Purpose
This paper aims to introduce a three-dimensional smoothed particle hydrodynamics (SPH) framework for simulating supercooled large droplets (SLD) dynamics at aeronautical speeds.
Design/methodology/approach
To include the effects of the surrounding air, a multiphase model capable of handling high density-ratio problems is adopted. A diffusive term is incorporated to smooth the density field and avoid numerical instabilities. Additionally, a particle shifting technique is used to eliminate anisotropic particle distributions.
Findings
The framework is validated against low-speed droplet impingement experimental results and then applied to the droplet impingement at high speeds typical of SLD conditions. Preliminary parametric studies are conducted to investigate the post-impact splashing. It is observed that a thicker water film can decrease the crown diameter and a smaller impact angle can suppress upward and forward splashing.
Originality/value
A three-dimensional multiphase SPH framework for SLD dynamics at a wide range of impact speed is developed and validated. The effects of particle resolution, water film thickness and impact angle on the post-impact crown evolution are investigated.
A numerical program based on the smoothed particle hydrodynamics (SPH) method has been developed to solve the nonlinear fluid-structure interaction problems. The numerical method simulates the breaking free-surface flows and evaluates hydrodynamic loads on structures. A kernel function was employed to interpolate the flow field and solve the Euler equations. The solid boundaries were modelled using a fixed ghost particle method. A particle shifting technique was adopted and improved to minimize the interpolation error caused by the non-uniform particle configuration on the free surface. Validation studies were carried out for three cases, including the dam-break flow impacting a vertical wall, water entry of a free-fall wedge and the sloshing flow in a rectangular container excited by roll motions. The numerical results were compared with the experimental data and other published numerical solutions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.