Name
Title | ||
|---|---|---|
Fluid flow simulation over complex shape objects using image processing to achieve mesh generation. |
Abstract | ||
|---|---|---|
In the domain of flow simulation, avoiding the manual conception and numerisation of the domain can lead to the saving of a certain amount of time. Some processes, using heavy devices like LASER metrology, allow the numerical reconstruction of a real object. The aim of this paper is to propose a more simple tool requiring a commercial digital camera (like a smartphone), to transform a digital picture into a ready to use mesh. Besides simplicity, the tool has to be precise enough to bring accurate simulation results. Then, image processing object detection and reconstruction are used to generate a 2D mesh that can be integrated in a finite volume transient CFD simulation. Cars and airfoils are chosen as objects and the DNS fluid flow Gerris solver performs the simulations. After a validation on a circular shape object, simulations, conducted at different Reynolds number, provide accurate results plotting the Von Karman alley regime. |
Year | Venue | Field |
|---|---|---|
2017 | IJSPM | Iterative reconstruction,Computer vision,Object detection,Computer science,Image processing,Digital camera,Artificial intelligence,Computational fluid dynamics,Solver,Finite volume method,Mesh generation |
DocType | Volume | Issue |
Journal | 12 | 1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khaoula Lassoued | 1 | 0 | 0.34 |
| Tonino Sophy | 2 | 0 | 0.34 |
| Julien Jouanguy | 3 | 0 | 0.34 |
| Luis Le-Moyne | 4 | 0 | 0.34 |