Leon C. Malan

Dr. Leon C. Malan

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Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2021 in Journal of Computational Physics
Verified
Journal Article
Closed access
LMLeon C. Malan
Leon C. Malan
AMA.G. Malan
A.G. Malan
SZS. Zaleski
S. Zaleski
PRPieter Rousseau
Pieter Rousseau

1 June 2021 in Computer Physics Communications
Verified
Journal Article
Closed access
WAW. Aniszewski
W. Aniszewski
TAT. Arrufat
T. Arrufat
MCM. Crialesi-Esposito
M. Crialesi-Esposito
SDS. Dabiri
S. Dabiri
DFD. Fuster
D. Fuster
SZS. Zaleski
S. Zaleski

3 December 2022 in Applied Sciences
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Journal Article
Open access
PDF file
LMLeon C. Malan
Leon C. Malan
CPChiara Pilloton
Chiara Pilloton
ACAndrea Colagrossi
Andrea Colagrossi
AMArnaud Malan
Arnaud Malan
As part of the Sloshing Wing Dynamics H2020 EU project, an experimental campaign was conducted to study slosh-induced damping in a vertically excited tank filled with liquid water or oil and air. In this work, we simulate these experiments using two numerical approaches. First, a single-phase, weakly compressible liquid model is used, and the gas flow (air) is not modeled. For this approach, a proven Smoothed Particle Hydrodynamics (SPH) model is used. In the second approach, both phases are simulated with an incompressible liquid and weakly compressible gas model via a Finite Volume Method (FVM) using Volume-of-Fluid (VOF) to track the liquid phase. In both approaches, the energy distribution of the flow is calculated over time in two- and three-dimensional simulations. It is found that there is reasonable agreement on the energy dissipation evolution between the methods. Both approaches show converging results in 2D simulations, although the SPH simulations seem to have a faster convergence rate. In general, the SPH results tend to overpredict the total dissipation compared to the experiment, while the finite volume 2D results underpredict it. Time histories of the center of mass positions are also compared. The SPH results show a much larger vertical center of mass motion compared to the FVM results, which is more pronounced for the high Reynolds number (water) case, probably linked to the absence of the air phase. On the other hand, the limited center of mass motion of the FVM could be linked to the need for higher spatial resolutions in order to resolve the complex gas–liquid interactions, particularly in 3D.

15 May 2019 in Computers & Fluids
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Journal Article
Closed access
LMLeon C. Malan
Leon C. Malan
YLYue Ling
Yue Ling
RSR. Scardovelli
R. Scardovelli
ALA. Llor
A. Llor
SZS. Zaleski
S. Zaleski

1 April 2019 in International Journal of Multiphase Flow
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Journal Article
Closed access
WAWojciech Aniszewski
Wojciech Aniszewski
SZStéphane Zaleski
Stéphane Zaleski
ALAntoine Llor
Antoine Llor
LMLeon C. Malan
Leon C. Malan

22 November 2022 in Applied Sciences
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Journal Article
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EBElrich Botha
Elrich Botha
LMLeon C. Malan
Leon C. Malan
AMArnaud Malan
Arnaud Malan
For CFD liquid sloshing simulations, fine computational mesh resolutions are typically required to model the flow within small flow passages or orifices found in fuel tanks. This work presents a method of replacing the fine computational mesh elements within orifices with large one-dimensional mesh elements that integrate seamlessly with standard finite volume computational elements with the intended advantage of reducing the overall computational cost of CFD simulations. These one-dimensional elements conserve mass and momentum for two-phase flow in incompressible Volume-Of-Fluid CFD. Instead of fully resolving the momentum diffusion term, empirical correlations are used to account for the viscous losses within the orifices for both two- and three-dimensional simulations. The one-dimensional orifice elements are developed and validated against analytical and experimental results using the finite volume CFD code Elemental®. Furthermore, these elements are tested in a violent sloshing simulation and compared with full-resolution numerical results as well as experimental results. The elements are shown to decrease computational cost significantly by reducing the number of computational elements as well as increasing the simulation time step sizes (due to an increase in element sizes).