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DOE OSTI2020

Maximising the investment returns of a grid‐connected battery considering degradation cost

Energy storage systems (ESSs) are being deployed widely due to numerous benefits including operational flexibility, high ramping capability, and decreasing costs. This study investigates the economic benefits provided by battery ESSs when they are deployed for market‐related applications, considering the battery degradation cost. A comprehensive investment planning framework is presented, which estimates the maximum revenue that the ESS can generate over its lifetime and provides the necessary tools to investors for aiding the decision making process regarding an ESS project. The applications chosen for this study are energy arbitrage and frequency regulation. Lithium‐ion batteries are considered due to their wide popularity arising from high efficiency, high energy density, and declining costs. A new degradation cost model based on energy throughput and cycle count is developed for Lithium‐ion batteries participating in electricity markets. The lifetime revenue of ESS is calculated considering battery degradation and a cost–benefit analysis is performed to provide investors with an estimate of the net present value, return on investment and payback period. The effect of considering the degradation cost on the estimated revenue is also studied. The proposed approach is demonstrated on the IEEE Reliability Test System and historical data from PJM Interconnection.

25 ENERGY STORAGE↗

DOE OSTI2023

Improved Water Sound Synthesis using Coupled Bubbles

We introduce a practical framework for synthesizing bubble-based water sounds that captures the rich inter-bubble coupling effects responsible for low-frequency acoustic emissions from bubble clouds. We propose coupled-bubble oscillator models with regularized singularities, and techniques to reduce the computational cost of time stepping with dense, time-varying mass matrices. Airborne acoustic emissions are estimated using finite-difference time-domain (FDTD) methods. We propose a simple, analytical surface-acceleration model, and a sample-and-hold GPU wavesolver that is simple and faster than prior CPU wavesolvers. Sound synthesis results are demonstrated using bubbly flows from incompressible, two-phase simulations, as well as procedurally generated examples using single-phase FLIP fluid animations. Our results demonstrate sound simulations with hundreds of thousands of bubbles, and perceptually significant frequency transformations with fuller low-frequency content.

Computer Science↗

DOE OSTI2020

A Retrospective of Findings From the FORTE Satellite Mission

We revisit the findings from the FORTE satellite program (1997–2004), which collected optical imaging of lightning as well as optical and radio frequency time series waveforms globally from low-earth-orbit. These include surveys of the earth's radio frequency anthropogenic noise environment; earth surface reflectivity at radio frequencies; a scheme for classifying lightning discharge types on the basis of their very high frequency time domain power envelope; insights into the polarization and radiation pattern characteristics of different lightning types, with implications for the underlying discharge processes; and estimates of cloud optical properties based on the statistics of scattered light. Most significantly, FORTE was uniquely suited to capture large samples of data from the rare discharge known as “narrow bipolar events,” enabling detailed examination of their basic characteristics and confirming that they appear to result from fundamentally distinct physical processes compared to other lightning. In particular, despite representing huge charge transfer they evidently produce little-to-no light output.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Further, comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Radiation driven Hohlraum using 2 ω for ICF implosions at the NIF

Radiation flux symmetry in laser-irradiated Hohlraum environments is difficult to model and control and relies on the details of plasma evolution and laser energy deposition in the harsh plasma-filled Hohlraum over the duration of the laser pulse. This study presents a conceptual design and assesses the feasibility of using lasers to create a radiation drive where the implosion symmetry relies mainly on radiation transport. In this design, the ends of a capsule containing Hohlraum are irradiated by drive laser beams that are shielded from the view of the capsule. This configuration enables the use of frequency doubled light that has a higher power and energy threshold for the current capability of NIF, up to 670 TW and ∼3.5 MJ. We estimate, using VISRAD benchmarked against HYDRA calculations, that the same drive conditions that are currently being achieved in hybridE experiments at the NIF 270–290 at the equator can be reached in this new geometry and large 6.4 mm diameter Hohlraums. The radiation drive asymmetries in this design can be mitigated by shimming the capsule ablator thickness or through tailoring the shape of the shielding to the laser spots.

