Related papers: Constructing a new predictive scaling formula for …
We introduce \textit{SeismoGPT}, a transformer-based model for forecasting three-component seismic waveforms in the context of future gravitational wave detectors like the Einstein Telescope. The model is trained in an autoregressive…
The transport of heat out of tokamak plasmas by turbulence is the dominant mechanism limiting the performance of fusion reactors. Turbulence can be driven by the ion temperature gradient (ITG) and suppressed by toroidal sheared flows.…
A two-field gyrofluid model including ion finite Larmor radius (FLR) corrections, magnetic fluctuations along the ambient field and electron inertia is used to study two-dimensional reconnection in a low $\beta_e$ collisionless plasma, in a…
Edge localised modes (ELMs) are a concern for future devices as they can limit the operational lifetime of the divertor. The mitigation of ELMs can be performed by the application of resonant magnetic perturbations (RMPs) which act to…
In this study, an implicit scheme for the gas-kinetic scheme (GKS) on the unstructured hybrid mesh is proposed. The Spalart-Allmaras (SA) one equation turbulence model is incorporated into the implicit gas-kinetic scheme (IGKS) to predict…
We derive finite-size scaling formulae for four-dimensional Higgs-Yukawa models near the Gaussian fixed point. These formulae will play an essential role in future, detailed investigation of such models. In particular, they can be used to…
A natural fueling mechanism that helps to maintain the main core deuterium and tritium (DT) density profiles in a tokamak fusion reactor is discussed. In H-mode plasmas dominated by ion- temperature gradient (ITG) driven turbulence, cold DT…
The transport of heat and particles in the relatively collisional edge regions of magnetically confined plasmas is a scientifically challenging and technologically important problem. Understanding and predicting this transport requires the…
Controlled fusion energy is deemed pivotal for the advancement of human civilization. In this study, we introduce $\textbf{LPI-LLM}$, a novel integration of Large Language Models (LLMs) with classical reservoir computing paradigms tailored…
In previous work we provided the explicit form of the nonlinear PDEs, subjected to the appropriate boundary conditions, which have to be satisfied by transport coefficients for systems out of Onsager's region. Since the proposed PDEs are…
New results from MAST are presented that focus on validating models in order to extrapolate to future devices. Measurements during start-up experiments have shown how the bulk ion temperature rise scales with the square of the reconnecting…
This study systematically explores the parameter space of disruption mitigation through shattered pellet injection in ITER with a focus on runaway electron dynamics, using the disruption modelling tool DREAM. The physics fidelity is…
Tokamak plasmas are confined by a magnetic field that limits the particle and heat transport perpendicular to the field. Parallel to the field the ionised particles can move freely, so to obtain confinement the field lines are "closed" (ie.…
Gaussian Process Regression-based Gaussian Approximation Potential has been used to develop machine-learned interatomic potentials having density-functional accuracy for free sodium clusters. The training data was generated from a large…
The paper is devoted to the Thomson scattering (TS) diagnostics recently developed for the Globus-M2 spherical tokamak and prototyping the ITER divertor TS diagnostics. The distinctive features of the system are the use of spectrometers,…
Deep learning is increasingly becoming a promising pathway to improving the accuracy of sub-grid scale (SGS) turbulence closure models for large eddy simulations (LES). We leverage the concept of differentiable turbulence, whereby an…
Most tokamak devices including ITER exploit the D-T reaction due to its high reactivity, but the wall loading caused by the associated 14MeV neutrons will limit the further development of fusion performance at high beta. To explore p-11B…
Conventional lattice Boltzmann models for the simulation of fluid dynamics are restricted by an error in the stress tensor that is negligible only for vanishing flow velocity and at a singular value of the temperature. To that end, we…
This paper introduces Eilmer, a general-purpose open-source compressible flow solver developed at the University of Queensland, designed to support research calculations in hypersonics and high-speed aerothermodynamics. Eilmer has a broad…
A data-driven model augmentation framework, referred to as Weakly-coupled Integrated Inference and Machine Learning (IIML), is presented to improve the predictive accuracy of physical models. In contrast to parameter calibration, this work…