Identifying non-performing or dud plasmas for burning plasma control: insights from JET and TFTR deuterium–tritium campaigns
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Abstract Recent JET D–T campaigns opened the possibility of unique isotope studies to investigate the L–H transition physics in view of reactor plasmas and to study the origin of the observed power threshold minimum. In the present paper, we characterise L–H transitions in the low and high-density branches of JET NBI-heated D–T plasmas. As discussed in the paper, L–H transition has been hypothesised to be determined by the transport power losses of plasma ions, i.e. the so-called ion heat flux ( Q i ). We present the first power balance analysis of JET NBI-heated D–T plasmas to evaluate the ion heat flux at the transition. Due to the experimental setting being similar to previous JET D experiments, we also directly compare the results, discussing the isotope effect and similarities between datasets. First, we find an isotope effect between D and D–T Q i , with a lower Q i in D–T plasmas. We confirm that the ion heat flux deviates from density linearity compared to the linear trend observed in wave-heated D plasmas of other tokamaks. The deviation we observe in NBI-heated L–H transitions happens at an isotope-dependent density. Plasma edge rotation correlates with Q i deviation from density linearity in the low-density branch. However, further investigations would be required to assess the role of rotation on Q i and the power threshold minimum at JET. At low plasma density, NBI power dominates Q i , while increasing the density makes the equipartition power dominant. We finally compare our results with hypotheses proposed from evidence in other tokamaks to present a complete overview of ion heat flux analyses in D and D–T NBI-heated plasmas at JET.
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In DT cryogenic implosions, hot-spot x-ray self-emission is observed to begin at a larger shell radius than is predicted by a 1-D radiation-hydrodynamic implosion model. Laser-imprint is shown to explain the observation for a low-adiabat implosion. Furthermore, for more-stable implosions the data are not described by the imprint model and suggest there are additional sources of decompression of the dense fuel.
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This SRTE PDRD sponsored project produced test articles, tooling, and training articles for evaluation. In addition, the hydrogen compatibility of the alloys that can be readily produced by the Arcam A2X was tested. During the evaluation it was determined that the mechanical properties were more sensitive to build plate location than hydrogen exposure. Hydrogen pressure – volume-temperature experiments showed that the as-fabricated samples did not absorb hydrogen readily, but activated samples did.
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Stakeholder engagement, outreach, and collaboration has been extensive throughout all project phases. Numerous alternatives were considered, and included SME and regulator input and consultation. All aspects of this operation have been specifically designed to prioritize the protection of our workers, the public, and the environment. This project is a one-time effort to prepare four unique waste containers for permanent offsite disposal.
As a part of the U.S. Department of Energy (DOE), Los Alamos National Laboratory (LANL or Laboratory) must comply with regulations in the Clean Air Act (CAA) put forth in 40 Code of Federal Regulations (CFR) 61, Subpart H “National Emission Standards for Emissions of Radionuclides Other Than Radon from Department of Energy Facilities.” The standard states, “Emissions of radionuclides to the ambient air from Department of Energy facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent of 10 mrem/yr [millirem per year] [1].” This regulation is referred to as the National Emission Standards for Hazardous Air Pollutants for Radionuclides (Radionuclide NESHAP or Rad-NESHAP).
Objective of this work was to study the formation of Sn impurity and hydride phases in Zr and study their impacts on the diffusion kinetics of 3 H by using DFT based ML approach. By implementing deep neural potential (DNP) technique, we developed potential for Zr-H and Sn impurity systems and validated the DNP by using DFT results. We found that by implementing machine learning approach, it is possible to achieve accuracy comparable to DFT level for the more realistic models by using less computational time and resources.
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