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LES stochastic modelling of cavitation with its applications in OpenFOAM
Doktorsavhandling, 2019

As much as HEMs have been widely applied in both academic studies and commercial computational tools, the stochastic feature of cavitation phenomena has been missing in the single Eulerian field models nowadays. With only one Eulerian field, only one bubble radius associated with the volume fraction is solved in any spatial location. However, physically, the vapor bubble sizes are highly fluctuating, hence can better be described by a probability density function (PDF). In order to solve the evolution equation of the PDF, a Eulerian Stochastic Field (ESF) model is developed in this work. Multiple Eulerian fields are used to represent a distribution of cavitation bubble radii.

The ESF method has been previously applied for cavitation simulations only in the context of a compressible flow solver. However, the solution of the compressible form of the Navier-Stokes equation is known to be computationally expensive for low Mach number flow. Therefore, whether the ESF model can be applied in combination with a pressure based solver became an interesting question. In this work, we coupled the ESF model to a pressure-based PISO algorithm, making the ESF model computationally efficient enough for studies of realistic injector nozzle geometries and standard operating conditions. Several simplified geometries, including one step-contraction throttle and two academic injector nozzle designs, are investigated using the novel cavitation model. Furthermore, we applied the ESF model on a realistic multi-hole injector geometry (spray G/G2 as defined by the Engine Combustion Network (ECN)) demonstrating that the ESF cavitation model can be applied in simulations of realistic nozzle injector geometries.

Rayleigh-Plesset Equation

Cavitation

Modelling

Simulation

Eulerian Stochastic Field Method

OpenFOAM

Homogeneous Equilibrium Model

## Författare

### Boxiong Chen

Chalmers, Mekanik och maritima vetenskaper, Förbränning och framdrivningssystem

### Ämneskategorier

Annan data- och informationsvetenskap

Annan maskinteknik

Teknisk mekanik

### Styrkeområden

Energi

### Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

### ISBN

978-91-7597-861-1

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4542

### Utgivare

Chalmers

HC1, Johanneberg

Opponent: Mario F. Trujillo, University of Wisconsin--Madison, USA