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At least 73 records · Page 4

Machine learning-aided line intensity ratio technique applied to deuterium plasmas

It has been demonstrated that the electron density, n e , and temperature, T e , are successfully evaluated from He I line intensity ratios coupled with machine learning (ML). In this paper, the ML-aided line intensity ratio technique is applied to deuterium (D) plasmas with 0.031 < n e (10 18 m –3 ) < 0.67 and 2.3 < T e (eV) < 5.1 in the PISCES-A linear plasma device. Two line intensity ratios, D α /D γ and D α /D β , are used to develop a predictive model for n e and T e separately. Reasonable agreement of both ne and Te with those from single Langmuir probe measurements is obtained at n e > 0.1 × 10 18 m –3 . Addition of the D 2 /D α intensity ratio, where the D 2 band emission intensity is integrated in a wavelength range of λ ~ 557.4–643.0 nm, is found to improve the prediction of, in particular, n e , and T e . It is also confirmed that the technique works for D plasmas with 0.067 < n e (10 18 m –3 ) < 6.1 and 0.8 < T e (eV) < 15 in another linear plasma device, PISCES-RF. The two training datasets from PISCES-A and PISCES-RF are combined, and unified predictive models for n e and T e give reasonable agreement with probe measurements in both devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Microgap breakdown with floating metal rod perturbations

Here, we report the characterization of microgap breakdown with perturbations from a metal rod floating between anode and cathode electrodes. The effects of the metal rod on the electric field distribution and the field enhancement factor are evaluated by numerical simulation and the conformal mapping method, and they indicate that the field emission regime is not reached. The breakdown voltages in the Townsend discharge regime are determined based on the voltage–current characteristics, which are obtained from two-dimensional fluid simulations. It is found that the breakdown characteristics can be significantly modulated by the floating metal rod, and the breakdown curve (breakdown voltage vs the net gap distance) is no longer U-shaped, which deviates from the conventional Paschen's law. The underlying physical mechanisms are related to the electric field enhancement, curved breakdown path, and nonuniform ion flux caused by the electric shielding effect. The results provide insights into breakdown characteristics in microscale discharges, which may promote conventional investigation of simplified clean gaps toward more complex conditions (e.g., with floating microparticles) in miniaturized plasma devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Theory of gradient drift instabilities in low-temperature, partially magnetised plasmas

A fluid dispersion theory in partially magnetised plasmas is analysed to examine the conditions under which large-wavelength modes develop in Penning-type configurations, that is, where an electric field is imposed perpendicular to a homogeneous magnetic field. The fluid dispersion relation assuming a slab geometry shows that two types of low-frequency, gradient drift instabilities occur in the direction of the E×B and diamagnetic drifts. One type of instability, observed when the equilibrium electric field and plasma density gradient are in the same direction, is similar to the classic modified Simon–Hoh instability. A second instability is found for conditions in which (i) the diamagnetic drift is in the direction opposite to the E×B drift and (ii) the magnitude of the diamagnetic drift is sufficiently larger than the electron thermal speed. The present fluid dispersion theory suggests that the rotating spokes driven by such fluid instabilities propagate in the same direction as the diamagnetic drift, which can be in the same direction as or opposite to the E×B drift, depending on the plasma conditions. This finding may account for the observation, in some plasma devices, of the rotation of large-scale structures in both the E×B and -E×B directions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Coupled Experimental/Computational Investigation of the Dynamics of Interacting Magnetized Plasmas

