Name
Title | ||
|---|---|---|
Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach. |
Abstract | ||
|---|---|---|
Eulerian Method of Moment MoM solvers are gaining popularity for multi-phase CFD simulation involving bubbles or droplets in process engineering. Because the actual positions of bubbles are uncertain, the spatial distribution of bubbles is described by scalar fields of moments, which can be interpreted as probability density functions. Visualizing these simulation results and comparing them to physical experiments is challenging, because neither the shape nor the distribution of bubbles described by the moments lend themselves to visual interpretation. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1111/cgf.13203 | Comput. Graph. Forum |
Field | DocType | Volume |
Computer vision,3D computer graphics,Computer graphics (images),Computer science,Multi phase,Theoretical computer science,Real-time computer graphics,Sampling (statistics),Artificial intelligence,Probabilistic logic,Fluid simulation,Computer graphics | Journal | 36 |
Issue | ISSN | Citations |
3 | 0167-7055 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Hummel | 1 | 68 | 3.32 |
| L. Jöckel | 2 | 0 | 0.34 |
| Jan Schäfer | 3 | 320 | 14.02 |
| Mario Hlawitschka | 4 | 162 | 15.39 |
| Christoph Garth | 5 | 751 | 50.85 |