Lagrangian Simulation Volume-Based Contour Tree Simplification

Fuente: arXiv
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Main Authors: Dilys, Domantas, Carr, Hamish, Boeing, Steven
Format: Preprint
Published: 2025
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author Dilys, Domantas
Carr, Hamish
Boeing, Steven
author_facet Dilys, Domantas
Carr, Hamish
Boeing, Steven
contents Many scientific and engineering problems are modelled by simulating scalar fields defined either on space-filling meshes (Eulerian) or as particles (Lagrangian). For analysis and visualization, topological primitives such as contour trees can be used, but these often need simplification to filter out small-scale features. For parcel-based convective cloud simulations, simplification of the contour tree requires a volumetric measure rather than persistence. Unlike for cubic meshes, volume cannot be approximated by counting regular vertices. Typically, this is addressed by resampling irregular data onto a uniform grid. Unfortunately, the spatial proximity of parcels requires a high sampling frequency, resulting in a massive increase in data size for processing. We therefore extend volume-based contour tree simplification to parcel-in-cell simulations with a graph adaptor in Viskores (VTK-m), using Delaunay tetrahedralization of the parcel centroids as input. Instead of relying on a volume approximation by counting regular vertices -- as was done for cubic meshes -- we adapt the 2D area splines reported by Bajaj et al. 10.1145/259081.259279, and Zhou et al. 10.1109/TVCG.2018.2796555. We implement this in Viskores (formerly called VTK-m) as prefix-sum style hypersweeps for parallel efficiency and show how it can be generalized to compute any integrable property. Finally, our results reveal that contour trees computed directly on the parcels are orders of magnitude faster than computing them on a resampled grid, while also arguably offering better quality segmentation, avoiding interpolation artifacts.
format Preprint
id arxiv_https___arxiv_org_abs_2508_14339
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Lagrangian Simulation Volume-Based Contour Tree Simplification
Dilys, Domantas
Carr, Hamish
Boeing, Steven
Computational Geometry
Distributed, Parallel, and Cluster Computing
Data Structures and Algorithms
Many scientific and engineering problems are modelled by simulating scalar fields defined either on space-filling meshes (Eulerian) or as particles (Lagrangian). For analysis and visualization, topological primitives such as contour trees can be used, but these often need simplification to filter out small-scale features. For parcel-based convective cloud simulations, simplification of the contour tree requires a volumetric measure rather than persistence. Unlike for cubic meshes, volume cannot be approximated by counting regular vertices. Typically, this is addressed by resampling irregular data onto a uniform grid. Unfortunately, the spatial proximity of parcels requires a high sampling frequency, resulting in a massive increase in data size for processing. We therefore extend volume-based contour tree simplification to parcel-in-cell simulations with a graph adaptor in Viskores (VTK-m), using Delaunay tetrahedralization of the parcel centroids as input. Instead of relying on a volume approximation by counting regular vertices -- as was done for cubic meshes -- we adapt the 2D area splines reported by Bajaj et al. 10.1145/259081.259279, and Zhou et al. 10.1109/TVCG.2018.2796555. We implement this in Viskores (formerly called VTK-m) as prefix-sum style hypersweeps for parallel efficiency and show how it can be generalized to compute any integrable property. Finally, our results reveal that contour trees computed directly on the parcels are orders of magnitude faster than computing them on a resampled grid, while also arguably offering better quality segmentation, avoiding interpolation artifacts.
title Lagrangian Simulation Volume-Based Contour Tree Simplification
topic Computational Geometry
Distributed, Parallel, and Cluster Computing
Data Structures and Algorithms
url https://arxiv.org/abs/2508.14339