Towards a fusion power plant: integration of physics and technology

Morris, W.; Akers, R.; Cox, M.; Militello, F.; Surrey, E.; Waldon, C.; Wilson, H. R.; Zohm, H.

doi:10.1088/1361-6587/ac6694

Cited by 10 publications

(8 citation statements)

References 91 publications

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“…The computational cost of constructing 3D magnetohydrodynamic (MHD) equilibria is one major limiting factor in stellarator theory, experimentation and design. Depending on the desired resolution and accuracy of the solution, such computations require up to O (10) CPUh [1,2].…”

Section: Introductionmentioning

confidence: 99%

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Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

et al. 2023

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The computational cost of constructing 3D magnetohydrodynamic (MHD) equilibria is one of the limiting factors in stellarator research and design. Although data-driven approaches have been proposed to provide fast 3D MHD equilibria, the accuracy with which equilibrium properties are reconstructed is unknown. In this work, we describe an artificial neural network (NN) that quickly approximates the ideal-MHD solution operator in Wendelstein 7-X (W7-X) configurations. This model fulfils equilibrium symmetries by construction. The MHD force residual regularizes the solution of the NN to satisfy the ideal-MHD equations. The model predicts the equilibrium solution with high accuracy, and it faithfully reconstructs global equilibrium quantities and proxy functions used in stellarator optimization. We also optimize W7-X magnetic configurations, where desiderable configurations can be found in terms of fast particle confinement. This work demonstrates with which accuracy NN models can approximate the 3D ideal-MHD solution operator and reconstruct equilibrium properties of interest, and it suggests how they might be used to optimize stellarator magnetic configurations.

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Section: Introductionmentioning

confidence: 99%

“…Experimental time is limited, and priorities must be established to fit financial and human resources. Flight simulators provide a parallel and cheaper path to explore and exploit current and future experiments [9,10]. In a stellarator, 3D MHD equilibria bound the accuracy and cost of simulation.…”

Section: Introductionmentioning

confidence: 99%

Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

et al. 2023

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“…Nowadays, the interest of the scientifc community involved in the study of the laser-driven nuclear reactions is growing because of the possible multidisciplinary applications. Although the fusion reaction between tritium and deuterium is still considered the most interesting among other fusion reactions considered for power generation [1], the one between hydrogen and 11 B nucleus, called proton-boron nuclear fusion reaction (p 11 B) [2], represents a complementary and potentially alternative solution in future advanced schemes. In fact the possibility to generate three alpha particles per single reaction, with a negligible generation of neutrons, makes this type of reaction of interest in many felds of research (for a futuristic nuclear plant [3], in space applications [4], in cancer treatment [5,6], in radioisotope production [7], or in material science).…”

Section: Introductionmentioning

confidence: 99%

A Methodology for the Discrimination of Alpha Particles from Other Ions in Laser-Driven Proton-Boron Reactions Using CR-39 Detectors Coupled in a Thomson Parabola Spectrometer

et al. 2023

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Solid-state nuclear track detectors (CR-39 type) are frequently used for the detection of ions accelerated by laser-plasma interaction because they are sensitive to each single particle. To the present day, CR-39 detectors are the main diagnostics in experiments focused on laser-driven proton-boron (p11B) fusion reactions to detect alpha particles, which are the main products of such a nuclear reaction, and to reconstruct their energy distribution. However, the acceleration of multispecies ions in the laser-generated plasma makes this spectroscopic method complex and often does not allow to unambiguously discriminate the alpha particles generated from p11B fusion events from the laser-driven ions. In this experimental work, performed at the PALS laser facility (600 J, 300 ps, laser intensity 1016 W/cm2), CR-39 detectors were used as main detectors for the angular distribution of the produced alpha particles during a p11B fusion dedicated experimental campaign. Additionally, a CR-39 detector was set inside a Thomson Parabola (TP) spectrometer with the aim to calibrate the CR-39 response for low energetic laser-driven ions originating from the plasma in the given experimental conditions. The detected ion energies were ranging from hundreds of keV to a few MeV, and the ion track diameters were measured for etching times up to 9 hours. The goal of the test was the evaluation of the detectors’ ability to discriminate the alpha particles from the aforementioned ions. Within this study, the calibration curves for protons and silicon low energy ions are accomplished, the overlapping of the proton tracks and alpha particles is verified, and a methodology to avoid this problem is realized.

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“…Finally, inserting equations ( 5), ( 6) and (10) to (12) in equation (1), the covariant form of the MHD force residual is given by:…”

Section: The Ideal-mhd Force Balancementioning

confidence: 99%

Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

Merlo¹,

Böckenhoff²,

Schilling³

et al. 2022

Preprint

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The stellarator is a promising concept to produce energy from nuclear fusion by magnetically confining a high-pressure plasma. In a stellarator, the confining field is three-dimensional, and the computational cost of solving the 3D magnetohydrodynamic (MHD) equations currently limits stellarator research and design. Although data-driven approaches have been proposed to provide fast 3D MHD equilibria, the accuracy with which equilibrium properties are reconstructed is unknown. In this work, we describe an artificial neural network (NN) that quickly approximates the ideal-MHD solution operator in Wendelstein 7-X (W7-X) configurations. This model fulfils equilibrium symmetries by construction. The MHD force residual regularizes the solution of the NN to satisfy the ideal-MHD equations. The model predicts the equilibrium solution with high accuracy, and it faithfully reconstructs global equilibrium quantities and proxy functions used in stellarator optimization. The regularization term enforces that the NN reduces the ideal-MHD force residual, and solutions that are better than ground truth equilibria can be obtained at inference time. We also optimize W7-X magnetic configurations, where desiderable configurations can be found in terms of fast particle confinement. This work demonstrates with which accuracy NN models can approximate the 3D ideal-MHD solution operator and reconstruct equilibrium properties of interest, and it suggests how they might be used to optimize stellarator magnetic configurations.

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Towards a fusion power plant: integration of physics and technology

Cited by 10 publications

References 91 publications

Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

A Methodology for the Discrimination of Alpha Particles from Other Ions in Laser-Driven Proton-Boron Reactions Using CR-39 Detectors Coupled in a Thomson Parabola Spectrometer

Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

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