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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Combined TREAT-LOC & SATS Integral LOCA Experiment Plan

The Transient Reactor Test Facility (TREAT) loss-of-coolant (LOC) and highburnup (HBu) experiment series, along with the Severe Accident Test Station (SATS) HBu experiment series, are integral LOC accident (LOCA) experiments planned under the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program, which aims to support burnup extension needs by addressing identified R&D priorities in order to achieve an improved understanding of fuel fragmentation, relocation, and dispersal (FFRD) of HBu fuel during LOCA events. Priorities have been identified by the Electric Power Research Institute (EPRI)’s Collaborative Research on Advanced Fuel Technologies (CRAFT) Fuel Performance and Testing Technical Experts Group (FPTTEG). The data produced under this plan will be used to further validate and confirm existing models and inform future R&D and model development. The experimental program was specifically developed to address data gaps and opportunities identified via detailed review of the existing public knowledge base on LOCA FFRD, as well as reviewing specific experimental development activities regarding prototypic LOCA conditions for light-water reactor (LWR) systems. The test program relies on a unique combination of in- and out-of-pile experimental approaches to provide a clear tieback to the existing integral and semi-integral LOCA experiment database, using state-of-the-art facilities. More importantly, the program will systematically investigate the impacts of prototypic HBu fuel/cladding thermomechanical behaviors under postulated LWR LOCA conditions not yet fully investigated. These conditions correspond with prototypic decay-energy heatup (DEH) and stored-energy heatup (SEH) conditions. First, TREAT’s unique capability will enable the first evaluation of the impact of SEH conditions on HBu fuels. The test program will emphasize the development of an improved mechanistic understanding of key phenomena through independent experimental systems, development of a database to support fuel performance modeling tools, world-leading advanced materials characterization, and the most advanced approach to in situ diagnostics ever deployed to evaluate FFRD. The results will represent a significant leap forward in evaluating prototypic conditions and novel data to support modeling development and validation, as well as to inform the technical basis for LOCA-induced FFRD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

First measurements of D{sub α} spectrum produced by anisotropic fast ions in the gas dynamic trap

Angled injection of eight deuterium beams in gas dynamic trap (GDT) plasmas builds up the population of fast ions with the distribution function, which conserves a high degree of initial anisotropy in space, energy, and pitch angle. Unlike the Maxwellian distribution case, the fast ion plasma component in GDT cannot be exhaustively characterized by the temperature and density. The instrumentation complex to study of fast ions is comprised of motional Stark effect diagnostic, analyzers of charge exchange atoms, and others. The set of numerical codes using for equilibrium modeling is also an important tool of analysis. In the recent campaign of summer 2014, we recorded first signals from the new fast ion D-alpha diagnostic on GDT. This paper presents the diagnostic description and results of pilot measurements. The diagnostic has four lines of sight, distributed across the radius of an axially symmetric plasma column in GDT. In the present setup, a line-integrated optical signal is measured in each channel. In the transverse direction, the spatial resolution is 18 mm. Collected light comes to the grating spectrometer with the low-noise detector based on a charge-coupled device matrix. In the regime of four spectra stacked vertically on the sensor, the effective spectral resolution of measurements is approximately 0.015 nm. Exposure timing is provided by the fast optical ferroelectric crystal shutter, allowing frames of duration down to 70 μs. This number represents the time resolution of measurements. A large dynamic range of the camera permits for a measurement of relatively small light signals produced by fast ions on top of the bright background emission from the bulk plasma. The fast ion emission has a non-Gaussian spectrum featuring the characteristic width of approximately 4 nm, which can be separated from relatively narrow Gaussian lines of D-alpha and H-alpha coming from the plasma periphery, and diagnostic beam emission. The signal to noise ratio varies from approximately ten for the central channel to approximately five for the outermost channel. We used the special set of Monte Carlo codes to fit the measured spectra. The shape of model fit shows a good agreement with the experimental fast ion D-alpha spectrum.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Molecular Biomarker-Based Biokinetic Modeling of a PCE-Dechlorinating and Methanogenic Mixed Culture

