Published March 15, 2023 | Version public
Journal Article

Conditional moment methods for polydisperse cavitating flows

  • 1. ROR icon Georgia Institute of Technology
  • 2. ROR icon Iowa State University
  • 3. ROR icon California Institute of Technology

Abstract

The dynamics of cavitation bubbles are important in many flows, but their small sizes and high number densities often preclude direct numerical simulation. We present a computational model that averages their effect on the flow over larger spatiotemporal scales. The model is based on solving a generalized population balance equation (PBE) for nonlinear bubble dynamics and explicitly represents the evolving probability density of bubble radii and radial velocities. Conditional quadrature-based moment methods (QBMMs) are adapted to solve this PBE. A one-way-coupled bubble dynamics problem demonstrates the efficacy of different QBMMs for the evolving bubble statistics. Results show that enforcing hyperbolicity during moment inversion (CHyQMOM) provides comparable model-form accuracy to the traditional conditional method of moments and decreases computational costs by about ten times for a broad range of test cases. The CHyQMOM-based computational model is implemented in MFC, an open-source multi-phase and high-order-accurate flow solver. We assess the effect of the model and its parameters on a two-way coupled bubble screen flow problem.

Additional Information

© 2023 Elsevier. We thank Alexis Charalampopoulos and Themis Sapsis for invaluable discussions regarding the presented method. The US Office of Naval Research supported this work under grant numbers N0014-17-1-2676 (PM Dr. Ki-Han Kim), N0014-18-1-2625 (PM Dr. Tim Bentley), and N00014-22-1-2519 (PM Dr. Julie Young). Computations were performed via the Extreme Science and Engineering Discovery Environment (XSEDE) under allocations TG-CTS120005 (PI Colonius) and TG-PHY210084 (PI Bryngelson), supported by National Science Foundation grant number ACI-1548562.

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional details

Identifiers

Eprint ID
121608
Resolver ID
CaltechAUTHORS:20230530-441187700.29

Funding

Office of Naval Research (ONR)
N0014-17-1-2676
Office of Naval Research (ONR)
N0014-18-1-2625
Office of Naval Research (ONR)
N00014-22-1-2519
NSF
TG-CTS120005
NSF
TG-PHY210084
NSF
OAC-1548562

Dates

Created
2023-07-12
Created from EPrint's datestamp field
Updated
2023-07-12
Created from EPrint's last_modified field