Canadian Economics Association

We present a semi-Lagrangian method for the numerical resolution of Vlasov-type equations on multi-patch meshes. Following N. Crouseilles et al. [A parallel Vlasov solver based on local cubic spline interpolation on patches. Journal of Computational Physics (2009)], we employ a local cubic spline interpolation with Hermite boundary conditions between the patches. The derivative reconstruction is adapted to cope with non-uniform meshes as well as non-conforming situations. In the conforming case, the constraint of the number of points for each patch, found in previous studies, is removed; however, a small global system must now be solved. In that case, the local spline representations coincide with the corresponding global spline reconstruction. Alternatively, we can choose not to apply the global system and the derivatives can be approximated. The influence of the most distant points diminishes as the number of points per patch increases. For uniform per patch configurations, a study of the explicit and asymptotic behavior of this influence has been led. The method is validated using a two-dimensional guiding-center model with an O-point. All the numerical results are carried out in the Gyselalib++ library.

Recent findings on improved thermal plasma confinement in the presence of large-scale Alfvén Eigenmodes in tokamak plasmas have sparked a great interest in the complex physics at play, as it is relevant for next-generation fusion device optimization. These studies must be framed within the latest two decades of efforts in analyzing the various mechanisms through which the fast ions, i.e. ions with much larger energy than that of thermal ions, can interact with the background turbulence and, remarkably, reduce or even suppress the latter in magnetized plasmas. This contribution aims at reviewing the latest results about experimental and modeling observation of reduced outward ion heat flux triggered by the nonlinear and multi-scale interplay of fast-ion-driven modes and background turbulence, and framing it within the broad knowledge on the well-established fast-ion mechanisms reducing the tokamak plasma turbulence.

An extensive documentation of ICRF-enhanced plasma potentials has been conducted over two experimental campaigns on the WEST tokamak using reciprocating emissive probes magnetically connected to two ICRF antennas. The collected data spans a wide range of antenna electrical settings (coupled power, toroidal phasing, left–right power balance) and plasma parameters (density at the antenna limiter above and below the lower hybrid resonance, plasma current, minority fraction). By scanning the edge safety factor across multiple probe plunges, the magnetic connection between the probe and the antenna varied, enabling the construction of a 2D map of the plasma and floating potentials around an active ICRF antenna. This dataset will be used to validate RF simulation tools equipped with the sheath boundary condition and used to predict RF rectified potentials and ICRF-induced impurity sputtering in future machines. This paper presents the diagnostic and some initial measurements, while the rest will be reported elsewhere.

Machine learning algorithms are recognized as effective tools for addressing challenges in nuclear methodologies and instrumentation, particularly when obtaining experimental data or precise mathematical models is difficult. One notable challenge in fast neutron spectroscopy involves unfolding neutron spectra from solid-state detectors, where conventional deconvolution techniques often suffer from instability. This study uses the PHITS code to simulate the behavior of a CVD diamond detector subjected to various neutron spectra. The simulated data serve as input to a regression model aimed at reconstructing the original spectra. In particular, we investigate the impact of four different signal processing and feature extraction techniques-Fourier transform, nodal basis projection, wavelet decomposition and agglomerative clustering-based compression-on the performance of spectrum reconstruction. These transformations are applied as preprocessing steps, and the resulting features are then used to train a supervised regression model (linear or kernel ridge, depending on the method). Model performance is evaluated using the R2 metric against reference spectra from the IAEA Compendium database. The most effective approach is then applied to experimental data collected with a CVD diamond detector at the DANAIDES irradiation facility, part of the TOTEM platform in Cadarache. This final test, performed on 14 MeV and AmBe neutron sources, demonstrates the practical feasibility of the proposed methodology for real-world neutron spectrum reconstruction.

Octogen (HMX) is widely used in detonators, by itself or in a mixture, due to its powerful detonation (pressure and velocity) and high initiation energy, combining safety and performance. Its usage in an optical slapper detonator where energy is limited requires the accurate identification of the critical initiation conditions. A tabletop system was used to generate laser-driven flyers from multi-layered metallic coatings deposited on a glass substrate. The impact velocities corresponding to the initiation thresholds were measured using photon Doppler velocimetry (PDV). Different flyer geometries were considered as they affect the critical initiation conditions, with diameters of 0.5 mm, 0.7 mm, and 1 mm, and thicknesses ranging from 4 to 40 mu m. An analytical initiation criterion, selected after its comparison to several others, was combined with a numerical laser-matter interaction model to serve as both a predictive model and a guide for future laser energy threshold identification. This combination allowed the determination of the critical laser energy input for a wider range of flyer thicknesses, and also the identification of the best configuration to minimize the required energy.