Bioremediation of chlorinated ethenes via anaerobic reductive dechlorination relies upon the activity of specific microbial population-most notably Dehalococcoides (DHC) strains. In the lab and field Dehalococcoides grow most robustly in mixed communities which usually contain both fermenters and methanogens. Recently, researchers have been developing quantitative molecular biomarkers to aid in field site diagnostics and it is hoped that these biomarkers could aid in the modeling of anaerobic reductive dechlorination. A comprehensive biokinetic model of a community containing Dehalococcoides mccartyi (formerly D. ethenogenes) was updated to describe continuously fed reactors with specific biomass levels based on quantitative PCR (qPCR)-based population data (DNA and RNA). The model was calibrated and validated with subsets of chemical and molecular biological data from various continuous feed experiments (n = 24) with different loading rates of the electron acceptor (1.5 to 482 μeeq/L-h), types of electron acceptor (PCE, TCE, cis-DCE) and electron donor to electron acceptor ratios. The resulting model predicted the sum of dechlorination products vinyl chloride (VC) and ethene (ETH) well. However, VC alone was under-predicted and ETH was over predicted. Consequently, competitive inhibition among chlorinated ethenes was examined and then added to the model. Additionally, as 16S rRNA gene copy numbers did not provide accurate model fits in all cases, we examined whether an improved fit could be obtained if mRNA levels for key functional enzymes could be used to infer respiration rates. The resulting empirically derived mRNA “adjustment factors” were added to the model for both DHC and the main methanogen in the culture (a Methanosaeta species) to provide a more nuanced prediction of activity. Results of this study suggest that at higher feeding rates competitive inhibition is important and mRNA provides a more accurate indicator of a population’s instantaneous activity than 16S rRNA gene copies alone as biomass estimates.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

Care 3 phase 2 report, maintenance manual

CARE 3 (Computer-Aided Reliability Estimation, version three) is a computer program designed to help estimate the reliability of complex, redundant systems. Although the program can model a wide variety of redundant structures, it was developed specifically for fault-tolerant avionics systems--systems distinguished by the need for extremely reliable performance since a system failure could well result in the loss of human life. It substantially generalizes the class of redundant configurations that could be accommodated, and includes a coverage model to determine the various coverage probabilities as a function of the applicable fault recovery mechanisms (detection delay, diagnostic scheduling interval, isolation and recovery delay, etc.). CARE 3 further generalizes the class of system structures that can be modeled and greatly expands the coverage model to take into account such effects as intermittent and transient faults, latent faults, error propagation, etc.

Bryant, L. A.↗
NASA NTRS2004

Interpretive Tools for Analysis of Coronal Images

Contents include list of publications resulting from grant: Magneto-Hydrodynamic Model of the Solar Corona and Interplanetary Medium. Coronal magnetic field topology and source of fast solar wind. Geophysical Importance of Global Magnetic Field Geometry and Density Distribution in Solar Wind Modeling. Empirical Model of the Corona-Solar Wind with Multiple Current Sheets. Model of the Solar Wind and its Comparison with ULYSSES. Physical properties of a coronal hole from a coronal diagnostic spectrometer, Mauna Loa Coronagraph, and LASCO observations during the Whole Sun Month. Semi-Empirical 2-D MHD Model of the Solar corona and Solar Wind: Energy Flow in the Corona. Source Region of High and Low Speed Wind during the Spartan. Three-dimensional coronal density structure. Cone Model for Halo CME's: Application to Space Weather Forecasting.

Ofman, Leon↗
NASA NTRS2003

Dynamic and Structural Gas Turbine Engine Modeling

Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.

Turso, James A.↗
DOE OSTI2019

Evaluation of emission contributions from charge-exchange between the excited states of deuterium with He + during diagnostic of thermal helium gas beam injection and laser-induced fluorescence

Emission contributions from charge-exchange of excited deuterium ( n = 2, 3) with He + are evaluated in a1-D kinetic collisional radiative model in order to analyze their effects on the Thermal Helium Beam (THB) line-ratio diagnostic on ASDEX Upgrade and Laser Induced Fluorescence (LIF) He I density measurements in ITER. Recent charge-exchange calculations show that cross sections from excited deuterium ( n = 2, 3) with He + are over 4-orders of magnitude higher than those from the ground state ( n = 1) and occur at very low energies where they are more likely to interact with the thermal He + ions introduced by ionization of the diagnostic helium gas-puff injection. Higher densities of excited deuterium are typically present in the Scrape-Off Layer (SOL), divertor, and edge regions of tokamaks, where the LIF and THB helium diagnostics are typically used for n HeI and simultaneous determination of electron temperatures and densities and where contributions from charge-exchange emission may offset these values if not taken into account. The analysis presented in this work shows that due to the higher density of deuterium in the ground rather than in excited states and the divergent behavior of deuterium and He + density profiles along the SOL and edge regions, the deuterium-He + charge-exchange contributions to the helium puff emission are 3-orders of magnitude lower than those from electron-impact excitation. Similar plasma conditions are expected in the ITER divertor, with the exception that in the area near the strike-points and targets, the electron temperature is not high enough to excite from the ground state but deuterium, electron, and He + densities are high enough to dominate the emission from charge-exchange and recombination. These findings strengthen the assumption made in the present line-ratio model that helium emission from gas-puff into plasma is mainly dominated by electron-excitation. It is also shown that, in general, charge-exchange helium emission is 2-orders of magnitude higher than the emission due to recombination. Finally, these findings suggest the importance of including charge-exchange processes as a source of neutrals in ionic fractional abundance calculations in plasmas and helium-ash transport modeling in fusion reactors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1987

Vector constraints on western U.S. deformation from space geodesy, neotectonics, and plate motions

The rate-of-slip vector on the San Andreas fault in central California estimated from geodetic and Holocene geological data is inconsistent with the prediction of rigid plate models such as RM2. This well-known 'San Andreas discrepancy' is diagnostic of plate deformation distributed both east of the fault in the Basin and Range and west of the fault along the California continental margin. Constraints on the integrated deformation rates across these two regions consistent with: (1) the kinematical boundary conditions imposed by the rigid plate model; (2) neotectonic and paleoseismic estimates of deformation rates; (3) ground-based geodetic measurements; and (4) rates of change observed by very long baseline interferometry along seven baselines to western U.S. sites are constructed. The space-geodetic data on Basin and Range extension taken over a 4-year interval are compatible with geological observations averaged over the Holocene; the best estimate of its integrated deformation rate, provided by the joint inversion of both data types, is 9.7 + or - 2.1 mm/yr, N 56 deg W + or - 10 deg, too small and in the wrong direction to account entirely for the San Andreas discrepancy. The integral of this deformation, estimated by subtracting the Basin and Range contribution from the discrepancy vector, requires significant right-lateral shear parallel to the San Andreas (13 + or - 5 mm/yr) and some compression perpendicular to it (9 + or - 3 mm/yr).

Minster, J. Bernard↗
DOE OSTI2025

Elemental and Isotopic Yields from T Coronae Borealis: Predictions and Uncertainties

