Gaussian process tomography for soft x-ray spectroscopy at WEST without equilibrium information

International audienceGaussian process tomography (GPT) is a recently developed tomography method based on the Bayesian probability theory [J. Svensson, JET Internal Report EFDA-JET-PR(11)24, 2011 and Li et al., Rev. Sci. Instrum. 84, 083506 (2013)]. By modeling the soft X-ray (SXR) emissivity field in a poloidal cross section as a Gaussian process, the Bayesian SXR tomography can be carried out in a robust and extremely fast way. Owing to the short execution time of the algorithm, GPT is an important candidate for providing real-time reconstructions with a view to impurity transport and fast magnetohydrodynamic control. In addition, the Bayesian formalism allows quantifying uncertainty on the inferred parameters. In this paper, the GPT technique is validated using a synthetic data set expected from the WEST tokamak, and the results are shown of its application to the reconstruction of SXR emissivity profiles measured on Tore Supra. The method is compared with the standard algorithm based on minimization of the Fisher information

Mesoscale numerical simulations of heavy nocturnal rainbands associated with coastal fronts in the Mediterranean Basin

Three offshore rainbands associated with nocturnal coastal fronts formed near the Israeli coastline, the Gulf of Genoa and on the northeastern coast of the Iberian Peninsula, are simulated using version 3.3 of the WRF-ARW mesoscale model in order to study the dynamics of the atmosphere in each case. <br><br> The simulations show coastal fronts producing relatively high (in comparison with some other similar rainbands) 1 and 10 h accumulated precipitations that formed in the Mediterranean Basin. According to these simulations, the coastal fronts that formed near the Israeli coastline and over the Gulf of Genoa are quasi-stationary, while the one that formed on the northeastern coast of the Iberian Peninsula moves away from the coast. For the three events, we evaluate and intercompare some parameters related to convective triggering, deceleration induced by the cold pool in the upstream flow, and the blockage that the cold coastal front offers to the warmer maritime air mass

Incorporating magnetic equilibrium information in Gaussian process tomography for soft X-ray spectroscopy at WEST

Paper published as part of the Proceedings of the 22nd Topical Conference on High-Temperature Plasma Diagnostics, San Diego, California, April 2018International audienceGaussian process tomography (GPT) [J. Svensson, JET Internal Report EFDA-JET-PR(11)24, 2011 and D. Li, J. Svensson, H. Thomsen, F. Medina, A. Werner, and R. Wolf, Rev. Sci. Instrum. 84, 083506 (2013)] is a recently developed tomography method applied earlier to soft X-ray (SXR) spectroscopy on WEST---Tungsten (W) Environment in Steady-state Tokamak. The short execution time of the algorithm makes GPT an important candidate for providing real-time information on impurity transport and for fast MHD control. In earlier work, GPT has shown its flexibility by providing good reconstruction results without background information about the magnetic equilibrium. On the other hand, information about the magnetic flux surface geometry can in general be useful for additional regularization of the solution. In this paper, we develop a way to take into account the equilibrium information, by constructing a covariance matrix of the prior Gaussian process depending on the flux surface geometry. The GPT method is validated using synthetic SXR emissivity profiles relevant to WEST plasmas and compares favorably with the classical algorithm based on minimization of the Fisher information

Comparison of two regularization methods for Soft x-ray tomography at Tore Supra

International audienceSoft x-ray (SXR) emission in the range 0.1-20 keV is widely used to obtain valuable information on tokamak plasma physics, such as particle transport, magnetic configuration or magnetohydrodynamic activity. In particular, 2D tomography is the usual plasma diagnostic to access the local SXR emissivity. The tomographic inversion is traditionally performed from lineintegrated measurements of two or more cameras viewing the plasma in a poloidal cross-section, like at Tore Supra (TS). Unfortunately, due to the limited number of measured projections and presence of noise, the tomographic reconstruction of SXR emissivity is a mathematical ill-posed problem. Thus, obtaining reliable results of the tomographic inversion is a very challenging task. In order to perform the reconstruction, inversion algorithms implemented in present tokamaks use a priori information as additional constraints imposed on the plasma SXR emissivity. Among several potential inversion methods, some of them have been identified as well suited to tokamak plasmas. The purpose of this work is to compare two promising inversion methods, i.e. the minimum fisher information method already used at TS and planned for WEST configuration, and the alternative 2nd order Phillips-Tikhonov regularization with smoothness constraints imposed on the second derivative norm. Respective accuracy of both reconstruction methods as well as overall robustness and computational time are studied, using several synthetic SXR emissivity profiles. Finally, a real case is studied through tomographic reconstruction from TS SXR database

Polycapillary optics for soft X-ray imaging and tomography

Magnetic plasmas are extended volumetric sources of X-rays, and these emissions could reveal a lot of information about the processes occurring into the plasmas. Unfortunately, the constraints posed by these toroidal devices (high neutron flux, gamma and hard-X background, extremely high radiofrequency powers, high magnetic fields, optical limitations and so on) are very severe and limit strongly the possibility to install X-ray detectors directly into or close to the machine. Soft X-ray diagnostics are meant both as tomography and imaging. We started, therefore, to investigate the feasibility of using polycapillary optics for these purposes, in collaboration between Istituto Nazionale di Fisica Nucleare (INFN)- Frascati, Ente per le Nuove tecnologie, l’Energia e l’Ambiente (ENEA)-Frascati and the Commissariat de l’Energie Atomique (CEA)-Cadarache. The first tests were performed in order to characterize the polycapillary lenses (convergence, divergence, efficiency, spectral dispersion, etc.) for distances much larger than the optical focal length of the lenses, both for the detector and for the source. A silicon-based C-MOS imager (Medipix 2) has been used as a detector and the micro focus X-ray tubes as point-like sources. Results of these preliminary tests are presented, and the imaging capabilities of a polycapillary lens as well

A new class of indicators for the model selection of scaling laws in nuclear fusion

The development of computationally efficient model selection strategies represents an important problem facing the analysis of Nuclear Fusion experimental data, in particular in the field of scaling laws for the extrapolation to future machines, and image processing. In this paper, a new model selection indicator, named Model Falsification Criterion (MFC), will be presented and applied to the problem of choosing the most generalizable scaling laws for the power threshold to access the H-mode of confinement in Tokamaks. The proposed indicator is based on the properties of the model residuals, their entropy and an implementation of the data falsification principle. The model selection ability of the proposed criterion will be demonstrated in comparison with the most widely used frequentist (Akaike Information Criterion) and bayesian (Bayesian Information Criterion) indicators.Comment: 4 pages, 2 figure