Direct Numerical Simulations and Robust Predictions of Cloud Cavitation Collapse

PI Name: 
Petros Koumoutsakos
PI Email:
ETH Zürich
Allocation Program: 
Allocation Hours at ALCF: 
88 Million
Research Domain: 

Cloud cavitation collapse is detrimental to the lifetime of high-pressure injection engines as well as instrumental to kidney lithotripsy and ultrasonic drug delivery. Despite its importance, we have limited understanding of its governing mechanisms so as to design informed strategies for preventing and controlling it.

The study of cloud cavitation collapse presents a formidable challenge to experimental and computational studies owing to its geometric complexity and the wide range of its characteristic spatiotemporal scales. Its simulation requires two-phase flow solvers capable of capturing interactions between multiple deforming bubbles, pressure waves, formation of shocks, and their interaction with boundaries and turbulent vortical flows

The goal of this project is to perform simulations that capture the collapse of more than 50,000 bubbles interacting with a turbulent flow field at unprecedented resolution and performance. Direct numerical simulations will provide databases for turbulent cavitation bubble clouds that can be used to extract relevant models for large eddy simulations. Moreover, the researchers will perform multilevel uncertainty quantification (UQ) on quantities of using the nonintrusive multi-level Monte Carlo method coupled with the present finite volume solver. The UQ studies will enable robust predictions for uncertainties in input parameters that will assist the development of engineering models. The researchers envision that the proposed simulations will drastically improve understanding of cloud cavitation collapse in turbulent flows and will revolutionize the development of engineering models for the prediction of the cavitation damage potential.