In Situ Data Summaries for Flexible Feature Analysis in Large-Scale Multiphase Flow Simulations
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2022
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| _version_ | 1866910504772960256 |
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| author | Dutta, Soumya Turton, Terece Rogers, David Musser, Jordan Ahrens, James Almgren, Ann |
| author_facet | Dutta, Soumya Turton, Terece Rogers, David Musser, Jordan Ahrens, James Almgren, Ann |
| contents | The study of multiphase flow is essential for understanding the complex interactions of various materials. In particular, when designing chemical reactors such as fluidized bed reactors (FBR), a detailed understanding of the hydrodynamics is critical for optimizing reactor performance and stability. An FBR allows experts to conduct different types of chemical reactions involving multiphase materials, especially interaction between gas and solids. During such complex chemical processes, formation of void regions in the reactor, generally termed as bubbles, is an important phenomenon. Study of these bubbles has a deep implication in predicting the reactor's overall efficiency. But physical experiments needed to understand bubble dynamics are costly and non-trivial. Therefore, to study such chemical processes and bubble dynamics, a state-of-the-art massively parallel computational fluid dynamics discrete element model (CFD-DEM), MFIX-Exa is being developed for simulating multiphase flows. Despite the proven accuracy of MFIX-Exa in modeling bubbling phenomena, the very-large size of the output data prohibits the use of traditional post hoc analysis capabilities in both storage and I/O time. To address these issues and allow the application scientists to explore the bubble dynamics in an efficient and timely manner, we have developed an end-to-end visual analytics pipeline that enables in situ detection of bubbles using statistical techniques, followed by a flexible and interactive visual exploration of bubble dynamics in the post hoc analysis phase. Positive feedback from the experts has indicated the efficacy of the proposed approach for exploring bubble dynamics in very-large scale multiphase flow simulations. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2201_02557 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | In Situ Data Summaries for Flexible Feature Analysis in Large-Scale Multiphase Flow Simulations Dutta, Soumya Turton, Terece Rogers, David Musser, Jordan Ahrens, James Almgren, Ann Human-Computer Interaction Distributed, Parallel, and Cluster Computing Fluid Dynamics The study of multiphase flow is essential for understanding the complex interactions of various materials. In particular, when designing chemical reactors such as fluidized bed reactors (FBR), a detailed understanding of the hydrodynamics is critical for optimizing reactor performance and stability. An FBR allows experts to conduct different types of chemical reactions involving multiphase materials, especially interaction between gas and solids. During such complex chemical processes, formation of void regions in the reactor, generally termed as bubbles, is an important phenomenon. Study of these bubbles has a deep implication in predicting the reactor's overall efficiency. But physical experiments needed to understand bubble dynamics are costly and non-trivial. Therefore, to study such chemical processes and bubble dynamics, a state-of-the-art massively parallel computational fluid dynamics discrete element model (CFD-DEM), MFIX-Exa is being developed for simulating multiphase flows. Despite the proven accuracy of MFIX-Exa in modeling bubbling phenomena, the very-large size of the output data prohibits the use of traditional post hoc analysis capabilities in both storage and I/O time. To address these issues and allow the application scientists to explore the bubble dynamics in an efficient and timely manner, we have developed an end-to-end visual analytics pipeline that enables in situ detection of bubbles using statistical techniques, followed by a flexible and interactive visual exploration of bubble dynamics in the post hoc analysis phase. Positive feedback from the experts has indicated the efficacy of the proposed approach for exploring bubble dynamics in very-large scale multiphase flow simulations. |
| title | In Situ Data Summaries for Flexible Feature Analysis in Large-Scale Multiphase Flow Simulations |
| topic | Human-Computer Interaction Distributed, Parallel, and Cluster Computing Fluid Dynamics |
| url | https://arxiv.org/abs/2201.02557 |