Stochastic-field cavitation model

Dumond, Julien; Magagnato, Franco; Class, Andreas G.

doi:10.1063/1.4813813

Cited by 26 publications

(14 citation statements)

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“…Within the workgroup at KIT the Stochastic Field Method is transferred to the field of two phase flow [1]. The volume fraction of the disperse phase as well as the bubble size depend on random processes.…”

Section: The Stochastic Field Methods In Two Phase Flowmentioning

confidence: 99%

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Application of the Stochastic Field Method to two phase flow

Raquet

Class

Edelbauer

2017

Proc Appl Math and Mech

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The Stochastic Field Method was introduced in the field of combustion and represents a Eulerian Monte-Carlo technique. It was first transfered to the field of multiphase flow in [1] facing a problem in nuclear technology. Within this work it is applied to cavitating flows in the automotive sector. Both phases, the continuous and the dispersed phase, are observed using a Eulerian perspective which fits the architecture of CFD solvers resulting in efficient computations. Instead of solving the behaviour of individual bubbles, as in Lagrangian Particle Methods, variations of volume fractions of the dispersed phase in each computational mesh cell are considered. A stochastic term is introduced into the transport equations for the volume fractions of the dispersed phase via a Wiener process. Thus sampling over several time steps provides the probability density function of volume fraction in each mesh cell. The implementation is carried out by compiling user-functions to a commercial CFD code. A test case representing an injection system in an automotive application is presented. Moreover strategies to implement the effect of coalescence are shown.

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Section: The Stochastic Field Methods In Two Phase Flowmentioning

confidence: 99%

“…It was first transfered to the field of multiphase flow in [1] facing a problem in nuclear technology. Within this work it is applied to cavitating flows in the automotive sector.…”

mentioning

confidence: 99%

Application of the Stochastic Field Method to two phase flow

Raquet

Class

Edelbauer

2017

Proc Appl Math and Mech

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“…Models that use probability density functions (PDF) have attained a certain level of popularity first in the simulations of combustion applications. A full Eulerian PDF solving framework has been developed in [13] and applied successfully on cavitation in [14]. Applying certain stochastic procedures, this approach uses an ensemble of Eulerian fields to represent a distribution of bubble radii.…”

Section: Introductionmentioning

confidence: 99%

LES Investigation with an Eulerian Stochastic Field Cavitation Model

Chen¹,

Oevermann²

2018

Proceedings of the 10th International Symposium on Cavitation (CAV2018)

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Due to an ongoing trend of high injection pressures in the realm of internal combustion engines, the role of cavitation that typically happens inside the injector nozzle has become increasingly important. In this work, a large eddy simulation (LES) with cavitation modeled on the basis of an Eulerian Stochastic Field (ESF) method and a homogeneous mixture model is performed to investigate the role of cavitation on academic injector. The ESF cavitation model is coupled to a pressure based solver for the flow, which lowers the computational cost, thereby making the methodology highly applicable to realistic injector geometries. Moreover, the nature of the ESF method makes it more convenient to achieve a high scalability when applied to parallel cases, which gives the method an edge over cavitation models that are based on Lagrangian tracking. The result of the ESF simulation is compared against that from a typical single volume fraction solver for validation. The capability of the ESF model to capture the probability density function (PDF) of vapor bubble radii is also demonstrated.

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confidence: 99%

Application of the Stochastic Field Method to Multi‐Fluid Flow

Raquet

Class

Edelbauer

2018

Proc Appl Math and Mech

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The Stochastic Field Method was originally derived in the field of combustion and firstly applied to a cavitation problem by our group [1]. Randomly distributed variables exist in both combustion and cavitating problems. Calculating strong nonlinear processes using mean values as input, leads to unphysical results. The consideration of the variable's probability density function (PDF) becomes mandatory. The Stochastic Field Method approximates this PDF by samples similar to methods of Lagrangian particles where imaginary particles are introduced to the flow. In contrast to Lagrangian particles methods, these samples are represented by Eulerian fields described by stochastic partial differential equations. This pure Eulerian interpretation makes the method attractive for CFD-codes: A coupling of an Eulerian and a Lagrangian perspective becomes obsolete which results in efficient computation times -especially in the presence of a vast number of bubbles. In contrast to other Eulerian methods, the calculation of an arbitrary PDF is possible at low computational cost. The representation of samples as fields allows the visualization of PDFs within every computational cell. The first implementation into a commercial CFD-Code is presented. In addition, industrial examples, like cavitation in an automotive injection nozzle, are shown.

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Stochastic-field cavitation model

Cited by 26 publications

References 50 publications

Application of the Stochastic Field Method to two phase flow

Application of the Stochastic Field Method to two phase flow

LES Investigation with an Eulerian Stochastic Field Cavitation Model

Application of the Stochastic Field Method to Multi‐Fluid Flow

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