A Review of the Accuracy of Direct Numerical Simulation Tools for the Simulation of Non-Spherical Bubble Collapses

TL;DR

This paper reviews the accuracy of direct numerical simulation tools for non-spherical bubble collapse, providing a theoretical analysis that generalizes existing models and identifies key parameters influencing simulation precision.

Contribution

It introduces a new theoretical framework for assessing numerical errors in non-spherical bubble collapse simulations, emphasizing the ratio of grid size to minimum radius.

Findings

The grid size to minimum radius ratio scales numerical errors.

A generalized theory predicts peak pressures during bubble collapse.

Simulation accuracy depends on specific initial conditions.

Abstract

Numerical methods for the simulation of cavitation processes have been developed for more than 50 years. The rich variety of physical phenomena triggered by the collapse of a bubble has several applications in medicine and environmental science but requires the development of sophisticated numerical methods able to capture the presence of sharp interfaces between fluids and solid/elastic materials, the generation of shock waves and the development of non-spherical modes. One important challenge faced by numerical methods is the important temporal and scale separation inherent to the process of bubble collapse, where many effects become predominant during very short time lapses around the instant of minimum radius when the simulations are hardly resolved. In this manuscript, we provide a detailed discussion of the parameters controlling the accuracy of direct numerical simulation in general non-spherical cases, where a new theoretical analysis is presented to generalize existing theories on the prediction of the peak pressures reached inside the bubble during the bubble collapse. We show that the ratio between the gridsize and the minimum radius allows us to scale the numerical errors introduced by the numerical method in the estimation of different relevant quantities for a variety of initial conditions.