T Coronae Borealis (T CrB) is a symbiotic recurrent nova system expected to undergo its next outburst within the next 2 yr. Recent hydrodynamic simulations have predicted the nucleosynthetic yields for both carbon–oxygen (CO) and oxygen–neon (ONe) white-dwarf models, but without accounting for thermonuclear reaction rate uncertainties. We perform detailed Monte Carlo postprocessing nucleosynthesis calculations based on updated thermonuclear reaction rates and uncertainties from the 2025 evaluation. We quantify the resulting abundance uncertainties and identify the key nuclear reactions that dominate them. Our results show that both the CO and ONe nova models robustly produce characteristic CNO isotopes. More pronounced abundance differences emerge for elements with A ≥ 20. Sulfur is the most robust observational discriminator between the CO and ONe nova models, with a model-to-model difference of a factor of ≈30 and minimal sensitivity to reaction rate uncertainties. Neon, silicon, and phosphorus exhibit even larger abundance differences (factors of ≈150–250), providing strong diagnostic potential. While their predicted yields are subject to larger uncertainties, these remain smaller than the model-to-model differences, allowing these elements to serve as useful, though less precise, tracers of white-dwarf composition. Chlorine, argon, and potassium also differ between models, but the 1σ-abundance ranges for the CO and ONe models overlap, reducing their present usefulness as composition tracers. We find that only nine nuclear reactions dominate the abundance uncertainties of the most diagnostically important isotopes, and their influence is largely independent of the underlying white-dwarf composition. These results provide guidance for future experimental efforts and for interpreting ejecta compositions in the next eruption of T CrB.

Chemical Abundances↗
DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗
DOE OSTI2021

High-energy-density-physics measurements in implosions using Bayesian inference

Convergent high-energy-density (HED) experimental platforms are used to study matter under some of the most extreme conditions that can be produced on Earth, comparable to the interior of stars. There are many challenges in using these systems for fundamental measurements currently being addressed by new analysis methods, such as the combination of a reduced physics model and Bayesian inference, allowing a self-consistent inference of physical quantities with a robust error analysis. These methods in combination with simple (as compared to inertial confinement fusion implosions) implosion platforms, which can be modified to show sensitivity to different physical mechanisms of interest, are used to study the physical properties of matter under extreme conditions. This work discusses a subset of implosion targets for studying opacity effects, electron-ion equilibration, and thermal conductivity and, as an example, a system consisting of a thick-shelled, gas-filled laser-direct-drive implosion is used to show how a reduced model and Bayesian inference can help inform experimental design decisions such as diagnostic choice. It is shown that for this system that a combination of neutron and x-ray self-emission diagnostics is critical for constraining the details of the thermodynamic states in the system and that the conductivity exponent in a Spitzer like framework can be constrained to the 30% level in deuterium at gigabar conditions. Furthermore, this process can be applied to many HED systems to make underlying model assumptions explicit and facilitate experimental design and analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

FLUORINE IN THE SOLAR NEIGHBORHOOD: IS IT ALL PRODUCED IN ASYMPTOTIC GIANT BRANCH STARS?

The origin of ''cosmic'' fluorine is uncertain, but there are three proposed production sites/mechanisms for the origin: asymptotic giant branch (AGB) stars, ν nucleosynthesis in Type II supernovae, and/or the winds of Wolf-Rayet stars. The relative importance of these production sites has not been established even for the solar neighborhood, leading to uncertainties in stellar evolution models of these stars as well as uncertainties in the chemical evolution models of stellar populations. We determine the fluorine and oxygen abundances in seven bright, nearby giants with well determined stellar parameters. We use the 2.3 μm vibrational-rotational HF line and explore a pure rotational HF line at 12.2 μm. The latter has never been used before for an abundance analysis. To be able to do this, we have calculated a line list for pure rotational HF lines. We find that the abundances derived from the two diagnostics agree. Our derived abundances are well reproduced by chemical evolution models including only fluorine production in AGB stars and, therefore, we draw the conclusion that this might be the main production site of fluorine in the solar neighborhood. Furthermore, we highlight the advantages of using the 12 μm HF lines to determine the possible contribution of the ν process to the fluorine budget at low metallicities where the difference between models including and excluding this process is dramatic.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Eye-tracking of nodule detection in lung CT volumetric data

