2014
DOI: 10.1016/j.jcp.2013.08.023
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A Lagrangian VOF tensorial penalty method for the DNS of resolved particle-laden flows

Abstract: OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.

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Cited by 61 publications
(78 citation statements)
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“…The choice of the grid resolution was the best compromise (as was observed in Vincent et al, 2014 , JCP) between accuracy of solution and calculation time. Concerning the sensitivity of results to the grid resolution using the ITPM, it was observed in Vincent et al (2014) that correct results were obtained when comparing particle flows with reference solutions for particle settling in a tank ( Fig. 13 of that paper) or particle rotating in a Stokes flow (Fig.…”
Section: Numerical Modelmentioning
confidence: 93%
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“…The choice of the grid resolution was the best compromise (as was observed in Vincent et al, 2014 , JCP) between accuracy of solution and calculation time. Concerning the sensitivity of results to the grid resolution using the ITPM, it was observed in Vincent et al (2014) that correct results were obtained when comparing particle flows with reference solutions for particle settling in a tank ( Fig. 13 of that paper) or particle rotating in a Stokes flow (Fig.…”
Section: Numerical Modelmentioning
confidence: 93%
“…Details of numerical approach and validation test cases are given in Vincent et al (2014) . The DNS approach is based on a one-fluid formalism of the incompressible Navier-Stokes equations with an algebraic adaptive augmented Lagrangian method used for pressure-velocity coupling (Implicit Tensorial Penalty Method, ITPM).…”
Section: Numerical Modelmentioning
confidence: 99%
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“…A detailed presentation of the finite size particle simulations and precise validations are presented elsewhere. 23 It is worthwhile to mention that the present model can be easily implemented in any code (based on IBM, Immersed Interface Method, etc.) accounting for finite size particles.…”
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confidence: 99%