Fourier neural operator based fluid-structure interaction for predicting the vesicle dynamics Article Swipe
Xiao Wang
,
Ting Gao
,
Kai Liu
,
Jinqiao Duan
,
Meng Zhao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.02311
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.02311
Solving complex fluid-structure interaction (FSI) problems, characterized by nonlinear partial differential equations, is crucial in various scientific and engineering applications. Traditional computational fluid dynamics (CFD) solvers are insufficient to meet the growing requirements for large-scale and long-period simulations. Fortunately, the rapid advancement in neural networks, especially neural operator learning mappings between function spaces, has introduced novel approaches to tackle these challenges via data-driven modeling. In this paper, we propose a Fourier neural operator-based fluid-structure interaction solver (FNO-based FSI solver) for efficient simulation of FSI problems, where the solid solver based on the finite difference method is seamlessly integrated with the Fourier neural operator to predict incompressible flow using the immersed boundary method. We analyze the performance of the FNO-based FSI solver in the following three situations: training data with or without the steady state, training method with one-step label or multi-step labels, and prediction in interpolation or extrapolation. We find that the best performance for interpolation is achieved by training the operator with multi-step labels using steady-state data. Finally, we train the FNO-based FSI solver using this optimal training method and apply it to vesicle dynamics. The results show that the FNO-based FSI solver is capable of capturing the variations in the fluid and the vesicle.
Related Topics
Concepts
Solver
Interpolation (computer graphics)
Computer science
Computational fluid dynamics
Operator (biology)
Artificial neural network
Extrapolation
Fourier transform
Applied mathematics
Artificial intelligence
Mathematical optimization
Mathematics
Mathematical analysis
Physics
Mechanics
Motion (physics)
Biochemistry
Programming language
Chemistry
Repressor
Gene
Transcription factor
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.02311
- https://arxiv.org/pdf/2401.02311
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390632590
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4390632590Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2401.02311Digital Object Identifier
- Title
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Fourier neural operator based fluid-structure interaction for predicting the vesicle dynamicsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-04Full publication date if available
- Authors
-
Xiao Wang, Ting Gao, Kai Liu, Jinqiao Duan, Meng ZhaoList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.02311Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2401.02311Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2401.02311Direct OA link when available
- Concepts
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Solver, Interpolation (computer graphics), Computer science, Computational fluid dynamics, Operator (biology), Artificial neural network, Extrapolation, Fourier transform, Applied mathematics, Artificial intelligence, Mathematical optimization, Mathematics, Mathematical analysis, Physics, Mechanics, Motion (physics), Biochemistry, Programming language, Chemistry, Repressor, Gene, Transcription factorTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.these | 59 |
| abstract_inverted_index.three | 124 |
| abstract_inverted_index.train | 170 |
| abstract_inverted_index.using | 107, 165, 175 |
| abstract_inverted_index.where | 85 |
| abstract_inverted_index.finite | 92 |
| abstract_inverted_index.labels | 164 |
| abstract_inverted_index.method | 94, 135, 179 |
| abstract_inverted_index.neural | 43, 46, 71, 101 |
| abstract_inverted_index.paper, | 66 |
| abstract_inverted_index.solver | 75, 88, 120, 174, 193 |
| abstract_inverted_index.state, | 133 |
| abstract_inverted_index.steady | 132 |
| abstract_inverted_index.tackle | 58 |
| abstract_inverted_index.Fourier | 70, 100 |
| abstract_inverted_index.Solving | 0 |
| abstract_inverted_index.analyze | 113 |
| abstract_inverted_index.between | 50 |
| abstract_inverted_index.capable | 195 |
| abstract_inverted_index.complex | 1 |
| abstract_inverted_index.crucial | 13 |
| abstract_inverted_index.growing | 31 |
| abstract_inverted_index.labels, | 141 |
| abstract_inverted_index.method. | 111 |
| abstract_inverted_index.optimal | 177 |
| abstract_inverted_index.partial | 9 |
| abstract_inverted_index.predict | 104 |
| abstract_inverted_index.propose | 68 |
| abstract_inverted_index.results | 187 |
| abstract_inverted_index.solver) | 78 |
| abstract_inverted_index.solvers | 25 |
| abstract_inverted_index.spaces, | 52 |
| abstract_inverted_index.various | 15 |
| abstract_inverted_index.vesicle | 184 |
| abstract_inverted_index.without | 130 |
| abstract_inverted_index.Finally, | 168 |
| abstract_inverted_index.achieved | 157 |
| abstract_inverted_index.boundary | 110 |
| abstract_inverted_index.dynamics | 23 |
| abstract_inverted_index.function | 51 |
| abstract_inverted_index.immersed | 109 |
| abstract_inverted_index.learning | 48 |
| abstract_inverted_index.mappings | 49 |
| abstract_inverted_index.one-step | 137 |
| abstract_inverted_index.operator | 47, 102, 161 |
| abstract_inverted_index.training | 126, 134, 159, 178 |
| abstract_inverted_index.vesicle. | 205 |
| abstract_inverted_index.FNO-based | 118, 172, 191 |
| abstract_inverted_index.capturing | 197 |
| abstract_inverted_index.dynamics. | 185 |
| abstract_inverted_index.efficient | 80 |
| abstract_inverted_index.following | 123 |
| abstract_inverted_index.modeling. | 63 |
| abstract_inverted_index.networks, | 44 |
| abstract_inverted_index.nonlinear | 8 |
| abstract_inverted_index.problems, | 5, 84 |
| abstract_inverted_index.(FNO-based | 76 |
| abstract_inverted_index.approaches | 56 |
| abstract_inverted_index.challenges | 60 |
| abstract_inverted_index.difference | 93 |
| abstract_inverted_index.equations, | 11 |
| abstract_inverted_index.especially | 45 |
| abstract_inverted_index.integrated | 97 |
| abstract_inverted_index.introduced | 54 |
| abstract_inverted_index.multi-step | 140, 163 |
| abstract_inverted_index.prediction | 143 |
| abstract_inverted_index.scientific | 16 |
| abstract_inverted_index.seamlessly | 96 |
| abstract_inverted_index.simulation | 81 |
| abstract_inverted_index.variations | 199 |
| abstract_inverted_index.Traditional | 20 |
| abstract_inverted_index.advancement | 41 |
| abstract_inverted_index.data-driven | 62 |
| abstract_inverted_index.engineering | 18 |
| abstract_inverted_index.interaction | 3, 74 |
| abstract_inverted_index.large-scale | 34 |
| abstract_inverted_index.long-period | 36 |
| abstract_inverted_index.performance | 115, 153 |
| abstract_inverted_index.situations: | 125 |
| abstract_inverted_index.Fortunately, | 38 |
| abstract_inverted_index.differential | 10 |
| abstract_inverted_index.insufficient | 27 |
| abstract_inverted_index.requirements | 32 |
| abstract_inverted_index.simulations. | 37 |
| abstract_inverted_index.steady-state | 166 |
| abstract_inverted_index.applications. | 19 |
| abstract_inverted_index.characterized | 6 |
| abstract_inverted_index.computational | 21 |
| abstract_inverted_index.interpolation | 145, 155 |
| abstract_inverted_index.extrapolation. | 147 |
| abstract_inverted_index.incompressible | 105 |
| abstract_inverted_index.operator-based | 72 |
| abstract_inverted_index.fluid-structure | 2, 73 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile |