Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
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. In this work, we describe a visualization approach that provides explicit instances of the bubble distribution and produces bubble geometry based on local flow properties. To facilitate animation, the instancing of the bubble distribution provides coherence over time by advancing bubbles between time steps and updating the distribution. Our approach provides an intuitive visualization and enables direct visual comparison of simulation results to physical experiments.
Description
@article{10.1111:cgf.13203,
journal = {Computer Graphics Forum},
title = {{Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach}},
author = {Hummel, Mathias and Jöckel, Lisa and Schäfer, Jan and Hlawitschka, Mark Werner and Garth, Christoph},
year = {2017},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13203}
}