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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited]

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Rao, Ashwin P. (ORCID:0000000319312568)↗
DOE OSTI2016

First Steps Toward Incorporating Image Based Diagnostics Into Particle Accelerator Control Systems Using Convolutional Neural Networks

At present, a variety of image-based diagnostics are used in particle accelerator systems. Often times, these are viewed by a human operator who then makes appropriate adjustments to the machine. Given recent advances in using convolutional neural networks (CNNs) for image processing, it should be possible to use image diagnostics directly in control routines (NN-based or otherwise). This is especially appealing for non-intercepting diagnostics that could run continuously during beam operation. Here, we show results of a first step toward implementing such a controller: our trained CNN can predict multiple simulated downstream beam parameters at the Fermilab Accelerator Science and Technology (FAST) facility's low energy beamline using simulated virtual cathode laser images, gun phases, and solenoid strengths.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

An Integrated High-Speed Microstructural Characterization Method Using Simultaneous XRD, Stereo-DIC, and PCI

High-speed characterization of the deformation mechanisms in polycrystalline metals requires the quantification of full strain fields and local microstructural evolutions simultaneously. In this paper, we present a novel experimental method to integrate phase-contrast imaging (PCI), stereographic digital image correlation (stereo-DIC), and full-ring X-ray diffraction (XRD) to allow for the simultaneous characterization of polycrystalline metals at 1MHz or higher. A Kolsky bar was integrated into the synchrotron X-ray source in Sector 32 ID-B at the Advance Photon Source (APS) at Argonne National Laboratory. When the sample is dynamically loaded, the diagnostic methods of full-ring XRD, PCI, and stereo-DIC are properly synchronized to record the deformation behavior at both continuum and microstructural scales as a function of the loading history. An advanced high-strength steel (AHSS) is used as a model material to demonstrate the capabilities of this new experimental method.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cost Benefit Analyses through Integrated Online Monitoring and Diagnostics (Final Report)

The objective of this research is to improve the economic competitiveness of advanced reactors through the optimization of cost and plant performance, which can be achieved by coupling intelligent online monitoring with asset management decision-making. As advanced reactors are early in the development life-cycle, online monitoring systems and associated sensor networks can be incorporated directly into the design without constraints related to retrofitting and system upgrades

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Physics of Solar Prominences: I-Spectral Diagnostics and Non-LTE Modelling

This review paper outlines background information and covers recent advances made via the analysis of spectra and images of prominence plasma and the increased sophistication of non-LTE (i.e. when there is a departure from Local Thermodynamic Equilibrium) radiative transfer models. We first describe the spectral inversion techniques that have been used to infer the plasma parameters important for the general properties of the prominence plasma in both its cool core and the hotter prominence-corona transition region. We also review studies devoted to the observation of bulk motions of the prominence plasma and to the determination of prominence mass. However, a simple inversion of spectroscopic data usually fails when the lines become optically thick at certain wavelengths. Therefore, complex

Labrosse, N.↗
DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2012

Broadband Liner Optimization for the Source Diagnostic Test Fan

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more appealing. This paper describes a broadband acoustic liner optimization study for the scale model Source Diagnostic Test fan. Specifically, in-duct attenuation predictions with a statistical fan source model are used to obtain optimum impedance spectra over a number of flow conditions for three liner locations in the bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Typical tonal liner designs targeting single frequencies at one operating condition are first produced to provide baseline performance information. These are followed by multiple broadband design approaches culminating in a broadband liner targeting the full range of frequencies and operating conditions. The broadband liner is found to satisfy the optimum impedance objectives much better than the tonal liner designs. In addition, the broadband liner is found to provide better attenuation than the tonal designs over the full range of frequencies and operating conditions considered. Thus, the current study successfully establishes a process for the initial design and evaluation of novel broadband liner concepts for complex engine configurations.

Nark, Douglas M.↗
DOE OSTI2023

Developing a Novel Neutron Time-of-Flight Diagnostic Platform for Z: Ultrafast Pixel Array Camera System

This report describes a Late-Start LDRD project on a compact neutron time-of-flight (nTOF) diagnostic, based on the Ultra-Fast Pixel Array Camera (UPAC) platform. By leveraging advancements in microelectronics, the UPAC nTOF is designed to address existing challenges of current nTOFs at the Z-machine that rely on large scintillators and photomultiplier tubes using bulky, discrete digitizing units hindering scalability with signal routing presenting an additional challenge. The report describes the UPAC diagnostic platform, outlines the calibration of the diagnostic and the latest results of fielding the UPAC as a ride-a-long diagnostic on the Magnetized liner inertial fusion (MagLIF) campaigns at the Z-machine supported by the Late-Start LDRD, and finally discusses conclusions and proposed future work.

