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Fast-Ion Diagnostic Development for High-Energy Neutral Beam Injection on the Large Helical Device


Core Concepts
A new sightline geometry for the fast-ion D-alpha (FIDA) diagnostic on the Large Helical Device (LHD) has been successfully tested, demonstrating its ability to measure high-energy fast ions produced by negative-ion neutral beam injection.
Abstract
  • Bibliographic Information: Hayashi, W.H.J., Heidbrink, W.W., Muscatello, C.M., Lin, D.J., Osakabe, M., Ogawa, K., et al. "Charge-exchange measurements of high-energy fast ions in LHD using negative-ion neutral beam injection". arXiv preprint arXiv:2411.10597 (2024).
  • Research Objective: This study aims to validate a new sightline geometry for the FIDA diagnostic on the LHD, designed to measure high-energy fast ions generated by NNBI.
  • Methodology: The researchers conducted experiments on the LHD using a new FIDA sightline nearly tangential to a high-energy (166 keV) NNBI beamline. They compared the measured FIDA signals with synthetic signals generated by the FIDASIM code, using a fast-ion distribution function calculated by the GNET transport code. The study focused on MHD-quiescent plasmas for accurate comparison with the simulation.
  • Key Findings: The new sightline successfully measured Doppler-shifted FIDA emissions corresponding to fast ions with energies close to the injection energy of the NNBI. The FIDA signal peak for the new sightline was observed at a higher wavelength (662.2 nm) compared to the old sightline (661.8 nm), indicating sensitivity to higher energy fast ions. The shape of the measured FIDA spectrum agreed well with the FIDASIM predictions, validating the effectiveness of the new sightline. The study also confirmed the expected parametric dependencies of the FIDA signal, with signal strength increasing with diagnostic beam power and decreasing with plasma density.
  • Main Conclusions: The new FIDA sightline geometry, tangential to the NNBI beamline, effectively measures high-energy fast ions in LHD. This development is crucial for studying fast-ion behavior in future fusion devices that will rely on high-energy NNBI for heating and current drive.
  • Significance: This research significantly advances fast-ion diagnostic capabilities for fusion devices, particularly those utilizing high-energy NNBI. Accurate measurement of fast-ion distributions is essential for optimizing plasma heating, current drive, and overall performance in fusion experiments.
  • Limitations and Future Research: The study primarily focused on MHD-quiescent plasmas. Further research is needed to assess the diagnostic's performance in the presence of MHD instabilities, which are common in fusion plasmas. Additionally, investigating the impact of other factors like charge-exchange losses on the FIDA signal could improve the accuracy of fast-ion distribution measurements.
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Stats
The NNBI injection energy was 166 keV with a power of 1.5 MW. The PNBI injection energy was 56 keV with a power of 3.5 MW. The plasma had a central electron temperature of 5 keV. The plasma had a central ion temperature of 1.4 keV. The volume-averaged electron density was 0.8×10¹⁹ m⁻³. The plasma current was 5 kA. The FIDA peak for the high-energy view was observed at 662.2 nm, corresponding to an energy component of 81 keV along the sightline. The FIDA peak for the low-energy view was observed at 661.8 nm, corresponding to an energy component of 71 keV along the sightline.
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Deeper Inquiries

How will this new FIDA diagnostic design be incorporated into the design of future fusion devices that plan to utilize high-energy NNBI?

This new FIDA diagnostic design, utilizing a sightline nearly tangential to the high-energy NNBI, offers valuable insights for the development of future fusion devices: Optimization of Tangential Sightlines: Future devices can be designed or retrofitted with FIDA diagnostics incorporating tangential sightlines specifically aimed at the high-energy NNBI. This strategic placement maximizes the sensitivity to high-energy fast ions, which are crucial for efficient heating and current drive in fusion plasmas. Enhanced Energy Resolution: By minimizing the relative velocity between the injected neutrals and the fast ions, this design allows for improved energy resolution of the FIDA measurements. This is particularly important in future devices operating at higher beam energies, where accurate measurement of the fast-ion distribution function in the high-energy range is essential. Integration with Advanced Modeling: The validated FIDASIM simulations, incorporating realistic geometries and beam characteristics, can be used to guide the design and optimization of FIDA systems for future devices. This ensures that the diagnostic system is tailored to the specific plasma parameters and operating scenarios expected. Real-time Control Applications: The improved understanding of high-energy fast-ion behavior, facilitated by this diagnostic, can contribute to the development of real-time control algorithms for NNBI systems. This enables dynamic adjustment of beam parameters to maintain optimal plasma conditions and maximize fusion performance.

