Viscous Fingering: A Topological Visual Analytic Approach

Lukasczyk, Jonas; Aldrich, Garrett; Steptoe, Michael; Favelier, Guillaume; Gueunet, Charles; Tierny, Julien; Maciejewski, Ross; Hamann, Bernd; Leitte, Heike

doi:10.4028/www.scientific.net/amm.869.9

Cited by 34 publications

(33 citation statements)

References 15 publications

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“…1). Fingers can be identified algorithmically by first sampling the salt concentration density of the pointsets on a regular grid and then deriving superlevel set components below the salt supply [17]. Lukasczyk et al [19] demonstrated that NTGs can be used to effectively summarize shared properties of the fingers across different runs, timesteps, and initial parameters.…”

Section: Viscous Fingeringmentioning

confidence: 99%

Dynamic Nested Tracking Graphs

Lukasczyk

Garth

Weber

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. The topology-based visual analytics framework supports the feature-centered navigation of Cinema databases consisting of image and analysis products generated during large-scale simulation runs, where numerous features are organized into a manageable amount of hierarchical groups that can be explored in a level-of-detail approach. Here, the interface shows an ensemble member of the viscous finger dataset, where colors encode individual fingers for salt concentration level 30. The prime interaction device of the framework is a nested tracking graph (NTG) that simultaneously displays the temporal evolution of superlevel set components for multiple levels (bottom). The NTG is used to navigate through time and retrieve component images from the database (top left), whereas the split tree (top center) and persistence diagram (top right) support the user in selecting important levels and filter criteria.Abstract-This work describes an approach for the interactive visual analysis of large-scale simulations, where numerous superlevel set components and their evolution are of primary interest. The approach first derives, at simulation runtime, a specialized Cinema database that consists of images of component groups, and topological abstractions. This database is processed by a novel graph operation-based nested tracking graph algorithm (GO-NTG) that dynamically computes NTGs for component groups based on size, overlap, persistence, and level thresholds. The resulting NTGs are in turn used in a feature-centered visual analytics framework to query specific database elements and update feature parameters, facilitating flexible post hoc analysis.

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Section: Viscous Fingeringmentioning

confidence: 99%

Dynamic Nested Tracking Graphs

Lukasczyk

Garth

Weber

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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“…Oftentimes, these approaches require the presence of clearly defined features in isomorphic structures, and are not directly relevant to our illustrative example: finger structures are soft-knowledge features. Favelier et al [21] and Lukasczyk et al [37] use an adaptation of Shepard's kernel method [59] to identify such features based on concentrations. Both these works rely on userdefined thresholds.…”

Section: Cfd Visualizationmentioning

confidence: 99%

“…Basic visual abstractions such as line charts, quartile charts, and histograms are commonly used in ensemble visualization to encode statistical parameters [28], as well as reduced spatial aggregate views [19,37] to display specific attributes at a specific time and location. To facilitate further exploration of ensemble members across space and time, these aggregate views are linked to range-based representations [26].…”

Section: Cfd Visualizationmentioning

confidence: 99%

“…To facilitate further exploration of ensemble members across space and time, these aggregate views are linked to range-based representations [26]. These representations may include colored overlays, multidimensional scaling projections [8], and various types of tracking graphs [9,37,69]. We use similar encodings for several of the features we compute.…”

Section: Cfd Visualizationmentioning

confidence: 99%

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Details-First, Show Context, Overview Last: Supporting Exploration of Viscous Fingers in Large-Scale Ensemble Simulations

Luciani

Burks

Sugiyama³

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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Visualization research often seeks designs that first establish an overview of the data, in accordance to the information seeking mantra: "Overview first, zoom and filter, then details on demand". However, in computational fluid dynamics (CFD), as well as in other domains, there are many situations where such a spatial overview is not relevant or practical for users, for example when the experts already have a good mental overview of the data, or when an analysis of a large overall structure may not be related to the specific, information-driven tasks of users. Using scientific workflow theory and, as a vehicle, the problem of viscous finger evolution, we advocate an alternative model that allows domain experts to explore features of interest first, then explore the context around those features, and finally move to a potentially unfamiliar summarization overview. In a model instantiation, we show how a computational back-end can identify and track over time low-level, small features, then be used to filter the context of those features while controlling the complexity of the visualization, and finally to summarize and compare simulations. We demonstrate the effectiveness of this approach with an online web-based exploration of a total volume of data approaching half a billion seven-dimensional data points, and report supportive feedback provided by domain experts with respect to both the instantiation and the theoretical model.

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“…Its applicability to time-varying data [10,91], ensembles [35] and comparisons [92] makes it a reliable candidate for assessing the likeliness of simulations in an ensemble given a ground truth. Although several approaches have explored the promising potential of TDA for extracting and characterizing the features of interest in viscous fingering simulations [36,59], no approach has been proposed to estimate the similarity between two time-varying viscous fingerings based on topological representations.…”

Section: Introductionmentioning

confidence: 99%

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

Soler

Martín

Darche

et al. 2019

2019 IEEE 9th Symposium on Large Data Analysis and Visualization (LDAV)

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Figure 1: Overview of the ranking framework. An ensemble of viscous fingering simulation runs S 1 , S 2 , S 3 is launched, and the persistence diagram of newly available time-steps can be computed in-situ (left). Only persistence diagrams for which there is a matching ground truth image (center, top) are computed. Diagrams of every simulation are compared with the diagrams of the ground truth (center, bottom) at matching time-steps. This comparison, based on a metric W 2 combining the notions of persistence and geometry, outputs a distance measurement, which can be integrated over time to form the metric d W 2. This produces a final ranking (right) which characterizes the quality of simulations, allowing experts to select and explore best performing runs automatically. ABSTRACTThis 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.2. Metrics: new topological metrics for comparing time-varying viscous fingers are introduced, based on the Wasserstein matching of persistence diagrams, specifically tuned for the viscous fingering phenomenon and integrated over time.3. Case study: a complete case study of a viscous fingering simulation ensemble is documented, along with a proof-ofconcept in-situ implementation of our approach. 4. Evaluation: the metrics and ranking framework are qualitatively evaluated with feedback from domain experts. The quantitative performance of our approach is also analyzed and its superiority over traditional alternatives is demonstrated.

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Viscous Fingering: A Topological Visual Analytic Approach

Cited by 34 publications

References 15 publications

Dynamic Nested Tracking Graphs

Dynamic Nested Tracking Graphs

Details-First, Show Context, Overview Last: Supporting Exploration of Viscous Fingers in Large-Scale Ensemble Simulations

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

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