42 ENGINEERING↗
NASA NTRS2005

A Concept for the Inclusion of Analytical and Computational Capability in Existing Systems for Measurement of Neutron Flux

For approximately two decades, efforts have been sponsored by NASA's Marshall Space Flight Center to make possible high-speed, automated classification and quantification of constituent materials in various harsh environments. MSFC, along with the Air Force/Arnold Engineering Development Center, has led the work, developing and implementing systems that employ principles of emission and absorption spectroscopy to monitor molecular and atomic particulates in gas plasma of rocket engine flow fields. One such system identifies species and quantifies mass loss rates in H2/O2 rocket plumes. Other gases have been examined and the physics of their detection under numerous conditions were made a part of the knowledge base for the MSFC/USAF team. Additionally, efforts are being advanced to hardware encode components of the data analysis tools in order to address real-time operational requirements for health monitoring and management. NASA has a significant investment in these systems, warranting a spiral approach that meshes current tools and experience with technological advancements. This paper addresses current systems - the Optical Plume Anomaly Detector (OPAD) and the Engine Diagnostic Filtering System (EDIFIS) - and discusses what is considered a natural progression: a concept for migrating them towards detection of high energy particles, including neutrons and gamma rays. The proposal outlines system development to date, basic concepts for future advancements, and recommendations for accomplishing them.

Patrick, Clinton↗
DOE OSTI2017

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

Introduction The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015. Methods We used standard searches to find publications using ADNI data. Results (1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β‐amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white‐matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion‐like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by “classic” AD pathology but also by normal biomarkers, accelerated decline, and suspected non‐Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers. Discussion Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

Weiner, Michael W.↗
DOE OSTI2020

A novel method to measure ion density in ICF experiments using x-ray spectroscopy of cylindrical tracers

The indirect drive approach to inertial confinement fusion has undergone important advances in the past few years. Improvements in temperature and density diagnostic methods are leading to more accurate measurements of the plasma conditions inside the Hohlraum and therefore to more efficient experimental designs. The implementation of dot spectroscopy has proven to be a versatile approach to extracting space- and time-dependent electron temperatures. In this method, a microdot of a mid-Z material is placed inside the Hohlraum and its K-shell emission spectrum is used to determine the plasma temperature. However, radiation transport of optically thick lines acting within the cylindrical dot geometry influences the outgoing spectral distribution in a manner that depends on the viewing angle. This angular dependence has recently been studied in the high energy density regime at the OMEGA laser facility, which allowed us to design and benchmark appropriate radiative transfer models that can replicate these geometric effects. By combining these models with the measurements from the dot spectroscopy experiments at the National Ignition Facility, we demonstrate here a novel technique that exploits the transport effects to obtain time-resolved measurements of the ion density of the tracer dots, without the need for additional diagnostics. Furthermore, we find excellent agreement between experiment and simulation, opening the possibility of using these geometric effects as a density diagnostic in future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Terahertz near-field imaging of sidewall-induced losses in superconducting qubits

Correlating superconducting qubit performance with advanced materials analysis is a key strategy for improving coherence. Existing diagnostics for key properties, such as dielectric loss, structural discontinuity, and interface heterogeneity, often rely on destructive electron microscopy or low-throughput millikelvin measurements. Here, in this study, we demonstrate noninvasive terahertz (THz) nano-imaging/spectroscopy of encapsulated niobium transmon qubits as a high-throughput proxy for performance evaluation. We identify large variations in sidewall near-field signals, implicating sidewall loss and discontinuity as major coherence limiters, and also use THz hyperspectral line scans to probe dielectric responses and field participation at Al junction interfaces.

Kim, Richard H. J. [Ames Laboratory (AMES), Ames, ↗
DOE OSTI2017

OPERATIONAL EXPERIENCE WITH FAST FIBER-OPTIC BEAM LOSS MONITORS FOR THE ADVANCED PHOTON SOURCE STORAGE RING SUPERCONDUCTING UNDULATORS

Fast fiber-optic (FFO) beam loss monitors (BLMs) installed with the first two superconducting undulators (SCUs) in the Advanced Photon Source storage ring have proven to be a useful diagnostic for measuring deposited charge (energy) during rapid beam loss events. The first set of FFOBLMs were installed outside the cryostat of the short SCU, a 0.33-m long device, above and below the beam centerline. The second set are mounted with the first 1.1-mlong SCU within the cryostat, on the outboard and inboard sides of the vacuum chamber. The next 1.1-m-long SCU is scheduled to replace the short SCU later in 2016 and will be fitted with FFOBLMs in a manner similar to original 1.1-m device. The FFOBLMs were employed to set timing and voltage for the abort kicker (AK) system. The AK helps to prevent quenching of the SCUs during beam dumps [1] by directing the beam away from the SC magnet windings. The AK is triggered by the Machine Protection System (MPS). In cases when the AK fails to prevent quenching, the FFOBLMs show that losses often begin before detection by the MPS.

