We present the latest developments of our High-Order Spectral Element Solver (Image 1),
an open source high-order discontinuous Galerkin framework, capable of solving a variety of …

We present a machine learning-based mesh refinement technique for steady and unsteady
incompressible flows. The clustering technique proposed by Otmani et al.(Phys Fluids 35 …

A diffused-interface approach based on the Allen-Cahn phase field equation is developed
within a high-order discontinuous Galerkin framework. The interface capturing technique is …

In this work we propose a very high-order compressible finite volume scheme with a
posteriori stabilization for the computation of multi-component two-phase flow with phase …

Reinforcement learning (RL) has emerged as a promising approach to automating decision
processes. This paper explores the application of RL techniques to optimise the polynomial …

In this paper, we introduce a data-driven filter to analyze the relationship between Implicit
Large-Eddy Simulations (ILES) and Direct Numerical Simulations (DNS) in the context of the …

The present work focuses on the generalisation of the Spectral Difference (SD) scheme to
the reduced Baer-Nunziato system known as five-equation model for the simulation of two …

This dissertation focuses on efficient and robust computation methods for multiphase flow
applications in the context of high–order (HO) methods. The flow modelling is done through …

Reinforcement learning (RL) has emerged as a promising approach to automating decision
processes. This paper explores the application of RL techniques to optimise the polynomial …