Purpose: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naïve observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll through image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. Methods: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naïve observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. Results: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naïve observers and the radiologists at the moment the signal was detected was measured at 25–30 fps. For the task chosen, the performance of the observers was not affected by the contrast or experience of the observer. However, the naïve observers exhibited a different pattern of scrolling than the radiologists, which included a tendency toward higher number of direction changes and number of slices viewed. Conclusions: The authors have determined a distribution of speeds for volumetric detection tasks. The speed at detection was higher than that subjectively estimated by the radiologists before the experiment. The speed information that was measured will be useful in the development of 3D model observers, especially anthropomorphic model observers which try to mimic human behavior.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Using Micro-Synchrophasor Data for Advanced Distribution Grid Planning and Operations Analysis

This report reviews the potential for distribution-grid phase-angle data that will be available from new micro-synchrophasors (µPMUs) to be utilized in existing distribution-grid planning and operations analysis. This data could augment the current diagnostic capabilities of grid analysis software, used in both planning and operations for applications such as fault location, and provide data for more accurate modeling of the distribution system. µPMUs are new distribution-grid sensors that will advance measurement and diagnostic capabilities and provide improved visibility of the distribution grid, enabling analysis of the grid’s increasingly complex loads that include features such as large volumes of distributed generation. Large volumes of DG leads to concerns on continued reliable operation of the grid, due to changing power flow characteristics and active generation, with its own protection and control capabilities. Using µPMU data on change in voltage phase angle between two points in conjunction with new and existing distribution-grid planning and operational tools is expected to enable model validation, state estimation, fault location, and renewable resource/load characterization. Our findings include: data measurement is outstripping the processing capabilities of planning and operational tools; not every tool can visualize a voltage phase-angle measurement to the degree of accuracy measured by advanced sensors, and the degree of accuracy in measurement required for the distribution grid is not defined; solving methods cannot handle the high volumes of data generated by modern sensors, so new models and solving methods (such as graph trace analysis) are needed; standardization of sensor-data communications platforms in planning and applications tools would allow integration of different vendors’ sensors and advanced measurement devices. In addition, data from advanced sources such as µPMUs could be used to validate models to improve/ensure accuracy, providing information on normally estimated values such as underground conductor impedance, and characterization of complex loads. Although the input of high-fidelity data to existing tools will be challenging, µPMU data on phase angle (as well as other data from advanced sensors) will be useful for basic operational decisions that are based on a trend of changing data.

25 ENERGY STORAGE↗
DOE OSTI2020

Learnings from the Marcellus Shale Energy and Environmental Lab (MSEEL) Using Fiber Optic Tools and Geomechanical Modeling

The study focuses on the MIP and Boggess pads of the MSEEL (Marcellus Shale Energy and Environmental Laboratory), a public-private partnership with a mandate to publicly release data for scientists and engineers to engage with. Multiple diagnostic tools are used to characterize the formation and monitor fracture treatment and propagation. Geomechanical modeling is used to understand the insitu stresses, microseismic to describe half-lengths and heights, and fiber optics to characterize offset well. Fracture Driven Interactions (FDI’s) and interstage communication. Recent publications covering the MSEEL MIP-3H and MIP-5H wells are reviewed and discussed. A preview of the findings from the Boggess pad (first production in November 2019) is also shared here

03 NATURAL GAS↗
NASA NTRS2017

El Nino-Induced Tropical Ocean/Land Energy Exchange in MERRA-2 and M2AMIP

Studies have shown the correlation and connection of surface temperatures across the globe, ocean and land, related to Tropical SSTs especially El Nino. This climate variability greatly influences regional weather and hydroclimate extremes (e.g. drought and flood). In this paper, we evaluate the relationship of temperatures across the tropical oceans and continents in MERRA-2, and also in a newly developed MERRA-2 AMIP ensemble simulation (M2AMIP). M2AMIP uses the same model and spatial resolution as MERRA-2, producing the same output diagnostics over 10 ensemble members. Composite El Nino temperature data are compared with observations to evaluate the land/sea contrast, variations and phase relationship. The temperature variations are related to surface heat fluxes and the atmospheric temperatures and transport, to identify the processes that lead to the lagged redistribution of heat in the tropics and beyond. Discernable cloud, radiation and data assimilation changes accompany the onset of El Nino affecting continental regions through the progression to and following the peak values. While the model represents these variations in general, regional strengths and weaknesses can be identified.

