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At least 55 records · Page 3

Parallel Diffusion Coefficient of Energetic Charged Particles in the Inner Heliosphere from the Turbulent Magnetic Fields Measured by Parker Solar Probe

Diffusion coefficients of energetic charged particles in turbulent magnetic fields are a fundamental aspect of diffusive transport theory but remain incompletely understood. In this work, we use quasi-linear theory to evaluate the spatial variation of the parallel diffusion coefficient κ ∥ from the measured magnetic turbulence power spectra in the inner heliosphere. We consider the magnetic field and plasma velocity measurements from Parker Solar Probe made during Orbits 5–13. The parallel diffusion coefficient is calculated as a function of radial distance from 0.062 to 0.8 au, and the particle energy from 100 keV to 1 GeV. We find that κ ∥ increases exponentially with both heliocentric distance and energy of particles. The fluctuations in κ ∥ are related to the episodes of large-scale magnetic structures in the solar wind. By fitting the results, we also provide an empirical formula of κ ∥ = (5.16 ± 1.22) × 10 18 r 1.17 ± 0.08 E 0.71 ± 0.02 (cm 2 s -1 ) in the inner heliosphere, which can be used as a reference in studying the transport and acceleration of solar energetic particles as well as the modulation of cosmic rays.

79 ASTRONOMY AND ASTROPHYSICS↗

Studying Wind Loading on CSP Collectors to Improve Performance and Reliability

Electricity generation through Concentrating Solar-thermal Power (CSP) adds the advantage of thermal energy storage and heat production. CSP collector costs constitute nearly one-third of total plant costs. Managing wind loading, especially dynamic wind loading caused by the turbulent wind flow, is a significant design challenge. Traditional collector designs rely on wind tunnel experiments and numerical simulations, which do not fully capture dynamic effects. Here, we provide an overview of NREL's activities on wind loading on CSP collectors, aiming to improve their reliability and cost-efficiency. We present insights from field measurements at operational parabolic trough and power-tower CSP plants. Over two years, we measured turbulent wind fields and resulting structural loads in a parabolic trough plant, revealing wind, turbulence, and collector field interactions. Similar measurements are ongoing at the Crescent Dunes heliostat field. These campaigns show how atmospheric turbulence, wind direction, and collector orientation affect dynamic wind loading. Upwind collector structures can generate turbulent structures, causing fluctuating loads at downstream collectors, impacting fatigue lifetime and optical efficiency. Preliminary results indicate that interior collectors experience higher turning moments than those at the edges, suggesting higher drive wear. At Crescent Dunes, we use instrumented heliostats at the field's edge and interior to study the translation of turbulent wind to dynamic structural loads. The campaign is still ongoing, and we will present first findings. Another focus of our work is tying the experimental wind loading findings to optical performance of the collectors, using simulation tools. For example, we derive torsional errors of the parabolic troughs - the angular offset from the sun position along a collector row. This error is impacted by wind-induced mirror deformations. Future work will focus on continuing the measurement efforts and combining them with computational fluid dynamic simulations. By providing detailed field measurements and validated models, our efforts aim to enhance understanding of wind loading on CSP collectors, improving their structural integrity and optical performance.

CSP↗

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↗

Toward Interpreting the IBEX Ribbon with Mirror Diffusion in Interstellar Turbulent Magnetic Fields

We investigate the role of the magnetohydrodynamic (MHD) turbulence measured by Voyager in the very local interstellar medium (VLISM) in modeling the Interstellar Boundary Explorer ribbon. We demonstrate that the mirroring by compressible modes of MHD turbulence dominates over that by the mean magnetic field. Based on the new mirror diffusion mechanism identified by Lazarian & Xu for particles with large pitch angles in MHD turbulence, we find that the mirror diffusion can both confine pickup ions and preserve their initial pitch angles, and thus it accounts for the enhanced intensity of energetic neutral atoms that return to the heliosphere. The ribbon width is determined by both the range of pitch angles for effective turbulent mirroring and the field line wandering induced by Alfvénic modes. It in turn provides a constraint on the amplitude of magnetic fluctuations of fast modes. The field line wandering also affects the coherence of the ribbon structure across the sky. By extrapolating the magnetic energy spectrum measured by Voyager, we find that the injection scale of the turbulence in the VLISM must be less than ~500 au for the ribbon structure to be coherent.

