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At least 577 records · Page 32

Development of a half-meter scale Traveling-Wave (TW) SRF cavity

Traveling-wave technology can push the accelerator field gradient of niobium SRF cavity to 70MV/m or higher beyond the fundamental limit of 50~60MV/m in Standing-Wave regime. The 1st demonstration of TW resonance excitation in a proof-of-principle 3-cell SRF cavity in 2K liquid helium was successfully carried out at Fermilab in collaboration with Euclid Techlabs. In parallel with that, the RF design process of 0.5~1 meter scale TW cavity was begun at Fermilab for advancing TW technologies necessary more for future accelerator-scale one. Considering the physical dimensions of existing SRF facilities (for fabrication, processing, and cryogenic testing) and the lessons learned from the 3-cell, Fermilab has proposed a preliminary RF design of a half-meter scale TW SRF cavity. It consists of a 7-cell structure and a power feedback waveguide (WG) loop with new RF configurations to control TW resonance. Here we report a preliminary RF design, development plans, and activities.

43 PARTICLE ACCELERATORS↗

Microscopic understanding of the effects of impurities in low RRR SRF cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, K.↗

Design and Engineering of LUPIN: A Test-Bed Radiofrequency Ion Source for Enhanced Neutral Beam Injection on DIII-D

The Large, Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma (ICP) chamber for demonstrating plasma performance of an RF ICP positive ion source upgrade for the DIII-D Neutral Beam Injection (NBI) system. LUPIN will be used to investigate ion source physics, including neutral gas dynamics, plasma density uniformity, interactions with Faraday shields, and power coupling to novel RF antenna designs. LUPIN has an RF generator capable of delivering 20 kW of power at 2 MHz, which is coupled into a cylindrical quartz vessel measuring 20 cm in length and 10 cm in radius. This configuration matches the power density requirements for a full-scale ion source. Target hydrogen and deuterium plasma densities exceeding 10 18 m -3 would relate to extracted ion current densities of 2100 A/m 2 for 10 s. Vacuum conductance and gas flow calculations predict a maximum achievable neutral gas flow rate of 1675 Pa·L/s at 5 Pa of He, which mimics the gas flow of the DIII-D NBI system. Designs have been developed for an internal Faraday shield to mitigate heat flux and ion sputtering on the dielectric vessel. Thermomechanical finite element simulations demonstrated the Faraday shield design to be capable of withstanding anticipated heat loads from worst-case operation scenarios. Results of upcoming experimental investigations on LUPIN will guide the design of a full-scale prototype for DIII-D integration.

Faraday shield↗

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

PIP-II LLRF Master Oscillator and Precision Reference Line- Station Level Design and Testing

The PIP-II superconducting linac at Fermilab requires a highly stable RF Reference Line to maintain phase synchronization throughout the accelerator. Temperature-induced changes in the electrical length of long coaxial cables can introduce phase drift and measurement errors. The reference-line architecture mitigates these effects by phase averaging the forward and reflected RF signals, while a phase-locked loop anchors the system to the master oscillator. This work focuses on the characterization, validation, and mechanical integration of station-level RF assemblies using CAD modeling, vector network analyzer measurements, and spectrum analyzer testing. PID-controlled thermal plates will stabilize critical RF components and further reduce temperature-dependent phase and amplitude variations. These methods support repeatable, standardized designs that can be reliably integrated across the different reference-line stations.

Mosher, Alexander [U. Illinois, Chicago; Fermilab]↗

A low-frequency buncher field-variation study on a 750 keV H – beam to increase Drift Tube Linac capture

We report low-frequency (such as 16.77 MHz) RF bunchers are widely used in RF accelerator systems for longitudinal compression of pulses into a single RF bucket, which increases instantaneous beam intensity for time-dependent studies. In this study, the dependency of capture into a 201.25 MHz Drift Tube Linac (DTL) was measured as a function of gap voltage for a 16.77 MHz buncher on chopped H - beam (approximately 25 ns at 750 keV, 10 mA peak current). The multiparticle code PARMILA was used to simulate the phase-space distribution of the 10 mA, 750 keV, H - beam at the entrance to DTL with a wide range of the Low-Frequency Buncher (LFB) field (10 kV to 35 kV). The measurement and simulation indicated that the DTL capture could be dilute (reduced) for a non-optimized buncher field to a pre-configured beamline geometry. The data shows that changing the bunch field while keeping the incoming beam current and energy constant does not significantly alter the beam’s emittance. However, downstream beam capture into the DTL is changed for a non-optimized phase-space bunching distance with the buncher field.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Erosion of high-Z refractory coatings for helicon plasma source window

