A Data-Assimilation Based Method for Equilibrium Reconstruction of Magnetic Fusion Plasma and its Application to Reversed Field Pinch

Sanpei, Akio; Okamoto, Takayuki; Masamune, S.; Kuroe, Yasuaki

doi:10.1109/access.2021.3081146

Cited by 7 publications

(1 citation statement)

References 47 publications

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“…Recently the methods and practices developed have been employed in diverse areas of geosciences, with Carrassi et al (2018); Vetra-Carvalho et al (2018) providing recent overviews. Further DA has seen a huge expansion into other scientific disciplines with applications in, for example, robotics (Berquin and Zell, 2022), economic modelling (Nadler et al, 2019) and plasma physics (Sanpei et al, 2021). In the era of digital twinning, which involves combining high-fidelity representations of reality with the optimal use of observations, real time data has become vital and DA frameworks have naturally been incorporated.The area of data learning has also emerged where DA approaches are integrated with machine learning techniques (Buizza et al, 2022).…”

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confidence: 99%

ParticleDA.jl v.1.0: A real-time data assimilation software platform

Giles

Graham

Giordano

et al. 2023

Preprint

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Abstract. Digital twins of physical and human systems informed by real-time data, are becoming ubiquitous across weather forecasting, disaster preparedness, and urban planning, but researchers lack the tools to run these models effectively and efficiently, limiting progress. One of the current challenges is to assimilate observations in highly nonlinear dynamical systems, as the practical need is often to detect abrupt changes. We developed a software platform to improve the use of real-time data in highly nonlinear system representations where non-Gaussianity prevents the use of more standard Data Assimilation. Optimal Particle filtering data assimilation (DA) techniques have been implemented within an user-friendly open source software platform in Julia – ParticleDA.jl. To ensure the applicability of the developed platform in realistic scenarios, emphasis has been placed on numerical efficiency, scalability and optimisation for high performance computing frameworks. Furthermore, the platform has been developed to be forward model agnostic, ensuring that it is applicable to a wide range of modelling settings, for instance unstructured and non-uniform meshes in the spatial domain or even state spaces that are not spatially organised. Applications to tsunami and numerical weather prediction demonstrate the computational benefits in terms of lower errors, lower computational costs (due to ensemble size and the algorithm's overheads being minimised) and versatility thanks to flexible I/O in a high level language Julia.

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mentioning

confidence: 99%

ParticleDA.jl v.1.0: A real-time data assimilation software platform

Giles

Graham

Giordano

et al. 2023

Preprint

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Multiple-pinhole camera for monitoring three-dimensional plasma shape

INAGAKI¹,

Sanpei²,

Himura³

2022

Nuclear Instruments and Methods in Physics Research Section A:

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Equilibrium reconstruction of axisymmetric plasmas by combining Gaussian process regression and Markov chain Monte Carlo sampling

Nishizawa,

Tokuda,

Sanpei

et al. 2024

Plasma Phys. Control. Fusion

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Reliable equilibrium reconstruction is indispensable for understanding and controlling hot magnetized plasmas to achieve fusion reactors. In axisymmetric systems, current and pressure profiles that satisfy the force balance conditions are given by the Grad-Shafranov (GS) equation. While many novel approaches have been developed to swiftly and robustly find an optimum solution of the GS equation, approaches based on a single solution search may not be adaptable if diagnostics fail to provide sufficient constraints. Here, we investigate the solution space of the GS equation when only basic edge magnetic measurements are available. By combining Gaussian process regression and Markov chain Monte Carlo sampling within the Bayesian framework, we treat each current element as an independent variable and evaluate the probability distribution that describes all possible solutions. We have applied this inference frame to the geometry of the PLATO tokamak and shown that the flux surface locations can be determined relatively well only from 16 pick-up coils, 4 flux loops and a diamagnetic loop. On the other hand, the toroidal current density is inferred with limited success, and the inferences of the safety factor and pressure profiles are difficult. The characterization of possible choices of equilibria realized by this inference frame will help optimize diagnostic setups for equilibrium reconstruction.

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A Data-Assimilation Based Method for Equilibrium Reconstruction of Magnetic Fusion Plasma and its Application to Reversed Field Pinch

Cited by 7 publications

References 47 publications

ParticleDA.jl v.1.0: A real-time data assimilation software platform

ParticleDA.jl v.1.0: A real-time data assimilation software platform

Multiple-pinhole camera for monitoring three-dimensional plasma shape

Equilibrium reconstruction of axisymmetric plasmas by combining Gaussian process regression and Markov chain Monte Carlo sampling

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