| 1. |
- Barcellona, C., et al.
(författare)
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Tokamaks images advanced processing for diagnostics
- 2022
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Ingår i: IEEE International Symposium on Industrial Electronics. ; 2022-June, s. 612-614
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Konferensbidrag (refereegranskat)abstract
- In this work-in-progress paper, novel recent results obtained in the field of advanced image processing in nuclear fusion plants are reported. In particular, a strategy based on the reconstruction of the runaway electrons beam allows to infer plasma characteristic parameters which allows for an advanced real-time monitoring of the nuclear fusion experiment. Preliminary results obtained at the Frascati Tokamak Upgrade allow to assess the validity of the approach and pave the way for successive refinement of the diagnostics.
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| 2. |
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| 3. |
- Ekmark, Ida, 1998, et al.
(författare)
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Bayesian optimization of disruption scenarios with fluid-kinetic models
- 2023
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Ingår i: 49th EPS Conference on Plasma Physics, EPS 2023. - : European Physical Society (EPS).
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Konferensbidrag (refereegranskat)abstract
- Tokamak disruptions can damage the machine due to localized heat loads, mechanical stresses and impact of energetic runaway electron beams. We use a Bayesian optimization framework to optimize massive material injection of deuterium and neon in an ITER-like tokamak set up. The optimization is performed using both fluid and kinetic plasma models. The fluid model allows the exploration of a large parameter space. Once promising parameter regions are located, these are studied in higher physics fidelity using kinetic simulations. The kinetic model predicts more optimistic results regarding the success of the disruption mitigation.
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| 4. |
- Ekmark, I., et al.
(författare)
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Fluid and kinetic studies of tokamak disruptions using Bayesian optimization
- 2024
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Ingår i: Journal of Plasma Physics. - : Cambridge University Press (CUP). - 0022-3778 .- 1469-7807. ; 90:3
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Tidskriftsartikel (refereegranskat)abstract
- When simulating runaway electron dynamics in tokamak disruptions, fluid models with lower numerical cost are often preferred to more accurate kinetic models. The aim of this work is to compare fluid and kinetic simulations of a large variety of different disruption scenarios in ITER. We consider both non-activated and activated scenarios; for the latter, we derive and implement kinetic sources for the Compton scattering and tritium beta decay runaway electron generation mechanisms in our simulation tool Dream (Hoppe et al., Comput. Phys. Commun., vol. 268, 2021, 108098). To achieve a diverse set of disruption scenarios, Bayesian optimization is used to explore a range of massive material injection densities for deuterium and neon. The cost function is designed to distinguish between successful and unsuccessful disruption mitigation based on the runaway current, current quench time and transported fraction of the heat loss. In the non-activated scenarios, we find that fluid and kinetic disruption simulations can have significantly different runaway electron dynamics, due to an overestimation of the runaway seed by the fluid model. The primary cause of this is that the fluid hot-tail generation model neglects superthermal electron transport losses during the thermal quench. In the activated scenarios, the fluid and kinetic models give similar predictions, which can be explained by the significant influence of the activated sources on the runaway dynamics and the seed.
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| 5. |
- Embréus, Ola, 1991, et al.
(författare)
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Dynamics of positrons during relativistic electron runaway
- 2018
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Ingår i: Journal of Plasma Physics. - 0022-3778 .- 1469-7807. ; 84:5, s. 905840506-
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Tidskriftsartikel (refereegranskat)abstract
- Sufficiently strong electric fields in plasmas can accelerate charged particles to relativistic energies. In this paper we describe the dynamics of positrons accelerated in such electric fields, and calculate the fraction of created positrons that become runaway accelerated, along with the amount of radiation that they emit. We derive an analytical formula that shows the relative importance of the different positron production processes, and show that, above a certain threshold electric field, the pair production by photons is lower than that by collisions. We furthermore present analytical and numerical solutions to the positron kinetic equation; these are applied to calculate the fraction of positrons that become accelerated or thermalized, which enters into rate equations that describe the evolution of the density of the slow and fast positron populations. Finally, to indicate operational parameters required for positron detection during runaway in tokamak discharges, we give expressions for the parameter dependencies of detected annihilation radiation compared to bremsstrahlung detected at an angle perpendicular to the direction of runaway acceleration. Using the full leading-order pair-production cross-section, we demonstrate that previous related work has overestimated the collisional pair production by at least a factor of four.
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| 9. |
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| 10. |
- Hesslow, Linnea, 1993, et al.
(författare)
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Evaluation of the Dreicer runaway generation rate in the presence of high-impurities using a neural network
- 2019
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Ingår i: Journal of Plasma Physics. - 0022-3778 .- 1469-7807. ; 85:6
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Tidskriftsartikel (refereegranskat)abstract
- Integrated modelling of electron runaway requires computationally expensive kinetic models that are self-consistently coupled to the evolution of the background plasma parameters. The computational expense can be reduced by using parameterized runaway generation rates rather than solving the full kinetic problem. However, currently available generation rates neglect several important effects; in particular, they are not valid in the presence of partially ionized impurities. In this work, we construct a multilayer neural network for the Dreicer runaway generation rate which is trained on data obtained from kinetic simulations performed for a wide range of plasma parameters and impurities. The neural network accurately reproduces the Dreicer runaway generation rate obtained by the kinetic solver. By implementing it in a fluid runaway-electron modelling tool, we show that the improved generation rates lead to significant differences in the self-consistent runaway dynamics as compared to the results using the previously available formulas for the runaway generation rate. © Cambridge University Press 2019.
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