Proto-MPEX (Materials Plasma Exposure eXperiment), a linear plasma device (LPD), using a high power radio frequency (RF) (⩾100 kW, 13.56 MHz) helicon plasma source, has suffered RF sheath-induced window erosion. The sputtered impurities from the window surface transport toward the downstream target affecting plasma-material interaction studies. The rectified sheath voltage formed was high enough to cause window erosion by light ions due to its low-Z components (e.g. Si 3 N 4 and AlN). Hence, we are proposing impurity mitigation strategies, which involve the application of a Faraday screen to lower the rectified sheath voltage and the application of high-Z refractory coatings on the existing window plasma-facing surface. In this work, we report the erosion of two different coatings, i.e., tantalum oxide (Ta 2 O 5 ) and hafnium oxide (HfO 2 ) on a silicon nitride (Si 3 N 4 ) window material under conditions of low-energy deuterium (D) ion impact, well below the Ta 2 O 5 sputtering energy threshold (i.e. 250 eV). The test samples were RF-biased and exposed to a high D-ion fluence (∼10 26 m −2 ) in Plasma Interaction with Surface Component Experimental Station (PISCES-A) LPD. The experimentally measured sputtering yields of the high-Z refractory coatings below the sputtering energy threshold of Ta 2 O 5 indicate an increased erosion due to the plasma impurities, especially due to oxygen. Improving the vacuum level could reduce the oxygen impurities and increase the lifespan of the coated helicon window for plasma operation. Post-surface analysis indicates no preferential erosion of oxygen or enrichment of the high-Z surface component. This is likely due to an effective energy transfer from the impurity ion for sputtering of the high-Z component in the coating. With the reduced rectified sheath voltage at the window surface and improved vacuum conditions, the proposed high-Z refractory coatings offer a promising solution for reducing window erosion in future MPEX plasma operations at ORNL.

RF bias↗

Combined Optical and Radio-Frequency Perspectives on a Hybrid Cloud-To-Ground Lightning Flash Observed by the FORTE Satellite

In this work, we use the coincident optical and radio-frequency (RF) measurements taken by the Fast On-orbit Recording of Transient Events (FORTE) satellite to shed light on common optical signatures recorded by NASA and NOAA lightning imagers during Cloud-to-Ground (CG) lightning. We build flash cluster data for FORTE using the same techniques as the NASA/NOAA instruments to document the optical/RF evolution of an oceanic hybrid -CG flash. The flash began with strong Very High Frequency (VHF)-band emission from a Narrow Bipolar Event (NBE) that initiated a period of normal bilevel intracloud (IC) activity in two vertical layers (8 and 12 km) that lasted for 490 ms. VHF waveforms show step leader activity ahead of the return stroke. All impulsive VHF sources after the stroke come from the lower (8 km) layer. K-changes are noted following the return stroke, but no subsequent strokes are detected. The optical flash began 136 ms after the NBE RF pulse. Twenty-two of the 33 optical groups were dim and occurred during the in-cloud phase of the flash. This activity included both isolated pulses and sustained periods of illumination over tens of milliseconds. Initial cloud pulses accounted for 23% of the total optical radiance from the flash. Illumination during the return stroke contributed 58% of the total radiance, and the K-changes and cloud pulses after the stroke supplied the remaining 19%. These results highlight the benefit of having RF alongside optical lightning measurements for clarifying signatures in the optical data and providing information on their physical origins.

54 ENVIRONMENTAL SCIENCES↗

Validity condition for the local sheath impedance boundary condition and a nonlocal generalization

ICRF sheaths can cause unwanted interactions of high-power RF waves with material surfaces in magnetic fusion devices. In previous work, a local RF sheath impedance boundary condition (BC) was derived for use in ICRF codes together with a microscale (i.e., Debye or sheath width scale) model for obtaining the sheath impedance used in that BC. This local RF sheath BC matches the normal component of current and electrostatic potential across the sheath-plasma interface. Collapsing the matching conditions at the sheath-plasma interface to a BC depends on the assumption of scale separation, which can be violated when conditions along the local radius of curvature of the surface vary sufficiently rapidly. The validity condition is explored in this contribution, with special attention to the case where the magnetic field approaches being tangent to the surface. When the local sheath BC no longer applies, a non-local sheath BC is developed under the assumption of a more relaxed scale separation assumption. It is shown that the non-local sheath BC reduces to the previous local sheath BC under appropriate conditions. Furthermore, a surface-integrated sheath admittance parameter describes the 2D physics in the new BC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Absolute atomic hydrogen density measurements in an atmospheric pressure plasma jet: generation, transport and recombination from the active discharge region to the effluent

