Showcase – Validation

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Rayleigh–Taylor Instability

Rayleigh–Taylor instability is one of the most important benchmarks for multiphase CFD solvers. The instability of the interface separating two fluids of different densities is known as Rayleigh-Taylor instability. Capturing this effect necessitates an accurate modelling of the interface between the two different fluids.

PreonLab results are compared to the reference solution given by a Level-Set solver used by Grenier, Nicolas, et al. in “An Hamiltonian interface SPH formulation for multi-fluid and free surface flows.” published in the Journal of Computational Physics 228, 22 (2009). This Level-Set solver was originally introduced in the PhD thesis of Colicchio, Giuseppina: “Violent disturbance and fragmentation of free surfaces.” (2005).


 

Torricelli’s Law

Torricelli’s law describes the outflow velocity of an aperture from a jar, based on its depth to the water surface. For a horizontal opening, the flow follows a parabolic path.

The variation of the depth to the surface leads to different outflow velocities and thus to different progressions of the parabolas. A tangent line for the family of parabolas generated by the apertures at varying depth can be found which is known as an envelope. As you can see in the video, this phenomenon is well captured in PreonLab.

 


 

Renault Validation: Leakage Simulation

PreonLab is successfully employed by Renault to validate and improve heat shield designs which guarantee that no flammable liquid gets in contact with hot parts of the engine. Our highly efficient, meshless Preon solver enables Renault to test many design variants for different liquids and possible leakages on virtual prototypes within a day.

 

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Benchmark Simulation Water Management

Our customer IAV GmbH designed and built a test bench to investigate various simulation tools, including PreonLab, to illustrate exemplary load cases from the field of water management.

PreonLab showed that the discharge behaviour of the water on an inclined plane is very similar to the real test bench. The constriction of the water with decreasing water pressure was also shown to be exactly symmetrical in the simulation.

The quantiative predictions made by PreonLab for this example and other variants were not only very well matching with the experiment but also computed in the shortest time.

Also the test bench with holes and obstacles shows great results:

 


 

Poiseuille Flow

Poiseuille Flow is a famous benchmark for CFD codes.
You will see how well PreonLab captures the flow across Reynolds numbers ranging from 10 to 1,000 for different combinations of inlet velocity, viscosity and density in this article:

Poiseuille Flow


 

Lid-Driven Cavity

The computation of a lid-driven cavity flow is a famous test bed for #CFD codes.
You will learn how well PreonLab captures the flow across Reynolds numbers ranging from 100 to 10,000 for different combinations of viscosity, density and lid velocity in this article:

Lid-Driven Cavity at PreonLab


 

MARIN Dam Break Simulation

Comparison of the rendered result simulated with PreonLab with real world video footage and experiment data. The validation scenario is specified in Kleefsman et al. “A volume-of-fluid based simulation method for wave impact problems“ published in the Journal of Computational Physics 206, 1 (2005). The real world pressure values described in the paper have been compared to the results computed in PreonLab.

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Drag Force Model

Being able to efficiently simulate free-surface flow without necessarily simulating the air phase of the simulation domain is a powerful method for rapid-prototyping. Within only a couple of hours the engineer gets the results of the PreonLab simulation and can react on the simulation analysis by performing another simulation with an evolved CAD model. Using the Liu drag force model, the air phase can nevertheless be taken into account without reducing the performance of the simulation.

In the showcased video you can see the validation results that have been compared to real world data in a tire development test environment.

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