The interaction, or interpenetration, of magnetized plasmas of different density and/or pressure occurs in a wide variety of natural and man-made systems. Such systems include extragalactic jets propagating into the intergalactic medium, solar coronal mass ejections into background solar wind, compact toroid (CT) fueling of magnetic fusion plasmas, and jets of capsule shell impurities into DT fusion fuel, which can lead to enhanced impurity mix in inertial fusion implosions. These plasmas may take the form of jets, with open, helical magnetic structure, or plasma “bubbles” with closed magnetic fields (B-fields), such as spheromaks or CT’s. Such structures, both open and closed B-field cases, can transport heat, particles and magnetic flux or magnetic helicity into background plasma regions. For example, the origin of extragalactic magnetic fields may be due, at least in part, to transport by astrophysical jets. The goal of this proposed work was to elucidate the detailed plasma and magnetic field dynamics of high-density plasma jets (open B-field) and bubbles (closed B-field) propagating into lower density background magnetized plasma through controlled laboratory experiments and closely coupled nonlinear MHD modeling. These experiments were conducted in the HelCat (Helicon-Cathode) linear plasma device at the University of New Mexico (UNM). Plasma jets and bubbles were launched via an existing compact coaxial plasma gun, mounted on the HelCat device. This gun produced plasmas tens of cm in scale and lasting tens of microseconds, thereby allowing detailed multipoint, space- and time-resolved measurements to be made routinely. The experiments were directly modeled using the extended magnetohydrodynamic (XMHD) PERSEUS code, developed at Cornell University [23,24]. Both experimental and numerical modeling work are ongoing. The main results to date are reported here. Additional supplemental funding for one year (8/1/2019 – 7/31/2020) supported numerical investigation of photoionization processes important in many low temperature plasmas, including the HelCat device. Initial results of this modeling work is also reported.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Kinetic simulations of ignited mode cesium vapor thermionic converters

Cesium vapor thermionic converters are an attractive method of converting high-temperature heat directly to electricity, but theoretical descriptions of the systems have been difficult due to the multi-step ionization of Cs through inelastic electron–neutral collisions. This work presents particle-in-cell simulations of these converters, using a direct simulation Monte Carlo collision model to track 52 excited states of Cs. Here, these simulations show the dominant role of multi-step ionization, which also varies significantly based on both the applied voltage bias and pressure. The electron energy distribution functions are shown to be highly non-Maxwellian in the cases analyzed here. A comparison with previous approaches is presented, and large differences are found in ionization rates due especially to the fact that previous approaches have assumed Maxwellian electron distributions. Finally, an open question regarding the nature of the plasma sheaths in the obstructed regime is discussed. The one-dimensional simulations did not produce stable obstructed regime operation and thereby do not support the double-sheath hypothesis.

30 DIRECT ENERGY CONVERSION↗

Vertical instability forecasting and controllability assessment of multi-device tokamak plasmas in DECAF with data-driven optimization

Abstract Reliable vertical position control will be an essential element of any future tokamak-based fusion power plant in order to reduce disruptions and maximize performance. We investigate methods to improve vertical controllability boundary determination in plasma operational space and demonstrate a data-driven approach based on direct pseudoinversion of operational space data that is rigorously quantitative, applicable in real-time plasma control systems, and physically intuitive to interpret. Applied to historical shot data from entire run campaigns on the MAST-U, KSTAR, and NSTX tokamaks, this approach, implemented in DECAF, improves vertical displacement event identification accuracy to 98.9%–100%. Further, we explore the application of a physics-based vertical stability metric as an early warning forecaster for vertical displacement events. The development of a linear surrogate model for the plasma current density profile, with a coefficient of determination of 0.992 on the training dataset, enables potential employment of this forecaster in real-time. The application of this approach on historical data from the MAST-U MU02 campaign yields a forecaster with 62.6% accuracy, indicating promise for this method when further refined and potentially coupled with other stability metrics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Materials Plasma Exposure eXperiment: Status of the Physics Basis Together With the Conceptual Design and Plans Forward

The Materials Plasma Exposure eXperiment (MPEX) is a linear plasma device that will address the plasma–material interaction (PMI) science for future fusion reactors and will enable testing of plasma-facing components (PFCs). It is designed as a steady-state device eventually delivering an ion fluence of up to 10 31 m -2 to the target. The device will be designed to handle neutron-activated materials. These capabilities should push the technical readiness level of PFCs up to six for some end-of-life aspects. In order to achieve the relevant plasma conditions, as they are expected in future fusion reactor divertors, MPEX will utilize a novel plasma source concept. This plasma source concept uses a high-power helicon (200 kW, 13.56 MHz), an electron cyclotron heating (ECH) system, which will heat electrons via electron Bernstein wave (EBW) heating (about 400 kW, 70 GHz), and an ion cyclotron heating (ICH) system (400 kW, 6–9 MHz). The physics basis for this plasma source concept including the heating physics and transport is based on experiments on Proto-MPEX. An overview of the experimental results and the physics basis will be given. The physics basis directly translates into functional requirements of MPEX and the conceptual design. The status of the conceptual design of MPEX will be shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Application of machine learning for optical emission spectroscopy data in NAGDIS-II