Could the discrepancy between the measured and simulated FIDA signal magnitudes be attributed to inaccuracies in the fast-ion distribution function calculated by the GNET code, rather than solely to experimental factors?

Yes, the discrepancy between the measured and simulated FIDA signal magnitudes could be partially attributed to inaccuracies in the fast-ion distribution function calculated by the GNET code. While the paper attributes the discrepancy to experimental factors like charge-exchange losses with cold neutrals, several factors could lead to inaccuracies in GNET's calculations: Simplified Physics Models: GNET, like all transport codes, relies on simplified physics models to make calculations computationally feasible. These simplifications might not fully capture the complexities of fast-ion behavior in the LHD, especially in the presence of instabilities. Steady-State Assumption: The GNET simulations were performed assuming steady-state conditions, while the experiment involved time-varying plasma parameters and potential instabilities. These dynamic effects could lead to deviations from the predicted fast-ion distribution. Input Parameter Uncertainties: The accuracy of GNET's calculations depends on the accuracy of the input parameters, such as plasma profiles and magnetic field configurations. Uncertainties in these parameters can propagate through the simulation and affect the predicted FIDA signal magnitude. Further investigation is needed to determine the relative contributions of experimental factors and GNET inaccuracies to the observed discrepancy. This could involve: Sensitivity Analysis: Performing simulations with varied input parameters to assess their impact on the predicted FIDA signal. Comparison with Other Diagnostics: Comparing the GNET-predicted fast-ion distribution with measurements from other fast-ion diagnostics on LHD, such as neutron detectors or collective Thomson scattering systems. Improved Modeling: Exploring more advanced transport codes or incorporating more realistic physics models into GNET to improve the accuracy of the fast-ion distribution function.

How might this research on fast-ion diagnostics in fusion plasmas contribute to advancements in other fields that rely on understanding and controlling high-energy particle beams, such as particle accelerators or medical treatments?

The research on fast-ion diagnostics in fusion plasmas, particularly the development of techniques like the tangential FIDA system, can significantly benefit other fields that utilize high-energy particle beams: Particle Accelerators: Beam Diagnostics and Optimization: The principles behind FIDA diagnostics can be adapted to develop non-invasive techniques for characterizing high-energy particle beams in accelerators. This includes measuring beam profiles, energy distributions, and even detecting minute beam instabilities. Understanding Beam-Plasma Interactions: The knowledge gained from studying fast-ion behavior in fusion plasmas can be applied to better understand and control beam-plasma interactions in accelerators. This is crucial for optimizing beam quality and mitigating unwanted effects like beam instabilities or plasma wakefield generation. Medical Treatments (e.g., Proton Therapy): Dose Monitoring and Verification: Adapting FIDA-like techniques could lead to real-time monitoring of the dose delivered during proton therapy. By analyzing the light emitted due to interactions between the proton beam and the patient's tissues, more precise and safer treatment delivery can be achieved. Treatment Planning and Optimization: The advanced modeling tools used in fusion research, such as FIDASIM, can be adapted to simulate the interaction of particle beams with biological tissues. This can lead to more accurate treatment planning and personalized optimization of radiation therapy. Overall, the advancements in fast-ion diagnostics driven by fusion research have the potential to significantly impact other fields by providing valuable tools for characterizing, controlling, and optimizing high-energy particle beams. This cross-fertilization of knowledge and technology can lead to breakthroughs in areas ranging from fundamental physics research to life-saving medical treatments.
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