CaNS-Fizzy: A GPU-accelerated finite difference solver for turbulent two-phase flows

TL;DR

CaNS-Fizzy is a GPU-accelerated solver enabling detailed direct numerical simulations of turbulent two-phase flows, providing comprehensive data for analyzing complex flow interactions relevant to various industrial processes.

Contribution

It introduces Fizzy, a GPU-accelerated two-phase flow solver built on CaNS, allowing high-resolution DNS of turbulent flows with detailed interface dynamics.

Findings

Enables high-fidelity simulations of turbulent two-phase flows.

Provides comprehensive datasets for flow mechanism analysis.

Facilitates design insights for heat and mass transfer applications.

Abstract

CaNS-Fizzy -- Fizzy for short -- is a GPU-accelerated numerical solver for massively-parallel Direct Numerical Simulations (DNS) of incompressible two-phase flows. A DNS enables direct access to all flow quantities, resolved in time and space at all relevant continuum scales. The resulting numerical experiments provide complete data sets for the analysis of the detailed mechanisms underlying the flow, particularly the interaction between the chaotic and multi-scale dynamics of turbulence and the interface movement and deformation. The insights gained can guide the design and operation of various applications, such as boiling heat transfer, liquid-liquid extraction, gas-liquid reactors, absorption and stripping columns, distillation columns, liquid combustion appliances, in all of which the rate of heat and mass transfer between phases is proportional to the interfacial area. Fizzy's two-phase capabilities were implemented using the efficient, GPU-accelerated Navier-Stokes solver CaNS as base.