79 ASTRONOMY AND ASTROPHYSICS↗

Wind Conditions for Solar Energy Facility Design Based on Field Measurements at Nevada Solar One

This study characterises near-surface wind conditions at the Nevada Solar One (NSO) concentrated solar power plant using two years of measurements from a 15-m mast located 30 m west of the solar arrays. The surrounding terrain is fairly flat within 3 km, but nearby solar photovoltaic (PV) and concentrated solar power (CSP) installations introduce strong directional wind inhomogeneity, which motivates a sector-based analysis that distinguishes undisturbed inflow from waked flow. The analysis uses data from three sonic anemometers to assess whether turbulence in the surface layer can be represented as Gaussian and whether standard surface-layer scaling remains valid below 10 m height. The roughness length and displacement height are estimated for twelve directional sectors under near-neutral wind conditions, and all three velocity components show departures from Gaussian behaviour. Spectral analysis indicates that the turbulence contains low-frequency fluctuations with amplitudes higher than those predicted by standard models such as the Kaimal model or the Simiu and Scanlan model. The study introduces a new turbulence spectral model based on the eddy-surface-layer framework to better represent near-surface wind turbulence. The analysis further quantifies the influence of the surrounding power plants on mean wind profiles, one-point spectra, and vertical coherence for all velocity components. The solar collector arrays located 30 m east of the mast significantly modify the turbulence structure, whereas PV installations situated a few hundred metres away have only a limited influence on the turbulence measured at the mast. These findings highlight the limitations of conventional turbulence models for near-surface wind over solar infrastructure and provide improved parameterisations to support the structural design. The implications for the structural response of parabolic troughs and PV modules to such turbulence remain uncertain and require further investigation.

14 SOLAR ENERGY↗

LiDAR Measurements of Wind Shear Exponents and Turbulence Intensity Offshore the Northeast United States

This paper presents wind speed shear exponents and turbulence intensity measurements collected from LiDARs measuring wind speeds from 40m to 200m above sea-level and provides comparisons to industry design guidelines. The high-altitude wind speed data are unique and represent some of the first measurements made offshore in this part of the country, which is actively being developed for offshore wind. The data is used to support the New England Aqua Ventus I Floating Offshore Wind Farm to be located 17km offshore the Northeast United States. Multiple LiDAR measurements were made using a DeepCLiDAR floating buoy and LiDARs located on a nearby island. Here, the measured wind speed shear exponents are compared against industry standard mesoscale model outputs and offshore design codes including the American Bureau of Shipping, American Petroleum Institute, and DNV-GL guides. Significant variation in the vertical wind speed profile occurs throughout the year which is not addressed in design standards. Additionally, turbulence intensity measurements made from the LiDAR, although not widely accepted in the scientific community, are presented and compared against industry guidelines.

42 ENGINEERING↗

Outlook for active plasma spectroscopy with entangled two-photon absorption

Entangled two-photon absorption (ETPA) exhibits a quantum-enhanced two-photon absorption cross-section and a linear scaling with incident power that exceeds classical two-photon absorption (TPA) at low photon flux. Here, we assess the feasibility and applications of ETPA for active plasma spectroscopy. The ETPA-absorbed power for an Ar + species in a helicon plasma scenario is calculated to be as high as 0.6 nW cm −1 along the incident beam path for nondegenerate-entangled photon pairs that are near-resonant with an intermediate level. The ETPA absorption power exceeds classical TPA and Bremsstrahlung emission, a necessary condition for a feasible fluorescence measurement. Applications of ETPA plasma spectroscopy may include trace impurity detection, ground-state excitation, and continuous-wave pumping for high-bandwidth turbulence measurements. Possible benefits of plasma measurements are less harm to optical components with lower incident flux and reduced stray light that can contaminate optical diagnostics.

active plasma spectroscopy↗

L-H transition trigger physics in ITER-similar plasmas with applied n = 3 magnetic perturbations

The L–H transition power threshold PLH is observed to increase with applied n = 3 resonant magnetic perturbations (RMP) in ITER-similar-shape plasmas with balanced neutral beam torque injection in DIII-D. The increase is most pronounced with added electron–cyclotron heating: PLH increases with decreasing edge plasma collisionality as PLH/PLH-08 ~ (ν*)−0.5, where PLH-08 is the 2008 ITPA multi-machine power threshold scaling. This result raises concerns for H-mode access at low edge collisionality in ITER, where RMP may have to be applied before the L–H transition to safely suppress the first edge-localized mode. Non-axisymmetric modifications with RMP include a simultaneous reduction of the radial electric field (Er) well depth and E × B shear. This can be attributed to increasing edge toroidal co-current rotation, and is consistent with substantially increased local long-wavelength turbulence (measured via beam emission spectroscopy). At high RMP perturbation strength the edge electric field Er reverses sign locally (becomes positive), with changes in dominant turbulence modes. Edge magnetic stochasticity provides an attractive explanation of the observed modifications, and the observed changes in toroidal rotation and Er are consistent with a simple fluid model describing radial electron current flow along stochastic fieldlines. The observed collisionality dependence of the L-mode edge electric field with applied RMP is also qualitatively consistent with this model. Reflectometry data indicate a significant reduction of the normalized L-mode radial density gradient a/Ln at high RMP field with simultaneous increase in radial particle flux and electron thermal flux from power balance analysis. We conjecture that the increase of PLH with RMP results from the combined effects of reduced E × B flow shear (increasing turbulent transport levels) and toroidal/poloidal flow modulation due to edge stochasticity. Initial experiments indicate that non-resonant n = 3 magnetic perturbations lead only to relatively small changes in Er, E × B shear and fluctuation characteristics, and have less impact on the L–H transition power threshold. This motivates further exploration of the RMP spectrum dependence of PLH for possible mitigation of the observed threshold increase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary

This data was collected between October 12 and December 15 of 2021 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). This data set includes over 29 days of grid connected turbine operation during this 65 day time frame. The priority for this measurement campaign was to collect data while the turbine was electrically connected to the grid by means of a rectifier and inverter. The Fall_2021_UNH_Measurement_Timeline.png highlights when each instrument was functioning and the Fall_2021_UNH_Test_Log.jpg indicates the four main regions for analysis available from this measurement campaign. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal forcing with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Kaelin Chancey (Assessment Of The Localized Flow And Tidal Energy Conversion System At An Estuarine Bridge - UNH MS Thesis 2019). The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. This project was pursued to quantify device performance for cross flow turbines operating in a marine environment. Accurate physical models, to characterize cross flow turbine performance, require real operational data sets due to the complexity of blade fluid interactions. This data can help support model development which will help predict turbine performance when analyzing perspective project locations in the future. Instrumentation was deployed to measure; water speed/direction, electrical power output, turbine shaft speed, turbine thrust force, and platform motion. Concurrent measurements of these parameters allow for correlations (cause and affect) to be inferred, allowing for characterization of device performance over a range of operating conditions. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) directly upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier and the Shark power meter. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. This submission includes zipped folders for each instrument containing quality controlled (QC'd) data in daily .csv files for the relevant duration specific to each instrument, along with separate .csv file that contains the units for each variable. Some instrument daily files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. Note the degree of QC varied between each instrument due to time constraints. Particular time and attention was given to perform quality control tests on the acoustic based instruments that are particularly suscep...

16 TIDAL AND WAVE POWER↗

In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow

This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.

16 TIDAL AND WAVE POWER↗

On the Injection Scale of the Turbulence in the Partially Ionized Very Local Interstellar Medium

The cascade of magnetohydrodynamic (MHD) turbulence is subject to ion–neutral collisional damping and neutral viscous damping in the partially ionized interstellar medium. By examining the damping effects in the warm and partially ionized local interstellar medium, we find that the interstellar turbulence is damped by neutral viscosity at ~261 au and cannot account for the turbulent magnetic fluctuations detected by Voyager 1 and 2. The MHD turbulence measured by Voyager in the very local interstellar medium (VLISM) should be locally injected in the regime where ions are decoupled from neutrals for its cascade to survive the damping effects. With the imposed ion–neutral decoupling condition and the strong turbulence condition for the observed Kolmogorov magnetic energy spectrum, we find that the turbulence in the VLISM is sub-Alfvénic, and its largest possible injection scale is ~194 au.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterization of the Vertical Evolution of the Three-Dimensional Turbulence for Fatigue Design of Tidal Turbines

A system of two coupled four-beam acoustic Doppler current profilers was used to collect turbulence measurements over a 36-h period at a highly energetic tidal energy site in Alderney Race. This system enables the evaluation of the six components of the Reynolds stress tensor throughout a large proportion of the water column. The present study provides mean vertical profiles of the velocity, the turbulence intensity and the integral lengthscale along the streamwise, spanwise and vertical direction of the tidal current.

Alderney Race↗

Effect of magnetic perturbations on turbulence-flow dynamics at the L-H transition on DIII-D

Detailed 2D turbulence measurements from the DIII-D tokamak provide an explanation for how resonant magnetic perturbations (RMPs) raise the L-H power threshold P LH [P. Gohil et al. , Nucl. Fusion 51 , 103020 (2011)] in ITER-relevant, low rotation, ITER-similar-shape plasmas with favorable ion ∇ B direction. RMPs simultaneously raise the turbulence decorrelation rate Δ ω D and reduce the flow shear rate ω shear in the stationary L-mode state preceding the L-H transition, thereby disrupting the turbulence shear suppression mechanism. RMPs also reduce the Reynolds stress drive for poloidal flow, contributing to the reduction of ω shear . On the ~100 μ s timescale of the L-H transition, RMPs reduce Reynolds-stress-driven energy transfer from turbulence to flows by an order of magnitude, challenging the energy depletion theory for the L-H trigger mechanism. In contrast, non-resonant magnetic perturbations, which do not significantly affect P LH , do not affect Δ ω D and only slightly reduce ω shear and Reynolds-stress-driven energy transfer.<