Kritcher, A. L. (ORCID:0000000296941088)↗

DOE OSTI2023

Energy transport analysis of NSTX plasmas with the TGLF turbulent and NEO neoclassical transport models

This work presents a study of plasma transport at low aspect ratio on the National Spherical Torus Experiment tokamak, where the turbulent and neoclassical energy fluxes calculated by the quasilinear Trapped Gyro Landau Fluid (TGLF) model and the multi species drift-kinetic Neoclassical solver (NEO) are validated against experimental data. The turbulent energy transport of two plasma discharges, one in the L-mode confinement regime and another in the H-mode regime, is dominated by electrostatic drift-wave instabilities, while the ion heat transport has a significant neoclassical contribution. The data analysis workflow is described in detail to understand how the variations of mapping and fitting of experimental data affect the power balance solution and subsequent flux-matching plasma profile predictions with the TGYRO solver. On average, the predicted plasma profiles are consistent with experimental data. However, the solutions are sensitive to various input parameters, including boundary conditions, and the electron-ion coupling. Linear gyrokinetic stability analysis demonstrates close agreement of the real frequencies of unstable modes between TGLF and CGYRO gyrokinetic simulations, but higher growth rates are predicted by TGLF, especially for the H-mode case. Estimates of the low-k modes' contributions to the total flux are consistent with linear stability analysis and the E × B suppression of turbulence in TGLF simulations with the SAT1 saturation model, while the SAT2 saturation model over-predicts the low-k modes' contribution in the H-mode case. Moreover, the results with SAT1 model are consistent with power balance analysis, which indicates only neoclassical ion energy fluxes inside ρ < 0.4 in the L-mode case and $\rho \unicode{x2A7D} 0.7$ in the H-mode case. The presence of multi-scale turbulence and ion-scale driven zonal flow mixing effects are also observed in TGLF scans of the electron turbulent heat flux over a range of temperature gradients and the electron-ion temperature ratio, which could explain the strong model sensitivity to variations of input parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Short-Term Energy and Meteorological Impacts on Thanksgiving CO2 in Salt Lake City

Abstract Long-term, high-frequency atmospheric CO2 measurements at multiple sites in the Salt Lake City (SLC), Utah, reveal that annual and monthly CO2 variability aligns with a priori estimates of emissions from anthropogenic and biological sources. In this study, we investigate whether short-term fluctuations in anthropogenic emissions, as captured in the Vulcan3 dataset for the United States, can be detected in atmospheric CO2 observations. Specifically, we focus on Thanksgiving holidays, when traffic and energy usage patterns differ from the rest of November. Onroad CO2 emissions exhibit a double peak during weekday morning and evening rush hours but remain relatively low on weekends and Thanksgiving. Interestingly, CO2 mole fractions during Thanksgiving were higher than the rest of November at all SLC monitoring sites, particularly from 2008 to 2013. This increase is partially attributed to elevated energy-related emissions — especially residential sources — and meteorological factors such as weak wind speeds, cold temperature, and a low planetary boundary layer height (PBLH). While CO₂ emissions and mole fraction patterns align over time, notable spatial differences exist. For instance, the near-highway site in Murray shows the highest CO₂ mole fractions despite low local emissions, suggesting pollution transport via highways and wind advection. Random Forest model-based SHapley Additive exPlanations (SHAP) analysis reveals that onroad emissions dominate CO2 contributions on weekdays and weekends, while energy-related emissions play a larger role during Thanksgiving, alongside meteorological drivers such as wind speed and PBLH. Across six urban cities, CO2 emissions display a consistent pattern: residential and commercial (onroad) emissions peak during Thanksgiving (weekday) with substantial (minimal) year-to-year variability. These findings highlight that urban CO₂ variability is driven by the combined influence of emissions and meteorology, underscoring the need for integrated mitigation strategies. Additionally, multi-site measurements are essential for accurate source attribution and the development of effective policy interventions. 

Ryoo, Ju-Mee (ORCID:0000000234256296)↗

DOE OSTI2021

Using Models to Predict the Hygrothermal Performance of Equipment and Piping Insulation

The development of hygrothermal models began in earnest in the 1990s, with the initial emphasis on the performance of building envelope systems. Numerous large-scale building envelope failures associated with water intrusion drove this development. The physical principles of moisture transfer that apply to building envelopes are equally valid for equipment and piping insulation systems. The main advantage of modeling is that carefully characterized models can predict the long-term hygrothermal performance of any system under different climatic and interior conditions. Thermal insulations are commonly used on outdoor equipment and piping for different applications, such as thermal energy conservation and freeze protection. The insulated equipment usually experiences moisture intrusion due to many factors, such as the duration and frequency of moisture exposure, equipment operating temperature, insulation type, exposure temperature, weather conditions, equipment thermal cycling, and weatherproofing condition. Hygrothermal models have been employed to estimate the moisture pickup of insulated equipment and piping systems, as well as the moisture redistribution and subsequent change in thermal performance as these systems become contaminated with moisture. The hygrothermal model provides insights on the parameters influencing the time of wetness, the lateral redistribution of moisture along the pipe away from the leak, and the ease by which water escapes the insulation/jacketing systems. It has been shown that the moisture leak effect decreases rapidly with distance from the leak and that one- and two-dimensional hygrothermal simulations help to identify solutions to reduce conditions that support corrosion under insulation (CUI).

