Symbolic regression (SR) is a machine learning-based regression method based on genetic
programming principles that integrates techniques and processes from heterogeneous …

This paper presents a brief review of grand challenges of Smoothed Particle Hydrodynamics
(SPH) method. As a meshless method, SPH can simulate a large range of applications from …

This paper aims at providing a state-of-the-art review on the applications of particle methods
in hydrodynamics-related problems in ocean and coastal engineering. The problems are …

This paper is dedicated to improved resolution of the continuity equation and thus more
precise satisfaction of incompressibility conditions in explicit weakly compressible SPH …

This paper presents a review of the progress of smoothed particle hydrodynamics (SPH)
towards high-order converged simulations. As a mesh-free Lagrangian method suitable for …

The smoothed particle hydrodynamics (SPH) method was employed to simulate the heat
transfer process in porous media at the pore scale. The effective thermal conductivity of a …

The proposed work describes a novel viscous term specifically conceived to reduce the
amount of acoustic pressure waves in weakly-compressible SPH models. The above …

Purpose This study aims to provide a comprehensive overview of the current state of the art
in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It …

Fluid-structure interaction (FSI) is a class of mechanics-related problems with mutual
dependence between the fluid and structure parts and it is observable nearly everywhere, in …

Since its inception, the full Lagrangian meshless smoothed particle hydrodynamics (SPH)
has experienced a tremendous enhancement in methodology and impacted a range of multi …