Dooling, J.↗
DOE OSTI2018

National Spherical Torus Experiment Upgrade Collaborative Research on Configuration Optimization of Advanced Operating Scenarios and Control Including Macroscopy Stability EOG for Period 3/1/14 through 2/28/18

General Atomics has collaborated with PPPL since 1999 in support of NSTX and NSXT-U by leveraging DIII-D program expertise. John Ferron was the principal investigator (PI) for the first nine years (to 2008) and Rob La Haye since then. The research effort evolved over a number of three-year grants and originally included both the core (control, stability, resonant error fields) and the boundary (ELMs, divertor, error fields). In 2014 the current and last grant extension was stretched to four years and split into a core grant (advanced scenarios and control, macroscopic plasma stability and extending 3D magnetics diagnostics) and a boundary grant. Todd Evans is the PI for the new boundary grant which while also for four years expires later than the core grant; a separate end of grant (EOG) report for that is due in July 2018.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

147 Sm Neutron Capture Cross Section and Resonances

Measurement of ( n,γ ) cross sections measurements are of high importance to many fields such as radiochemical diagnostics, technical nuclear forensics, nuclear physics and astrophysics, nuclear criticality safety, advanced reactors, and isotope production. For these applications an accurate characterization of the resonances in the resolved resonance region is important. In the energy range of the resonance region neutron capture, and scattering are possible so the total resonance width Γ is the sum of the gamma and neutron widths Γ = Γ γ +Γ n .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1999

Particle-Image Velocimetry in Microgravity Laminar Jet Diffusion Flames

This paper discusses planned velocity measurements in microgravity laminar jet diffusion flames. These measurements will be conducted using Particle-Image Velocimetry (PIV) in the NASA Glenn 2.2-second drop tower. The observations are of fundamental interest and may ultimately lead to improved efficiency and decreased emissions from practical combustors. The velocity measurements will support the evaluation of analytical and numerical combustion models. There is strong motivation for the proposed microgravity flame configuration. Laminar jet flames are fundamental to combustion and their study has contributed to myriad advances in combustion science, including the development of theoretical, computational and diagnostic combustion tools. Nonbuoyant laminar jet flames are pertinent to the turbulent flames of more practical interest via the laminar flamelet concept. The influence of gravity on these flames is deleterious: it complicates theoretical and numerical modeling, introduces hydrodynamic instabilities, decreases length scales and spatial resolution, and limits the variability of residence time. Whereas many normal-gravity laminar jet diffusion flames have been thoroughly examined (including measurements of velocities, temperatures, compositions, sooting behavior and emissive and absorptive properties), measurements in microgravity gas-jet flames have been less complete and, notably, have included only cursory velocity measurements. It is envisioned that our velocity measurements will fill an important gap in the understanding of nonbuoyant laminar jet flames.

Sunderland, P. B.↗
NASA NTRS2002

Flight Test of Propulsion Monitoring and Diagnostic System

The objective of this program was to perform flight tests of the propulsion monitoring and diagnostic system (PMDS) technology concept developed by Honeywell under the NASA Advanced General Aviation Transport Experiment (AGATE) program. The PMDS concept is intended to independently monitor the performance of the engine, providing continuous status to the pilot along with warnings if necessary as well as making the data available to ground maintenance personnel via a special interface. These flight tests were intended to demonstrate the ability of the PMDS concept to detect a class of selected sensor hardware failures, and the ability to successfully model the engine for the purpose of engine diagnosis.

Gabel, Steve↗
NASA NTRS2002

Characterization of Liquid Fuel Evaporation of a Lifted Methanol Spray Flame in a Vitiated Coflow Burner

An experimental investigation of lifted spray flames in a coflow of hot, vitiated gases is presented. The vitiated coflow burner is a spray flame that issues into a coaxial flow of hot combustion products from a lean, premixed H2/Air flame. The spray flame in a vitiated coflow emulates the combustion that occurs in many advanced combustors without the detailed fluid mechanics. Two commercially available laser diagnostic systems are used to characterize the spray flame and to demonstrate the vitiated coflow burner's amenability to optical investigation. The Ensemble Particle Concentration and Size (EPCS) system is used to measure the path-average droplet size distribution and liquid volume fraction at several axial locations while an extractive probe instrument named the Real-time Fuel-air Analyzer (RFA) is used to measure the air to fuel ratio downstream of the spray nozzle with high temporal and spatial resolution. The effect of coflow conditions (stoichiometry) and dilution of the fuel with water was studied with the EPCS optical system. As expected, results show that water retards the evaporation and combustion of fuels. Measurements obtained by the RFA extractive probe show that while the Delavan manufactured nozzle does distribute the fuel over the manufacturer specified spray angle, it unfortunately does not distribute the fuel uniformly, providing conditions that may result in the production of unwanted NOx. Despite some limitations due to the inherent nature of the experimental techniques, the two diagnostics can be readily applied to spray flames in the vitiated coflow environment.

Cabra, Ricardo↗