Interactive visual steering of hierarchical simulation ensembles

Splechtna, Rainer; Matković, Krešimir; Gračanin, Denis; Jelovic, Mario; Hauser, Helwig

doi:10.1109/vast.2015.7347635

Cited by 18 publications

(5 citation statements)

References 14 publications

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“…Visualization researchers usually regard simulation parameters as multidimensional vectors and use techniques designed for high-dimensional data to analyze the parameter space. These techniques contains radial plots [9,11,12], glyphs [8], scatter plots [23,29,36], parallel plots [28,42], matrices [33], and line charts [7]. One significant constraint of these techniques is that they cannot explore the input parameters that have not been simulated.…”

Section: Parameter Space Explorationmentioning

confidence: 99%

VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations

Neng¹,

Fan²,

Guo³

et al. 2022

Preprint

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We propose VDL-Surrogate, a view-dependent neural-network-latent-based surrogate model for parameter space exploration of ensemble simulations that allows high-resolution visualizations and user-specified visual mappings. Surrogate-enabled parameter space exploration allows domain scientists to preview simulation results without having to run a large number of computationally costly simulations. Limited by computational resources, however, existing surrogate models may not produce previews with sufficient resolution for visualization and analysis. To improve the efficient use of computational resources and support high-resolution exploration, we perform ray casting from different viewpoints to collect samples and produce compact latent representations. This latent encoding process reduces the cost of surrogate model training while maintaining the output quality. In the model training stage, we select viewpoints to cover the whole viewing sphere and train corresponding VDL-Surrogate models for the selected viewpoints. In the model inference stage, we predict the latent representations at previously selected viewpoints and decode the latent representations to data space. For any given viewpoint, we make interpolations over decoded data at selected viewpoints and generate visualizations with user-specified visual mappings. We show the effectiveness and efficiency of VDL-Surrogate in cosmological and ocean simulations with quantitative and qualitative evaluations. Source code is publicly available at https://github.com/trainsn/VDL-Surrogate.

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Section: Parameter Space Explorationmentioning

confidence: 99%

VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations

Neng¹,

Fan²,

Guo³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…K-means [19,83], hierarchical clustering [92], and DBSCAN [47] are the most common clustering algorithms. Clustering methods can use different common distance measures such as the Euclidean [26,27,30,44,85], the Manhattan [11], the Mahalanobis distance [40,59] or application-or data-specific measures that use scalar values as the feature vectors [44], or sums of squared intensity differences [14], etc. In this work, we incorporate traditional distance measures and domainspecific characteristics to achieve relevant clustering results for our domain problem; details of our approach are discussed in Section 3.4.…”

Section: Related Work and Backgroundmentioning

confidence: 99%

Visual Analysis and Detection of Contrails in Aircraft Engine Simulations

Nipu¹,

Floricel²,

Naghashzadeh³

et al. 2022

Preprint

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Fig. 1. Visual analysis of contrails using multiple coordinated views. (A) Filters for I/O/model parameters and color legend. (B) Colored-tile glyphs representing groups of same-parameter ensemble members; the bottom run is currently selected. A large number of runs appear to share the same input parameters. (C) Filament plots grouping output parameters of all ensemble runs; the current run is highlighted and appears significantly different. (D) 3D plumes of two similar runs, showing cooling temperatures further down the jet plume, along with animated particle trajectories. (E) Contrail evolution panel displaying the progression of contrail structures, showing a general trend where smaller groups merge into larger groups.

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“…For example, Ferstl et al 12 use PCA to convert streamlines into a structure preserving Euclidean space. Furthermore, a lot of approaches are implemented by feature extraction algorithms like k-series in the work 5,36,6 , and the work based on DBSCAN 10,26 , AHC 12,13,37,38,39,40 and topic modeling 41,42,43,44,45,46,47,48,49,50,51,52,53 .…”

Section: Spatio-temporal Simulation Data Visualizationmentioning

confidence: 99%

eBoF: Interactive Temporal Correlation Analysis for Ensemble Data Based on Bag-of-Features

Ding

Qian

Chen

et al. 2022

Preprint

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We propose eBoF, a novel time-varying ensemble data visualization approach based on bag-of-features (BoF). In the eBoF model, we take a simple and monotone interval from all target variables of ensemble scalar data as a local feature patch of BoF model and the duration time of each interval (i.e., feature patch) as its frequency. The feature clusters in ensemble runs are then identified based on the similarity of temporal correlations. eBoF generates the clusters together with their probability distribution across all the feature patches while storing the geo-spatial information, which is often lost in the traditional topic modelling or clustering algorithms. The probability distribution across different clusters can help to generate reasonable clustering results evaluated by the domain knowledge. We conduct several case studies and performance analyses. We also consult the domain experts to evaluate the proposed eBoF model. Evaluation results suggest the proposed eBoF can provide insightful and comprehensive evidence on ensemble simulation data analysis.

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Interactive visual steering of hierarchical simulation ensembles

Cited by 18 publications

References 14 publications

VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations

VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations

Visual Analysis and Detection of Contrails in Aircraft Engine Simulations

eBoF: Interactive Temporal Correlation Analysis for Ensemble Data Based on Bag-of-Features

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