Leveraging NVIDIA Omniverse for In Situ Visualization

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Abstract

Typical in situ visualization approaches involve rendering images of the simulation data in step with the simulation itself, using in situ visualization tools such as ParaView Catalyst, VisIt libsim, or SENSEI. For these approaches, one has to determine visualization parameters such as camera perspective, color maps, or scene properties in advance. The resulting frames can later be combined to produce animations, but leave little room for improving the presentation. Alternatively, simulation data can be distilled in situ to a geometric representation, which is then transferred to a workstation and used for live exploration and visualization. Producing high-quality animations, for example for outreach purposes, typically requires a somewhat tedious process of exporting the geometry to different formats and postprocessing using dedicated modelling, rendering, or compositing software. We propose a method that allows interactive, high-quality visualization of distilled simulation geometry. Omniverse is NVIDIA’s collaboration platform for 3D production pipelines. It is integrated with a number of freely and commercially available 3D software packages and game engines and enables content creators to work on different aspects of models or entire scenes simultaneously. By integrating ParaView and Catalyst with the Omniverse, the visualization geometry becomes immediately accessible to a number of 3D content authoring and rendering tools without the requirement of invasive software changes in situ or tedious postprocessing and conversion workflows. Since Omniverse can directly communicate with game engines, the visualization can be augmented using advanced features such as game physics simulation to improve insight and enhance intuition. We demonstrate this by placing architectural building models on a surface that is deformed by an earthquake-like wave. This makes it possible to immediately assess the impact of the earthquake on buildings in a live, interactive way, while leveraging the advanced rendering capabilities of the game engine.

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Hummel, M., & van Kooten, K. (2019). Leveraging NVIDIA Omniverse for In Situ Visualization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11887 LNCS, pp. 634–642). Springer. https://doi.org/10.1007/978-3-030-34356-9_48

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