Shrestha, Som↗

DOE OSTI2025

Simultaneous Observation of Ion-scale Wave Packets with Opposite Polarizations and Their Implications on the Generation Region in the Inner Heliosphere

This paper reports a dispersion analysis of two wave packets simultaneously observed near the local proton gyrofrequency by the Parker Solar Probe. The observed wave event exhibits clear two-banded wave packets both propagating along the magnetic field, characterized by left-handed (L-mode) and right-handed (R-mode) polarizations simultaneously. By incorporating the Doppler shift effect into a linear dispersion analysis, we find two possible scenarios that explain these simultaneous opposite polarizations: (1) Two inherently L-mode waves in the plasma frame, propagate parallel and antiparallel to the solar wind velocity, with similar wave frequencies and wave numbers. The polarization of the antiparallel propagating wave reverses as it moves sunward in the plasma frame while still comoving with the solar wind in the stationary frame. This reversal manifests the polarization of the wave as an R-mode in the spacecraft frame. (2) Simultaneous L-mode and R-mode waves propagate parallel to the solar wind velocity, with different wave frequencies and wave numbers. Concurrent proton observations during the wave event reveal a dominant anisotropic ($T$⟂/$T$ ∥ > 1) core distribution with a drifting beam population. Estimation of the linear growth rate for both L-mode and R-mode waves suggests that both scenarios are plausible, indicating that the observation is near the wave-generation region. We explore the potential impact of these simultaneous waves on solar wind heating and scattering effects, hypothesizing that such waves might enhance efficiency compared to waves with a single wave packet, contingent upon the statistical significance of such waves.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability

Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.

14 SOLAR ENERGY↗

DOE OSTI2020

Relaxation time estimation in surface NMR

Technologies including NMR relaxation time estimation methods and corresponding apparatus are disclosed. Example techniques may include performing at least one single-pulse acquisition sequence, the single-pulse acquisition sequence comprising transmitting a single modulated pulse with a surface coil, wherein the phase, frequency, or amplitude of the single modulated pulse is varied during the single modulated pulse, and wherein the single modulated pulse excites a transverse magnetization component within a subsurface fluid. The resulting NMR signal may be recorded on at least one receiving device, including recording the NMR signal associated with the transverse magnetization component excited by the single modulated pulse. Processing techniques may be applied in which recorded NMR response data are used to estimate NMR properties and the relaxation times T1 and T2* as a function of position as well as one-dimensional and two-dimension distributions of T1 versus T2* as a function of subsurface position.

58 GEOSCIENCES↗

DOE OSTI2022

Second Annual Report on Development of Microwave Resonant Cavity Transducer for Fluid Flow Sensing