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Turbulence-Resolving Simulations of Hurricane Laura (2020): Insights Into Extreme Winds and Eyewall Turbulence

Extreme weather events pose significant risks to coastal and offshore energy infrastructure. In this work, we investigate the structure of mean winds and turbulence near the surface ( z < 300 m) that occurred during Hurricane Laura in 2020 on the US Gulf Coast. To this end, we perform turbulence-resolving simulations (..delta..x = 33.33 m) that encompass the entire eyewall of Hurricane Laura by introducing a novel method that we will refer to as Moving-Mesoscale to Static-LES Integrated Coupling (MOSAIC). The simulation results are validated against surface, boundary-layer, and mid-tropospheric observations. Our analysis of the extreme wind conditions near the surface indicates that the mean wind and turbulence profiles vary greatly at and near the eyewall, resulting in extreme values of mean wind speed (U > 50 m * s-1) and turbulence kinetic energy (k ~ 50 m2 * s-2) at altitudes above 50 m . To investigate in detail the nature of turbulence within the eyewall of the storm, we conduct higher-resolution simulations (..delta..x = 11.11 m) of a portion of the hurricane. We provide a comprehensive statistical description of turbulence in the eyewall region, highlighting the need to employ ..delta..x ~ 10 m grid spacing to capture the integral length-scales near the surface, second- and higher-order central moments (i.e., skewness and kurtosis), and spectral coherence in the flow accurately. These numerical simulations provide the most detailed description of mean winds and turbulent conditions within the eyewall of a historical tropical cyclone to date, illustrating how high-resolution simulations can enhance limited turbulence measurements in hurricanes and giving insight into the extreme conditions threatening offshore and coastal infrastructure.

17 WIND ENERGY↗

Validation of turbulence intensity as simulated by the Weather Research and Forecasting model off the US northeast coast

We report turbulence intensity (TI) is often used to quantify the strength of turbulence in wind energy applications and serves as the basis of standards in wind turbine design. Thus, accurately characterizing the spatiotemporal variability in TI should lead to improved predictions of power production. Nevertheless, turbulence measurements over the ocean are far less prevalent than over land due to challenges in instrumental deployment, maintenance, and operation. Atmospheric models such as mesoscale (weather prediction) and large-eddy simulation (LES) models are commonly used in the wind energy industry to assess the spatial variability of a given site. However, the TI derivation from atmospheric models has not been well examined. An algorithm is proposed in this study to realize online calculation of TI in the Weather Research and Forecasting (WRF) model. Simulated TI is divided into two components depending on scale, including sub-grid (parameterized based on turbulence kinetic energy (TKE)) and grid resolved. The sensitivity of sea surface temperature (SST) on simulated TI is also tested. An assessment is performed by using observations collected during a field campaign conducted from February to June 2020 near the Woods Hole Oceanographic Institution Martha's Vineyard Coastal Observatory. Results show that while simulated TKE is generally smaller than the lidar-observed value, wind speed bias is usually small. Overall, this leads to a slight underestimation in sub-grid-scale estimated TI. Improved SST representation subsequently reduces model biases in atmospheric stability as well as wind speed and sub-grid TI near the hub height. Large TI events in conjunction with mesoscale weather systems observed during the studied period pose a challenge to accurately estimating TI from models. Due to notable uncertainty in accurately simulating those events, this suggests summing up sub-grid and resolved TI may not be an ideal solution. Efforts in further improving skills in simulating mesoscale flow and cloud systems are necessary as the next steps.

17 WIND ENERGY↗

Can machine learning improve the model representation of turbulent kinetic energy dissipation rate in the boundary layer for complex terrain?

Current turbulence parameterizations in numerical weather prediction models at the mesoscale assume a local equilibrium between production and dissipation of turbulence. As this assumption does not hold at fine horizontal resolutions, improved ways to represent turbulent kinetic energy (TKE) dissipation rate (ϵ) are needed. Here, we use a 6-week data set of turbulence measurements from 184 sonic anemometers in complex terrain at the Perdigão field campaign to suggest improved representations of dissipation rate. First, we demonstrate that the widely used Mellor, Yamada, Nakanishi, and Niino (MYNN) parameterization of TKE dissipation rate leads to a large inaccuracy and bias in the representation of ϵ. Next, we assess the potential of machine-learning techniques to predict TKE dissipation rate from a set of atmospheric and terrain-related features. We train and test several machine-learning algorithms using the data at Perdigão, and we find that the models eliminate the bias MYNN currently shows in representing ϵ, while also reducing the average error by up to almost 40 %. Of all the variables included in the algorithms, TKE is the variable responsible for most of the variability of ϵ, and a strong positive correlation exists between the two. These results suggest further consideration of machine-learning techniques to enhance parameterizations of turbulence in numerical weather prediction models.

58 GEOSCIENCES↗

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