Atomic hydrogen (H) generated by atmospheric pressure radio frequency (RF) plasma jet is investigated by two-photon absorption laser induced fluorescence in a He-H 2 mixture. The reported time and spatially resolved H density profiles enable a detailed analysis of the species generation, transport and decay along the axis of symmetry of the jet. Here, the H density distribution for a continuous RF plasma jet corresponds well with the outcome of a Pseudo-1D plug flow model. In addition, RF power modulation has a strong effect on the H density in the active discharge region but has a negligible effect on the H density in the far effluent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Generalizing Similarity Laws for Radio-Frequency Discharge Plasmas across Nonlinear Transition Regimes

We generalize similarity theory based on the scaling and solution invariance of the Boltzmann equation, coupled with the Poisson equation, and demonstrate similarity laws for radio-frequency (rf) discharge plasmas across three nonlinear transitional regimes, namely, the alpha-gamma mode transition, the stochastic-Ohmic-heating mode transition, and the bounce-resonance-heating mode transition. Fundamental plasma parameters, e.g., the electron power absorption, under similar discharge conditions are examined via fully kinetic particle-in-cell simulations, and electron-kinetic invariance is exemplified in similar rf discharge plasmas. The results unambiguously confirm the applicability of similarity laws for rf plasmas in extended operating regimes, and strengthen the foundations and framework of similarity physics with universality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Predicting chatter using machine learning and acoustic signals from low-cost microphones

Machining chatter is a phenomenon resulting from self-oscillation between a machining tool and workpiece. This self-oscillation results in variation on the machined product that reduces the ability to meet desired specifications. Chatter is a widely studied topic as it directly relates to the quality of machined products. Here, this study details the application of a Random Forest (RF) classifier with Recursive Feature Elimination (RFE) to machining audio collected by a single microphone during down-milling operations. This approach allows straightforward feature elimination that results in an easily understood set of analyzed dimensions. Stability is predicted solely based on the classification output of the RF classifier. Our approach proves highly predictive with consistent machining setup and a small sample set. We also review transferability between machining setups and present key findings. Our RF approach demonstrates the ability to analyze and classify chatter through a low-cost approach with limited training data required. The motivation for using a single microphone is to enable detection on machines without other sensors, such as accelerometers, present in the machining setup. The value of the in-process sensor and chatter classifier is highlighted because the machining setup included asymmetric dynamics that reduced the accuracy of the traditional analytical stability solution. We see a natural progression to deploying this audio-only methodology with real-time processing and classification using either a laptop or smartphone. This progression will allow visual indicators during the machining process that can alert machinists of progression into unstable machining processes.

42 ENGINEERING↗

Chatter detection in simulated machining data: a simple refined approach to vibration data

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a novel approach to an RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

42 ENGINEERING↗

ELM Suppression by Boron Powder Injection and Comparison with Lithium Powder Injection on EAST

Type I edge-localized modes (ELMs) in the Experimental Advanced Superconducting Tokamak (EAST) were completely suppressed via boron powder injection into the X-point region of an upper-single null configuration over a wide range of operating conditions (2.8 < P aux < 7.5 MW, 3.8 × 10 19 < n e < 6 × 10 19 m -3 , RF-only and RF + NBI heating scenarios, both grad-B drift directions, and even He ion majority plasmas) (Sun et al. in Nucl. Fusion, 2020). A window of edge B concentration for stable long pulse operation was identified: too low and ELMs return, too high and the discharge suffers radiative collapse. The injection of boron powder above the minimum for ELM suppression coincided with the occurrence of an edge harmonic oscillation detected in magnetics (both on the high-field side and low-field side), in AXUV diodes near the upper X-point, divertor Dα emission, and in a range of other diagnostics (Diallo et al. in: Proceedings of 2020 IAEA fusion energy conference, 2021). Furthermore, no harmonic oscillation was observed when ELMs were present, and stored energy was slightly increased at constant density during ELM suppression. Core tungsten emission during ELM suppression either increased or decreased relative to ELMy H-mode, but the W emission was maintained at acceptable levels. The threshold B injection rate was measured for several conditions, and found to increase with heating power. Li powder injection into comparable discharges also resulted in a short phase of ELM suppression, but density and stored energy both decreased due to the strong pumping effect of lithium; no edge harmonic oscillation was observed with Li injection, indicating that the ELM suppression mechanisms differ. The new set of B-seeded, ELM-suppressed discharges exhibited certain characteristics of quiescent H-mode (Burrell et al. in Phys Plasmas 8:2153, 2001), but did not require high shear, counter beams, etc. The wide operating window and compatibility with RF-only discharges paves the way for future experiments targeting long pulse H-mode discharges with complete ELM suppression.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Additive manufacturing of nanotube-loaded thermosets via direct ink writing and radio-frequency heating and curing

