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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A laser powder bed fusion system for operando synchrotron x-ray imaging and correlative diagnostic experiments at the Stanford Synchrotron Radiation Lightsource

Laser powder bed fusion (LPBF) is a highly dynamic multi-physics process used for the additive manufacturing (AM) of metal components. Improving process understanding and validating predictive computational models require high-fidelity diagnostics capable of capturing data in challenging environments. Synchrotron x-ray techniques play a vital role in the validation process as they are the only in situ diagnostic capable of imaging sub-surface melt pool dynamics and microstructure evolution during LPBF-AM. In this article, a laboratory scale system designed to mimic LPBF process conditions while operating at a synchrotron facility is described. The system is implemented with process accurate atmospheric conditions, including an air knife for active vapor plume removal. Significantly, the chamber also incorporates a diagnostic sensor suite that monitors emitted optical, acoustic, and electronic signals during laser processing with coincident x-ray imaging. The addition of the sensor suite enables validation of these industrially compatible single point sensors by detecting pore formation and spatter events and directly correlating the events with changes in the detected signal. Experiments in the Ti–6Al–4V alloy performed at the Stanford Synchrotron Radiation Lightsource using the system are detailed with sufficient sampling rates to probe melt pool dynamics. X-ray imaging captures melt pool dynamics at frame rates of 20 kHz with a 2 µm pixel resolution, and the coincident diagnostic sensor data are recorded at 470 kHz. Furthermore, this work shows that the current system enables the in situ detection of defects during the LPBF process and permits direct correlation of diagnostic signatures at the exact time of defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Developing time-resolved x-ray diffraction diagnostics at the National Ignition Facility (invited)

As part of a program to measure phase transition timescales in materials under dynamic compression, we have designed new x-ray imaging diagnostics to record multiple x-ray diffraction measurements during a single laser-driven experiment. Our design places several ns-gated hybrid CMOS (hCMOS) sensors within a few cm of a laser-driven target. The sensors must be protected from an extremely harsh environment, including debris, electromagnetic pulses, and unconverted laser light. Another key challenge is reducing the x-ray background relative to the faint diffraction signal. Building on the success of our predecessor (Target Diffraction In Situ), we implemented a staged approach to platform development. First, we built a demonstration diagnostic (Gated Diffraction Development Diagnostic) with two hCMOS sensors to confirm we could adequately protect them from the harsh environment and also acquire acceptable diffraction data. This allowed the team to quickly assess the risks and address the most significant challenges. Here, we also collected scientifically useful data during development. Leveraging what we learned, we recently developed a much more ambitious instrument (Flexible Imaging Diffraction Diagnostic for Laser Experiments) that can field up to eight hCMOS sensors in a flexible geometry and participate in back-to-back shots at the National Ignition Facility (NIF). The design also allows for future iterations, such as faster hCMOS sensors and an embedded x-ray streak camera. The enhanced capabilities of the new instrument required a much more complex design, and the unexpected issues encountered on the first few shots at NIF remind us that complexity has consequences. Our progress in addressing these challenges is described herein, as is our current focus on improving data quality by reducing x-ray background and quantifying the uncertainties of our diffraction measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting

Deep learning predictive models have the potential to simplify and automate medical imaging diagnostics by lowering the skill threshold for image interpretation. However, this requires predictive models that are generalized to handle subject variability as seen clinically. Here, we highlight methods to improve test accuracy of an image classifier model for shrapnel identification using tissue phantom image sets. Using a previously developed image classifier neural network—termed ShrapML—blind test accuracy was less than 70% and was variable depending on the training/test data setup, as determined by a leave one subject out (LOSO) holdout methodology. Introduction of affine transformations for image augmentation or MixUp methodologies to generate additional training sets improved model performance and overall accuracy improved to 75%. Further improvements were made by aggregating predictions across five LOSO holdouts. This was done by bagging confidences or predictions from all LOSOs or the top-3 LOSO confidence models for each image prediction. Top-3 LOSO confidence bagging performed best, with test accuracy improved to greater than 85% accuracy for two different blind tissue phantoms. This was confirmed by gradient-weighted class activation mapping to highlight that the image classifier was tracking shrapnel in the image sets. Overall, data augmentation and ensemble prediction approaches were suitable for creating more generalized predictive models for ultrasound image analysis, a critical step for real-time diagnostic deployment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Spatiotemporal structure of edge harmonic oscillation and its role in ELM-free QH-mode at KSTAR