In this study, we applied machine learning to optical emission spectroscopy (OES) data and device parameters from the linear plasma device NAGDIS-II to explore the potential application of machine learning for predicting electron density, $n$ e , and temperature, $T$ e . The covered ranges of $n$ e and $T$ e , which were measured by an electrostatic probe, are 3.6 × 10 17 –2.4 × 10 19 m -3 and 0.3–7.1 eV, respectively. A three hidden layer neural network (NN) is introduced to model the relationship between $n$ e /$T$ e and the combination of line intensities, radial position, and device parameters. It is shown that the errors in $n$ e and $T$ e become 18.0 and 18.8%, respectively, which were almost the same level for the electrostatic probe, using all available data. Lasso regression and greedy algorithm are used to select the necessary line emissions. In conclusion, it is shown that four- or five-line intensities are sufficient to obtain almost the same quality as the one with all the other lines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Impurity transport in PISCES-RF

Linear plasma devices (LPD) utilizing a helicon plasma source, a high density light ion source, can generate impurities due to progressive erosion of the radio frequency (RF) transmission window caused by rectified sheath voltage. These source-born impurities can entrain and be transported by the plasma toward a target, affecting plasma-material interaction studies. Earlier work on material testing in Prototype-Materials Plasma Exposure eXperiment at ORNL revealed significant source impurity deposition on downstream targets. However, using a similar RF source, no target impurity deposition is observed in Plasma Interaction Surface Component Experimental Station (PISCES)-RF despite evidence of RF window erosion in the source region, thereby motivating the present work. Experimentally, using various magnetic field configurations upstream of the PISCES-RF plasma source and seeding titanium (Ti) impurities at various axial locations, impurity transport and deposition along the machine axis were investigated. It was found that Ti deposition was localized to the side of the plasma source where the Ti impurity was seeded. In contrast, aluminum (Al) deposition, originating from the sputtering of the helicon window, occurred predominantly upstream of the plasma source, suggesting an asymmetry in the axial transport of eroded RF window material. These observations suggest a stagnation of the parallel plasma flow immediately downstream of the plasma source, with impurity ions remaining unmagnetized near the source upstream. Al deposition in magnetic field-free regions in PISCES-RF indicates that sputtered Al impurities likely remained neutral due to their large ionization mean-free path under PISCES-RF conditions. Plasma modeling and simulation supported this, indicating that Al-neutrals transport toward the helicon source upstream for low electron density cases. It was found that the Larmor radius of the Al ions was greater than the plasma radius towards the source upstream and remained weakly magnetized in PISCES-RF, meaning that plasma source-born impurities are not efficiently entrained in the plasma flow. These findings provide critical insights into impurity transport in helicon plasma-based LPDs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physical and technical basis of Materials Plasma Exposure eXperiment from modeling and Proto-MPEX results *

Abstract The Materials Plasma Exposure eXperiment (MPEX) is a steady-state linear plasma device that will address plasma-material interaction (PMI) science and enable testing of fusion reactor-relevant divertor plasma-facing materials. The MPEX source concept consists of a helicon plasma source to generate the plasma, electron cyclotron heating (ECH) for electron heating, and ion cyclotron heating (ICH) for ion heating. The MPEX source plasma is then transported axially to the PMI material target region to test material samples in fusion reactor-relevant divertor conditions. This paper will summarize the physical and technical basis of MPEX. The paper will first define the MPEX parameters and scenarios at the target relevant to PMI science for various fusion reactor-relevant divertor conditions and show plasma transport modeling results to set the MPEX source parameters. Recent experimental and modeling results from Proto-MPEX, a short-pulse experiment to develop the plasma production, heating, and transport physics for MPEX, will be shown. From these results, it will be shown that MPEX can reach its desired scenarios. The MPEX physical and technical basis will also determine important functional requirements for magnetic field, radiofrequency (RF) power, RF frequency, and neutral pressure in the helicon, ECH, ICH, and PMI regions that are required to achieve the desired MPEX scenarios. The necessity for key in-vessel components such as skimmers, limiters, and microwave absorbers will also be highlighted.

