The paper aims to provide a comprehensive review on the achievements made on moving
particle semi-implicit (MPS) method and the applications in nuclear engineering. The state …

The paper presents a concise review on latest advances related to development of entirely
Lagrangian meshfree computational methods for hydroelastic fluid-structure interactions …

In nuclear engineering, solid particles are associated with numerous processes, such as
solid–fluid flows in pebble bed reactors, coating during fuel fabrication, and debris bed …

Graph neural network (GNN) is a promising approach to learning and predicting physical
phenomena described in boundary value problems, such as partial differential equations …

The Lagrangian moving particle semi‐implicit (MPS) method has potential to simulate free‐
surface and multiphase flows. However, the chaotic distribution of particles can decrease …

In this paper, a novel SPH (Smoothed Particle Hydrodynamics)-based implicit structure
model as well as its refined coupled fully-Lagrangian meshfree FSI (Fluid-Structure …

In this study, a new quasi-Lagrangian particle method is developed aiming at accurate and
stable numerical simulation of complex free-surface flows. The main novelties of this …

In this paper, we propose a class of decoupled first-and second-derivatives models for the
Smoothed Particle Hydrodynamics (SPH) method, which were inspired by the Lagrangian …

In this paper, the partitioned MPS-FEM method is employed for two-dimensional and three-
dimensional free surface flow interacting with deformable structures. The discretization of …

In this work, the Moving Particle Semi-implicit (MPS) method is enhanced for multi-resolution
problems with different resolutions at different parts of the domain utilising a particle splitting …