In Quiescent H-mode (QH-mode), edge-localized modes (ELMs) are naturally replaced by a low-n edge harmonic oscillation (EHO), yet the self-regulating transport mechanism driven by the EHO remains insufficiently understood. Using high-spatiotemporal-resolution imaging diagnostics on KSTAR—electron cyclotron emission imaging and broadband electron cyclotron emission—we resolve the eigenmode structure of the EHO and elucidate its regulatory role in edge transport. The EHO is localized within the pedestal near the maximum pressure gradient, propagates in the ion-diamagnetic direction, and its radial envelope expands with increasing shear, suggesting that rotational shear is closely associated with the structural evolution of the EHO. Information-theoretic Transfer Entropy analysis identifies a distinct ‘dual-stabilization’ regulatory interaction pattern: the EHO is associated with enhanced outward energy transport to limit the pressure gradient, while the background shear flow is associated with preferential regulatory influence on the EHO saturation amplitude and energy flux. These results demonstrate that the QH-mode pedestal is sustained by a shear-associated regulation mechanism, where the coupling between rotational shear and mode structure appears closely linked to the sustained ELM-free state.

ECEI↗
DOE OSTI2021

3D optical diagnostics for explosively driven deformation and fragmentation

High-speed, optical imaging diagnostics are presented for three-dimensional (3D) quantification of explosively driven metal fragmentation. At early times after detonation, Digital Image Correlation (DIC) provides non-contact measures of 3D case velocities, strains, and strain rates, while a proposed stereo imaging configuration quantifies in-flight fragment masses and velocities at later times. Experiments are performed using commercially obtained RP-80 detonators from Teledyne RISI, which are shown to create a reproducible fragment field at the benchtop scale. DIC measurements are compared with 3D simulations, which have been ‘leveled’ to match the spatial resolution of DIC. Overall, results demonstrate improved ability to identify predicted quantities-of-interest that fall outside of measurement uncertainty and shot-to-shot variability. Similarly, video measures of fragment trajectories and masses allow rapid experimental repetition and provide correlated fragment size-velocity measurements. Measured and simulated fragment mass distributions are shown to agree within confidence bounds, while some statistically meaningful differences are observed between the measured and predicted conditionally averaged fragment velocities. Together these techniques demonstrate new opportunities to improve future model validation.

42 ENGINEERING↗
DOE OSTI2022

Experimental validation of universal plasma blob formation mechanism

Anomalous plasma transport in the boundary region of a tokamak plasma is commonly associated with the formation and evolution of coherent density structures known as blobs. Recently, a theory for a universal mechanism of plasma blob formation has been put forward. It is based on a breaking process of a radially elongated streamer due to poloidal and radial velocity shears. The theory is well supported by two-dimensional and three-dimensional numerical simulation results but lacks experimental validation. Here, we report the first ever experimental validation of this universal criterion by testing it against NSTX data on blobs obtained using the gas-puff imaging diagnostic. It is found that the criterion is widely satisfied in most L-mode discharges and may explain the significantly larger number of blob events. We also validate the theoretical criterion against ADITYA Langmuir probe data taken in the scrape-off layer region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Predictive Modeling of NOx Emissions from Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends Using Flame Imaging and Machine Learning

This research paper explores the use of machine learning to relate images of flame structure and luminosity to measured NOx emissions. Images of reactions produced by 16 aero-engine derived injectors for a ground-based turbine operated on a range of fuel compositions, air pressure drops, preheat temperatures and adiabatic flame temperatures were captured and postprocessed. The experimental investigations were conducted under atmospheric conditions, capturing CO, NO and NOx emissions data and OH* chemiluminescence images from 27 test conditions. The injector geometry and test conditions were based on a statistically designed test plan. These results were first analyzed using the traditional analysis approach of analysis of variance (ANOVA). The statistically based test plan yielded 432 data points, leading to a correlation for NOx emissions as a function of injector geometry, test conditions and imaging responses, with 70.2% accuracy. As an alternative approach to predicting emissions using imaging diagnostics as well as injector geometry and test conditions, a random forest machine learning algorithm was also applied to the data and was able to achieve an accuracy of 82.6%. This study offers insights into the factors influencing emissions in ground-based turbines while emphasizing the potential of machine learning algorithms in constructing predictive models for complex systems.

