GEO-PHCGCVIVAug 20, 2019

Ranking Viscous Finger Simulations to an Acquired Ground Truth with Topology-aware Matchings

arXiv:1908.07841v131 citations
AI Analysis

This is an incremental improvement for experts in porous media fluid flow, enabling automatic discarding of irrelevant simulations and ranking plausible ones.

The paper tackles the problem of automatically evaluating and ranking viscous finger simulation runs against a reference acquisition using a topological data analysis framework, achieving quantitative superiority over traditional alternatives.

This application paper presents a novel framework based on topological data analysis for the automatic evaluation and ranking of viscous finger simulation runs in an ensemble with respect to a reference acquisition. Individual fingers in a given time-step are associated with critical point pairs in the distance field to the injection point, forming persistence diagrams. Different metrics, based on optimal transport, for comparing time-varying persistence diagrams in this specific applicative case are introduced. We evaluate the relevance of the rankings obtained with these metrics, both qualitatively thanks to a lightweight web visual interface, and quantitatively by studying the deviation from a reference ranking suggested by experts. Extensive experiments show the quantitative superiority of our approach compared to traditional alternatives. Our web interface allows experts to conveniently explore the produced rankings. We show a complete viscous fingering case study demonstrating the utility of our approach in the context of porous media fluid flow, where our framework can be used to automatically discard physically-irrelevant simulation runs from the ensemble and rank the most plausible ones. We document an in-situ implementation to lighten I/O and performance constraints arising in the context of parametric studies.

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