Lau, C. (ORCID:0000000285765867)↗

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↗

Superconducting Magnet Qualification Methodology for the Material Plasma Exposure Experiment

The Material Plasma Exposure eXperiment (MPEX), currently under design, is a new linear plasma device to advance the understanding of plasma-material interactions through the generation and delivery of plasmas as they are expected in future fusion reactor divertors. MPEX will be a steady-state device to study high-fluence exposures of plasma-facing materials and components. The requirements for the magnetic field at the target and the heating stages make the application of superconducting coils necessary. Conceptual designs for the superconducting magnets have been developed, and multiple cryostats with warm bore diameters of either 65 cm or 156 cm are envisioned to facilitate their integrated and timely assembly with other systems such as vacuum, water cooling, and RF power. Although design, fabrication, and testing for the magnets as stand-alone units are straightforward, challenges will arise during the integration of the system. Two different field profiles will be used during operation. The magnetic field where the electron cyclotron heating occurs needs to operate at both 1.25 and 2.5 T. It is critical that the magnets all share the same magnetic axis and alignment. The mutual inductance between cryostats will affect the quench behavior of the system. Also, cryostat-to-cryostat forces can be as large as 700 kN, and the magnitude and direction will change depending on which coils are energized. The design of the system must take those characteristics into account along with the quench scenarios. This paper describes the qualification approach that will be used to determine whether stand-alone tests can be used to ensure the success of the integrated system. Fiducials will be used to define the location of the magnetic axis for each cryostat to ensure proper alignment. Quench tests of a single magnet will be performed at a current above the normal operating current to account for additional stored energy from the mutual inductance to adjacent cryostats. Also, a 1018 steel plate will be mounted on either end of a cryostat to simulate the cryostat-to-cryostat forces. Requirements for the size and location of the steel plates are described.

Burkhardt, Earle↗

Final Design and Analysis of the Superconducting Magnets for the Material Plasma Exposure Experiment

The Material Plasma Exposure eXperiment (MPEX), which has completed its final design, is a new linear plasma device to advance the understanding of plasma-material interactions through the generation and delivery of plasmas as they are expected in future fusion reactor divertors. MPEX will be a steady-state device to study high-fluence exposures of plasma-facing materials and components. The requirements for the magnetic field at the heating stages and the target make the application of superconducting coils necessary. The final designs for the superconducting magnets have been developed using three cryostat designs with warm bore diameters of 65 cm and 156 cm. The large bores are required to for other systems such as vacuum, water cooling, and RF power. There are 19 superconducting coils in MPEX that are contained in six cryostats. Although design, fabrication, and testing for the magnets as stand-alone units are straightforward, challenges will arise during the integration of the system. Various field profiles will be used during operation. The magnetic field where the electron cyclotron heating occurs needs to operate at both 1.25 and 2.50 T. Analyses that have been performed on the final design include designing the coils and determining operating currents to meet field requirements, forces between cryostats, the effects of coil and/or cryostat movement, and quench analysis. To ensure that the magnetic field requirements are met, a plan for monitoring the magnetic field at specified locations has been developed which includes the effect of coil and/or cryostat movement.

Burkhardt, Earle↗

RF sheath induced sputtering on Proto-MPEX part 2: Impurity transport modeling and experimental comparison

The Prototype Material Plasma Exposure eXperiment (Proto-MPEX) is a pulsed linear plasma device that uses a radio frequency (RF) helicon antenna and a helicon ceramic window as the plasma ionization source. Modeling performed within this work on the helicon operations predicts hot spots on the helicon ceramic window due to an RF-induced sheath. The RF sheath potential leads to physical sputtering of the ceramic window predominantly where the helicon antenna sits around the helicon window. The role of oxygen in sputtering within Proto-MPEX is also investigated and is needed to match the experimental data. Experiments on Proto-MPEX show reasonable agreement with the modeled erosion/redeposition pattern on the helicon window, and the modeled impurity flux to the target shows radial transport within the device as expected from classical collisional impurity transport. Temperature screening of impurities is shown to be needed for Proto-MPEX to reduce impurity flux to the target. The modeling approach used in this work can be applied to other plasma RF applications for the determination of impurity production and transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