08 HYDROGEN↗
DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗
DOE OSTI2023

Image Characterization of Reactions Generated by an Aeroengine Micromixing Injector for Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blend

An aeroengine micromixing injector, originally designed for lean direct injection of jet fuel, was adapted to work with hydrogen, natural gas, and any blend in between. The ultimate goal of the design was to achieve low NOx emissions when operated on pure hydrogen; to better characterize its performance, flame imaging diagnostics was implemented. Three types of cameras mounted parallel to the injector base and pointing towards the quartz combustor cylinder with the same angle were operated simultaneously: Nikon D90, Dynacolor FB-N9-U, and Phantom v7.1, to capture the visible spectrum, OH* chemiluminescence, and dynamic behavior of the flames, respectively. The current work also includes the overlapping of visible spectrum and OH* chemiluminescence, as an effort to qualitatively define the heat release over the flame area, i.e., UV over visible domain. Additionally, a z-type schlieren configuration was employed to reinforce the presence of some small-scale details occurring near the injector outlet ports. Using the airbox pressure drop, preheat temperature, fuel composition and flame temperature as the factors of study, a Box Behnken model was designed yielding into a 16-points matrix for the operability region, at atmospheric pressure. The main responses were extracted from the OH* images, because of its correlation with the flame heat release, these being the flame area and its average brightness, the heat release area and its center of gravity and leading edge. To assess the importance of the main factors and their interactions, an analysis of variance (ANOVA) was performed for each response, considering as significant each contributor with a p-value below 0.05. For these five responses it was found that all four main factors need to be included into the model (most of them because its own significance, others to ensure the model hierarchy), as well as some common interactions as the preheat and flame temperatures or pressure drop and fuel composition, and quadratic terms from fuel composition or flame temperature. Three of the five models presented R2 and coefficient of variance (C.V.) indicators around 0.97 and 5%, respectively; the leading edge ANOVA yielded into R2=0.78 and C.V.=18.88%; and the heat release area showed R2=0.91 and C.V.=24.13%. Lastly, the confinement ratio effect of the combustor over the flame structure was quantified, for three different conditions: the original 80 mm inner diameter and 200 mm length cylinder was compared against a shorter 150 mm tube (same inner diameter) and a narrower 47 mm inner diameter one (same 200 mm length). The length had a smaller effect than the inner diameter, even though both factors were not strong enough to make a significant deviation on most of the flame parameters: the difference was within the repeatability margin of error for the brightness, flame area, and center of gravity and leading edge of the heat release area.

Imaging diagnostics, flame characterization, OH* c↗
DOE OSTI2021

A time-resolved, in-chamber x-ray pinhole imager for Z

We have commissioned a new time-resolved, x-ray imaging diagnostic for the Z facility. The primary intended application is for diagnosing the stagnation behavior of Magnetized Liner Inertial Fusion (MagLIF) and similar targets. We have a variety of imaging systems at Z, both time-integrated and time-resolved, that provide valuable x-ray imaging information, but no system at Z up to this time provides a combined high-resolution imaging with multi-frame time resolution; this new diagnostic, called TRICXI for Time Resolved In-Chamber X-ray Imager, is meant to provide time-resolved spatial imaging with high resolution. The multi-frame camera consists of a microchannel plate camera. A key component to achieving the design goals is to place the instrument inside the Z vacuum chamber within 2 m of the load, which necessitates a considerable amount of x-ray shielding as well as a specially designed, independent vacuum system. Here, a demonstration of the imaging capability for a series of MagLIF shots is presented. Predictions are given for resolution and relative image irradiance to guide experimenters in choosing the desired configuration for their experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

NEREIDS

NEREIDS (NEutron REsonance Imaging Diagnostic Suite) is a research-grade toolkit for neutron resonance imaging, providing a Rust physics core, Python bindings, and NeXus/HDF5-compliant data I/O, with a path to fast, standalone GUI workflows for VENUS/MARS.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2024

High-magnification Faraday rotation imaging and analysis of X-pinch implosion dynamics

