 (TRL5) by utilizing a commercially available surface-based Controlled-Source Electromagnetic (CSEM) method (Objectives 1, 2). We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, the observed electric field in our study is influenced by bottomhole pressure, flow rate, and salinity, which is demonstrated by comparing these parameters with the electrical field potentials. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce the whole measured electric field magnitudes. Preliminary estimates showed that including Streaming Potential (SP) in our geophysical model is likely needed to reduce the simulation misfit.

02 PETROLEUM↗
DOE OSTI2024

Numerical modeling of impurity powder injection in W7-X

In this work, we present numerical simulation results of powder injection in W7-X using the EMC3-EIRENE and DIS codes. First, we model powder injection experiments performed in W7-X with the Probe Mounted Powder Injector. The simulation results qualitatively agree with visible imaging measurements. Secondly, we perform predictive simulations to guide the installation of an Impurity Powder Dropper in W7-X, allowing to choose in between several available non-vertical ports to maximize the amount of powder penetrating into the plasma, as well as the verticality of the port, to minimize sticking of the powders in the in-vessel stainless steel guiding tube. Port AEM41 is selected as the best candidate for IPD installation. The robustness of the simulation results has been verified for different plasma densities, powder materials and sizes, powder friction coefficient and changes in the plasma flow.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Emulsion droplets detection suite

The code is a set of Python libraries/scripts that leverage open source computer vision packages like YOLO and SAM2 to identify emulsion droplets in plate reader images and videos of microfluidic device flows.

Reddy, Tyler [LANL]↗
DOE OSTI2025

Modeling the Interaction of Laser-Produced Proton Beams with Matter

A major goal of this project is to significantly increase our understanding of isochoric heating of matter using laser produced proton beams, and the associated high energy density (HED) and warm dense matter (WDM) regimes generated. This will benefit research fields such as planetary science, fusion energy, plasma physics, and material science. For example, it will enhance our understanding of WDM properties of iron and silica under conditions encountered in planetary interiors and diagnostic components in fusion devices exposed to high fluxes of energetic plasma ions. The project is motivated by recent experiments that irradiated Si targets with proton beams generated by the 20 TW-laser at the SLAC MEC end-station. The HED/WDM states are probed using the 50 fs hard X-rays available in the 3rd harmonic of the LCLS. As part of this project, results from the phase contrast X-ray imaging, which shows the generation of compression waves that produces rear surface spallation, are compared with results from the 3D multi-physics multi- material code, PISALE, that combines Arbitrary Lagrangian-Eulerian (ALE) hydrodynamics with Adaptive Mesh Refinement (AMR). This comparison required modifications to several physics models in the PISALE (Pacific Island Structured-AMR with ALE) code. An important aspect of this project is the continued training of graduate students in HED physics and in conducting complex multiphysics simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Design and simulation of multilayer coatings for a multi-channel Wolter-like x-ray imager with large field of view and high resolution

X-ray diagnostics are key instruments for understanding the physics behind inertial confinement fusion experiments. We report on the multilayer design optimization for the Toroidal X-ray Imager (TXI), a hard x-rays microscope instrument designed by Commissariat à l’énergie atomique (CEA) and Laboratoire Charles Fabry (LCF) to be installed on the National Ignition Facility. TXI includes six channels designed for three different energy bands centered on 8.7, 13, and 17.5 keV. Each channel is made up of two toroidal mirrors arranged in a Wolter-like configuration. The required field of view is 800 × 400 µm2, and the resolution should be better than 5 µm. In addition, we seek to estimate the spatial distribution of the temperature, which requires no spectral overlap of the different energy bands and a good spectral homogeneity of the image produced. The development of the multilayer coatings was performed in a two-step method. First, the coatings were optimized to obtain proper energy bands. Then, an x-ray tracing code was used to calculate the integrated optical response of each channel and adjust the response of the mirror to fulfill the requirements. To fulfill all the specifications, we propose an original design using a combination of two aperiodic coatings, one with a narrow bandwidth and the other one with a larger bandwidth.

hard x-rays↗