Bosilovich, Michael G.↗
NASA NTRS2008

Integrated System Health Management (ISHM) for Test Stand and J-2X Engine: Core Implementation

ISHM capability enables a system to detect anomalies, determine causes and effects, predict future anomalies, and provides an integrated awareness of the health of the system to users (operators, customers, management, etc.). NASA Stennis Space Center, NASA Ames Research Center, and Pratt & Whitney Rocketdyne have implemented a core ISHM capability that encompasses the A1 Test Stand and the J-2X Engine. The implementation incorporates all aspects of ISHM; from anomaly detection (e.g. leaks) to root-cause-analysis based on failure mode and effects analysis (FMEA), to a user interface for an integrated visualization of the health of the system (Test Stand and Engine). The implementation provides a low functional capability level (FCL) in that it is populated with few algorithms and approaches for anomaly detection, and root-cause trees from a limited FMEA effort. However, it is a demonstration of a credible ISHM capability, and it is inherently designed for continuous and systematic augmentation of the capability. The ISHM capability is grounded on an integrating software environment used to create an ISHM model of the system. The ISHM model follows an object-oriented approach: includes all elements of the system (from schematics) and provides for compartmentalized storage of information associated with each element. For instance, a sensor object contains a transducer electronic data sheet (TEDS) with information that might be used by algorithms and approaches for anomaly detection, diagnostics, etc. Similarly, a component, such as a tank, contains a Component Electronic Data Sheet (CEDS). Each element also includes a Health Electronic Data Sheet (HEDS) that contains health-related information such as anomalies and health state. Some practical aspects of the implementation include: (1) near real-time data flow from the test stand data acquisition system through the ISHM model, for near real-time detection of anomalies and diagnostics, (2) insertion of the J-2X predictive model providing predicted sensor values for comparison with measured values and use in anomaly detection and diagnostics, and (3) insertion of third-party anomaly detection algorithms into the integrated ISHM model.

Figueroa, Jorge F.↗
DOE OSTI2025

Predicted thresholds for RMP ELM suppression access in double-null configurations

Modeling of DIII-D plasmas spanning shapes from single to double-null (DN) reveals new insights into the nature of resonant magnetic perturbation (RMP) conditions necessary for edge-localized mode (ELM) suppression. The suppression of ELMs with RMPs has proven difficult in DN configurations, where no device has thus far reported any hints of suppression. Modeling using the GPEC code finds a reduced high-field side response closer to DN shaping. The resulting synthetic diagnostic measurements are consistent with what has been observed in experiments on DIII-D, validating the plasma response model in this regime. While common metrics for suppression do not illustrate a clear distinction between single-null (SN) and DN cases, the pedestal top resonant field does show a ∼20% decrease at DN shaping in modeling. Field penetration is assessed using linear tearing theory, which demonstrates a lack of sufficient pedestal top resonant flux in the DN shape, requiring at least 1.5 × greater RMP coil currents than what was used in experiment. Analysis from drift kinetic simulations further indicate up to 2 × larger critical island widths are required at the pedestal top for tearing mode growth compared to SN cases. Effective island widths inferred from 3D ideal MHD are also analyzed, where maximum widths in lab coordinates indicate a threshold of ∼18–24× the ion gyroradius for sufficient profile flattening for ELM suppression. These results suggest that ELM suppression may be possible in DN with sufficiently large RMP coil amplitude. Future prospects of achieving RMP ELM suppression in the DN configuration may involve going to lower triangularity, which is also highlighted in this work.

RMP ELM suppression↗