We are investigating a microwave resonant cavity transducer for flow sensing in the vessel of a high temperature fluid advanced reactor (AR), such as a molten salt cooled reactor (MSCR) or a sodium fast reactor (SFR). This transducer is a hollow metallic cylindrical cavity, with the flat wall of the cylinder flexible enough to undergo microscopic deflection due to dynamic fluid pressure. Membrane deflection leads to a shift in the resonant frequency, which can be detected with a spectrum analyzer. Because the transducer is intended for immersion in a high temperature corrosive fluid, understanding of material degradation is crucial for estimation of transducer performance lifetime, and development of measurement interpretation algorithms. We conducted a preliminary computational investigation of relevant damage mechanisms of a stainless steel 316 cylindrical resonator in FLiBe salt. The two main damage mechanisms, creep and corrosion, were modeled using multiphysics COMSOL software. Degradation was modeled for a temperature range 500°C to 700°C. Coupling of the damage mechanisms was not considered. These models predict significant inelastic deformation at most temperatures due to creep, and qualitatively predict chromium depletion both along the liquid/solid interface and along the grain boundaries. An algorithmic approach for compensation of these degradation effects during fluid flow measurements will be developed in the future work. To validate sensor physics, we have performed proof-of-principle test of flow sensing in water. For this test, we have developed a cylindrical resonator for K-band, which was machined from brass. The cavity was excited through WR-42 waveguide through a subwavelength hole on the side of the wall of the cylinder. To increase the spectral signal visibility, we developed a signal processing method for baseline subtraction. A flow loop for proof-of-principle test of transducer performance in water was assembled. A commercial flow meter was installed in the loop for reference measurements. Cylindrical cavity was excited in the TE 011 mode with resonant frequency f ≈ 17.8GHz. Frequency shift of cavity spectral response was obtained by gradually increasing water flow rate from 0 to 60gpm. Corresponding monotonic increase of resonant frequency shift by several MHz was observed. Approximate figure of merit of sensitivity to flow rate is 100KHz/GPM. In addition, we have identified an existing liquid sodium experimental setup for demonstration of flow sensing in environment similar to that of an advanced reactor. The setup consists of a cylindrical vessel and center feed line, where transducer inserted through the lid will measure velocity of the impinging liquid jet. As a calibration experiment, we have assembled a water vessel with center feed with the same dimensions as those of the liquid sodium setup. We have also developed and insertion probe consisting of a 50cm brass waveguide enclosed in protective SS316 tube. Using the water loop, we have demonstrated feasibility of sensing the impinging liquid jet in the vessel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

The effect of magnetic susceptibility and magnetic field strength on porosity estimates determined from low-field nuclear magnetic resonance

The presence of materials with high magnetic susceptibility are known to have an impact on 1H nuclear magnetic resonance (NMR) measurements and in laboratory data this often results in poor estimates of porosity from NMR data. To quantify and understand the cause of the poor NMR porosity estimations, in this laboratory study, we examine the effect of magnetic susceptibility, NMR measurement parameters, and NMR instrument design on NMR measurements. Data were collected with two instruments, each with a different Larmor frequency (2 MHz and 485 kHz), on water-saturated unconsolidated sediments with magnetic susceptibility values ranging from 3.6 × 10 -6 to 7020 × 10 -6 SI. The results show that for materials with low magnetic susceptibility (<378 × 10 -6 SI), the gravimetric porosity is accurately predicted from the NMR measurements. For the samples with high magnetic susceptibility (>987 × 10 -6 SI) the gravimetric porosity is poorly predicted from the 2 MHz NMR measurements made at all echo times (from 0.2 to 3.0 ms). In contrast, the gravimetric porosity is more accurately predicted at an echo time of 0.2 ms for measurements made using the 485 kHz instrument, although at larger echo times (>1.0 ms), the porosity estimate becomes poor. The 485 kHz NMR instrument has non-zero internal magnetic field gradients, similar to those found in borehole instruments, in contrast to the 2 MHz NMR instrument, which has a homogeneous applied magnetic field. Finally, we conclude that differences is the magnetic field strength and higher magnetic field inhomogeneities in the 485 kHz NMR instrument contribute to a reduction of the impact of inhomogeneities in the magnetic field caused by materials with high magnetic susceptibility, allowing for improved porosity estimation. These results indicate that NMR measurements collected at short echo times in low, inhomogeneous static fields, e.g., borehole instruments, may provide accurate estimates of porosity in water saturated sediments, even in the presence of magnetic minerals.

58 GEOSCIENCES↗

DOE OSTI2021

Estimating the strength of selection for new SARS-CoV-2 variants

Abstract Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is needed to determine whether a new variant is a global threat and the magnitude of its selective advantage. We present two models for quantifying the strength of selection for new and emerging variants of SARS-CoV-2 relative to the background of contemporaneous variants. These methods range from a detailed model of dynamics within one country to a broad analysis across all countries, and they include alternative explanations such as migration and drift. We find evidence for strong selection favoring the D614G spike mutation and B.1.1.7 (Alpha), weaker selection favoring B.1.351 (Beta), and no advantage of R.1 after it spreads beyond Japan. Cutting back data to earlier time horizons reveals that uncertainty is large very soon after emergence, but that estimates of selection stabilize after several weeks. Our results also show substantial heterogeneity among countries, demonstrating the need for a truly global perspective on the molecular epidemiology of SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

The Diurnal Dynamics of Gross Primary Productivity Using Observations From the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R Series at an Oak Savanna Ecosystem