An X-pinch load driven by an intense current pulse (>100 kA in ~100 ns) can result in the formation of a small radius, runaway compressional micro-pinch. A micro-pinch is characterized by a hot (>1 keV), current-driven (>100 kA), high-density plasma column (near solid density) with a small neck diameter (1–10 µm), a short axial extent (<1 mm), and a short duration (≲1 ns). With material pressures often well into the multi-Mbar regime, a micro-pinch plasma often radiates an intense, sub-ns burst of sub-keV to multi-keV x rays. A low-density coronal plasma immediately surrounding the dense plasma neck could potentially shunt current away from the neck and thus reduce the magnetic drive pressure applied to the neck. Here, to study the current distribution in the coronal plasma, a Faraday rotation imaging diagnostic (1064 nm) capable of producing simultaneous high-magnification polarimetric and interferometric images has been developed for the MAIZE facility at the University of Michigan. Designed with a variable magnification (1–10×), this diagnostic achieves a spatial resolution of ~35 µm, which is useful for resolving the ~100-μm-scale coronal plasma immediately surrounding the dense core. This system has now been used on a reduced-output MAIZE (100–200 kA, 150 ns) to assess the radial distribution of drive current immediately surrounding the dense micro-pinch neck. The total current enclosed was found to increase as a function of radius, r, from a value of ≈ 50 ± 25 kA at r ≈ 140 µm (at the edge of the dense neck) to a maximal value of ≈150 ± 75 kA for r ≥ 225 µm. This corresponds to a peak magnetic drive pressure of ≈75 ± 50 kbar at r ≈ 225 µm. The limitations of these measurements are discussed in the paper.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

High-Magnification Faraday Rotation Imaging and Analysis of X-pinch Implosion Dynamics

An X-pinch load driven by an intense current pulse (>100 kA in ~100 ns) can result in the formation of a small radius, runaway compressional micro-pinch. A micro-pinch is characterized by a hot (>1 keV), current-driven (>100 kA), high-density plasma column (near solid density) with a small neck diameter (1–10 μm), a short axial extent (<1 mm), and a short duration (.1 ns). With material pressures often well into the multi-Mbar regime, a micro-pinch plasma often radiates an intense, sub-ns burst of sub-keV to multi-keV x-rays. A low-density coronal plasma immediately surrounding the dense plasma neck could potentially shunt current away from the neck and thus reduce the magnetic drive pressure applied to the neck. To study the current distribution in the coronal plasma throughout the implosion process, a Faraday rotation imaging diagnostic (1064 nm) capable of producing simultaneous high-magnification polarimetric and interferometric images has been developed for the 1-MA, 100-ns MAIZE facility at the University of Michigan. Designed with a variable magnification (1–10&times;), this diagnostic achieves a spatial resolution of approximately 35 μm, which is useful for resolving the ~100-μm-scale coronal plasma region immediately surrounding the dense core. Combined with the corresponding interferogram, which provides the radial density distribution in the low-density coronal plasma, the measured rotation can be used to diagnose the delivery of the driver current, and thus the magnetic drive pressure, to the micro-pinch plasma as it approaches minimal radius. Using this technique on MAIZE, we have measured

Dowhan, G. V.↗
DOE OSTI2021

Optical Imaging on Z LDRD: Design and Development of Self-Emission and Debris Imagers

We present an overview of the design and development of optical self-emission and debris imaging diagnostics for the Z Machine at Sandia National Laboratories. These diagnostics were designed and implemented to address several gaps in our understanding of visibly emitting phenomenon on Z and the post-shot debris environment. Optical emission arises from plasmas that form on the transmission line that delivers energy to Z loads and on the Z targets themselves; however, the dynamics of these plasmas are difficult to assess without imaging data. Addressing this, we developed a new optical imager called SEGOI (Self-Emission Gated Optical Imager) that leverages the eight gated optical imagers and two streak cameras of the Z Line VISAR system. SEGOI is a low cost, side-on imager with a 1 cm field of view and 30-50 µm spatial resolution, sensitive to green light (540-600 nm). This report outlines the design considerations and development of this diagnostic and presents an overview of the first diagnostic data acquired from four experimental campaigns. SEGOI was fielded on power flow experiments to image plasmas forming on and between transmission lines, on an inertial confinement fusion experiment called the Dynamic Screw Pinch to image low density plasmas forming on return current posts, on an experiment designed to measure the magneto Rayleigh-Taylor instability to image the instability bubble trajectory and self-emission structures, and finally on a Magnetized Liner Inertial Fusion (MagLIF) experiment to image the emission from the target. The second diagnostic developed, called DINGOZ (Debris ImagiNG on Z), was designed to improve our understanding of the post-shot debris environment. DINGOZ is an airtight enclosure that houses electronics and batteries to operate a high-speed (10-400 kfps) camera in the Z Machine center section. We report on the design considerations of this new diagnostic and present the first high-speed imaging data of the post-shot debris environment on Z.