Direct Ink Writing (DIW) is an extrusion-based additive manufacturing method where the print medium is a liquid-phase ‘ink’ dispensed out of nozzles and deposited along digitally defined paths. Conventional DIW of thermosetting resins relies on viscosity modifying agents, novel crosslinking chemistries, and/or long curing schedules in an oven. Here we demonstrate the use of a co-planar radio frequency applicator to generate an electric field, which can be used to rapidly heat and cure nano-filled composite resins as they are printed. This method avoids the need for an oven or post- curing step. This process consists of a sequential print-and-cure cycle which allows for printing of high-resolution, multi-layered structures. Every extruded layer is partially cured using RF before depositing the next layer; this allows the printed part to maintain structural integrity. The process enables both increased throughput and decreased touch time relative to traditional manufacturing. Commercial epoxy resin with varied nano-filler loadings were examined as DIW candidates. After printing, the thermo-mechanical properties, surface finish, and shape retention of RF-cured samples were comparable to conventionally cured samples. Furthermore, this method of manufacturing establishes RF heating as a suitable alternative to conventional methods, facilitating rapid, free-form processing of thermosetting resins without a mold.

36 MATERIALS SCIENCE↗

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗

Optical design and synthetic analysis of the electron cyclotron emission imaging diagnostic of HL-2M tokamak

The electron cyclotron emission imaging (ECEI) diagnostic is a powerful tool to study the MHD and turbulent transport in magnetically confined fusion plasmas. In this work, the optical system including the local oscillator (LO) coupling and radio frequency (RF) receiving optics, has been designed and analyzed for the HL-2M ECEI diagnostic. The LO optics can illuminate the antenna array and drive the mixer diode to work efficiently, with more than 36% of the beam intensity for the channels which probe the plasma edge relative to those of channels which probe the plasma core. The RF optics aims at guiding the plasma emission signal to the antenna array. To meet different physical requirements, three types of field of view have been achieved for the plasma imaging, with zoom factors of around 1, 1.5 and 2, respectively. The focal surfaces are almost flat, with a maximum off-mapping (defined as the radial distance between the beam waists of the lower-/uppermost antennas and electron cyclotron emission layer) less than 2.5 cm, which can match the electron cyclotron emission layer quite well and suppress the image distortion in the plasma edge region. Furthermore, the impact of possible vibrations and installation error on the focal plane has been evaluated. In addition, the predefined MHD and turbulence perturbations are well reproduced by combining the optical simulation results and synthetic ECEI modeling, which further verifies the good performance of the RF optics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Focusing ions at atmospheric pressure using nonlinear DC voltage sequences applied to a stacked ring ion guide

Many modern ion mobility (IM) and mass spectrometers (MS) operate under low pressure (= 10 Torr) and employ high voltage radiofrequencies (RF) to provide ion confinement. Unfortunately, RF effectiveness drastically decreases as pressure increases, and few techniques for focusing ions at elevated pressures exist. Here we demonstrate a new approach for focusing ions at atmospheric pressure (AP) by applying nonlinear DC voltage sequences following quadratic and power (exponential) functions to a stacked ring ion guide. In this work, we used ion trajectory simulations to rigorously explore how ions react to nonlinear electric fields and validate the simulations with a set of ion current measurements performed at AP. Ion trajectory simulations show that ions initially defocus near the entrance of the device but then become intensely focused as they travel through the device. Contour plots for both nonlinear voltage sequences show electric field lines that increasingly curve inwards as a function of distance, resulting in spatial ion focusing. Experimental ion current and spot size measurements were performed at AP using a 10-cm stacked ring ion guide and a segmented Faraday cup detector. Quadratic sequences produced ~5% smaller spot sizes (~22.8 mm) and ~25% higher ion current compared to a linear voltage sequence (~24.0 mm). Alternatively, power sequences produced ~64% smaller spot sizes (~8.7 mm), albeit with ~10x lower ion current. However, both nonlinear voltage sequences produced similar ion currents at the center of the Faraday cup detector, indicating that higher ion densities are achieved when using nonlinear voltage gradients. These results demonstrate a new way to focus ions at AP, and the capabilities demonstrated here provide fundamental insights on how to keep ions inside analytical devices at elevated pressures without RF.

47 OTHER INSTRUMENTATION↗