Gross primary productivity (GPP) is the largest flux in the global carbon cycle and satellite-based GPP estimates have long been used to study the trends and interannual variability of GPP. With recent updates to geostationary satellites, we can now explore the diurnal variability of GPP at a comparable spatial resolution to polar-orbiting satellites and at temporal frequencies comparable to eddy covariance (EC) tower sites. We used observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite-R series (GOES-R) to test the ability of subdaily satellite data to capture the shifts in the diurnal course of GPP at an oak savanna EC site in California, USA that is subject to seasonal soil moisture declines. We compared three methods to estimate GPP: (a) a light-use efficiency model, (b) a linear relationship between the product of near-infrared reflectance of vegetation and photosynthetically active radiation (LIN-NIR v P) and EC tower GPP, and (c) a light response curve (LRC-NIR v P) between NIR v P and EC GPP. The LRC-NIR v P achieved the lowest mean absolute error for winter (2 µmol CO 2 m –2 s –1 ), spring (2.51 µmol CO 2 m –2 s –1 ), summer (1.43 µmol CO 2 m –2 s –1 ), and fall (1.35 µmol CO 2 m –2 s –1 ). The ecosystem experienced the largest shift in daily peak GPP in relation to the peak of incoming solar radiation toward the morning hours during the dry summers. The LRC-NIRvP and the light-use efficiency model were in agreement with these patterns of a shift in peak daily GPP toward the morning hours during summer. Our results can help develop diurnal estimates of GPP from geostationary satellites that are sensitive to fluctuating environmental conditions during the day.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗

DOE OSTI2022

Dipolar Heteronuclear Correlation Solid-State NMR Experiments between Half-Integer Quadrupolar Nuclei: The Case of 11 B– 17 O

With 73% of all NMR-active nuclei being quadrupolar, there is great interest in the development of NMR experiments that can probe the proximity of quadrupolar spins. Here, pulse sequences for magic-angle spinning (MAS) 11 B– 17 O resonance-echo saturation-pulse double-resonance (RESPDOR) and dipolar heteronuclear multiple quantum correlation (D-HMQC) solid-state NMR experiments were investigated. In these pulse sequences, rotational-echo double-resonance (REDOR) recoupling was used with central transition (CT)-selective π-pulses applied to either the 11 B or 17 O spins to recouple 11 B– 17 O dipolar interactions. 11 B{ 17 O} RESPDOR experiments on 17 O-enriched boric acid and benzene diboronic acid showed that application of dipolar recoupling on the 11 B channel yielded more signal dephasing than when recoupling is applied on the 17 O channel; however, short effective 11 B transverse relaxation time constants (T 2 ') hinder the acquisition of dephasing curves out to long recoupling durations. Application of REDOR recoupling to 17 O spins was found to produce significant dephasing without compromising the 11 B T 2 '. Comparison of experimental 11 B{ 17 O} RESPDOR curves to those of numerical simulations enabled the 17 O isotopic enrichment to be estimated. 2D 11 B{ 17 O} D-HMQC spectra were recorded with either 11 B or 17 O REDOR recoupling under a variety of radio frequency field conditions. Lastly, 2D 11 B{ 17 O} and 23 Na{ 17 O} D-HMQC spectra of an 17 O-enriched sodium borate glass were acquired to demonstrate the practical application of these heteronuclear correlation experiments to probe structural connectivity between two quadrupolar spins. Importantly, the high-field 2D 11 B– 17 O D-HMQC NMR spectrum revealed two unique 17 O sites correlating to 4-coordinate BO 4 ( [4] B), which were attributed to the [3] B–O– [4] B and [4] B–O– [4] B bridging O atoms. Furthermore, the heteronuclear correlation experiments outlined here should be applicable to a variety of quadrupolar spin pairs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Experimental Validation of a Kinetic Ballooning Mode in High-Performance High-Bootstrap Current Fraction Fusion Plasmas

We report the observation of a set of coherent high frequency electromagnetic fluctuations that leads to a turbulence induced self-regulating phenomenon in the DIII-D high bootstrap current fraction plasma. The fluctuations have frequency of 130~220kHz, the poloidal wave length and phase velocity are 16~30 m -1 and ~30 km/s, respectively in the outboard midplane with the estimated toroidal mode number n~5- 9. The fluctuations are located in the internal transport barrier (ITB) region at large radius and are experimentally validated to be kinetic ballooning modes (KBM). Furthermore, quasilinear estimation predicts the KBM to be able to drive experimental particle flux and non-negligible thermal flux, suggesting its significant role in regulating the ITB saturation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