42 ENGINEERING↗
DOE OSTI2024

Frontier system-on-chip (SoC) technology for microwave diagnostics (invited)

The next generation of fusion reactors, exemplified by projects such as the Demonstration Power Plant following the International Thermonuclear Experimental Reactor, faces the monumental challenge of proving the viability of generating electricity through thermonuclear fusion. This pursuit introduces heightened complexities in diagnostic methodologies, particularly in microwave-based diagnostics. The increased neutron fluence necessitates significant reductions in vessel penetrations and the elimination of internal diagnostics, posing substantial challenges. SoC technology offers a promising solution by enabling the miniaturization, modularization, integration, and enhancing the reliability of microwave systems. After seven years of research, our team successfully pioneered the V- and W-band system-on-chip approach, leading to the development of active transmitters and passive receiver modules applied in practical settings, notably within the DIII-D tokamak project. Arrays of these modules have supported microwave imaging diagnostics. New physics measurement results from the Electron Cyclotron Emission Imaging system on DIII-D provide compelling evidence of improved diagnostics following the adoption of SoC technology. Furthermore, we achieved a breakthrough in developing an F-band SoC, advancing higher frequency capabilities for fusion devices. These achievements represent a significant leap forward in fusion diagnostic technology, marking substantial progress toward establishing reliable and efficient plasma diagnostics for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A digital holography ex situ measurement characterization of plasma-exposed surface erosion from an electrothermal arc source

Digital holography has been proposed to fulfill a need for an imaging diagnostic capable of in situ monitoring of surface erosion caused by plasma–material interaction in nuclear fusion devices. A digital holography diagnostic for 3D surface erosion measurement has been developed at Oak Ridge National Laboratory with the goal of deployment on a plasma device. A proof-of-concept in situ demonstration is planned which would involve measurement of plasma erosion on targets exposed to an electrothermal arc source. This work presents the results of an ex situ characterization of the capability and limitations of holographic imaging of targets exposed to the arc source. Targets were designed to provide a fiducial for comparison of deformed and unaffected areas. The results indicated that the average net erosion was ~150 nm/plasma exposure, which is expected to be within the diagnostic’s measurement capacity. Surface roughness averages determined by holographic image analysis showed good agreement with measurements taken with a profilometer. Finally, the limit of the holography diagnostic’s x–y spatial resolution was characterized by comparison with scanning electron microscope imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Converting existing optical detectors into fast x-ray detectors

Here, the very short burn time and small size of burning plasmas created at advanced laser-fusion facilities will require high-spatial-resolution imaging diagnostics with fast time resolution. These instruments will need to function in an environment of extremely large neutron fluxes that will cause conventional diagnostics to fail because of radiation damage and induced background levels. One solution to this challenge is to perform an ultrafast conversion of the x-ray signals into the optical regime before the neutrons are able to reach the detector and then to relay image the signal out of the chamber and into a shielded bunker, protected from the effects of these neutrons. With this goal in mind, the OMEGA laser was used to demonstrate high-temporal-resolution x-ray imaging by using an x-ray snout to image an imploding backlighter capsule onto a semiconductor. The semiconductor was simultaneously probed with the existing velocity interferometry system for any surface reflector (VISAR) diagnostic, which uses an optical streak camera and provided a one-dimensional image of the phase in the semiconductor as a function of time. The phase induced in the semiconductor was linearly proportional to the x-ray emission from the backlighter capsule. This approach would then allow a sacrificial semiconductor to be attached at the end of an optical train with the VISAR and optical streak camera placed in a shielded bunker to operate in a high neutron environment and obtain time-dependent one-dimensional x-ray images or time-dependent x-ray spectra from a burning plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Intracardiac Electrical Imaging using the 12-lead ECG: A Machine Learning Approach using Synthetic Data

Current state-of-the-art techniques for non-invasive imaging of cardiac electrical phenomena require voltage recordings from dozens of different torso locations and anatomical models built from expensive medical diagnostic imaging procedures. Here this study aimed to assess if recent machine learning advances could alternatively reconstruct electroanatomical maps at clinically relevant resolutions using only the standard 12-lead electrocardiogram (ECG) as input. To that end, a computational study was conducted to generate a dataset of over 16000 detailed cardiac simulations, which was then used to train neural network (NN) architectures designed to exploit both spatial and temporal correlations in the ECG signal. Analysis over a validation set showed average errors in activation map reconstruction below 1.7 msec over 75 intracardiac locations. Furthermore, phenotypical patterns of activation and the morphology of the activation potential were correctly reconstructed. The approach offers opportunities to stratify patients non-invasively, both retrospectively and prospectively, using metrics otherwise only available through invasive clinical procedures.

59 BASIC BIOLOGICAL SCIENCES↗