Multi-dimensional Optimal Order Detection

Utilising Computational Fluid Dynamics (CFD) revolutionises our understanding of compressible flows, offering insights crucial for the efficient design of products and processes destined for such environments.

However, navigating this complex realm requires careful selection of numerical schemes, equations, and frameworks, as each scenario presents unique challenges.

These challenges span across multi-physics, multi-scale continuum problems like inertial confinement fusion (ICF) and magnetic confinement fusion (MCF), holding the key to transformative breakthroughs and expediting our journey towards achieving net-zero emissions.

In this research, cutting-edge decision-making algorithms, including MOOD will be developed while harnessing AI techniques.

These innovations will be integrated into a high-order open-source CFD software tailored for ALE schemes and deployed in world-class Exascale High Performance Computing Facilities (HPC).