Data-driven modeling of multiscale phenomena with applications to fluid turbulence
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913028308467712 |
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| author | Choi, Brandon Ugliotti, Matteo Reynoso, Mateo Gurevich, Daniel R. Grigoriev, Roman O. |
| author_facet | Choi, Brandon Ugliotti, Matteo Reynoso, Mateo Gurevich, Daniel R. Grigoriev, Roman O. |
| contents | This paper introduces a novel data driven framework for constructing accurate and general equivariant models of multiscale phenomena which does not rely on specific assumptions about the underlying physics. This framework is illustrated using incompressible fluid turbulence as an example that is representative, practically important, reasonably simple, and exceedingly well studied. We use direct numerical simulations of freely decaying turbulence in two spatial dimensions to infer an effective field theory comprising explicit, interpretable evolution equations for both the large (resolved) and small (modeled) scales. The resulting closed system of equations is capable of accurately describing the effect of small scales, including backscatter -- the flow of energy from small to large scales, which is particularly pronounced in two dimensions -- which is an outstanding challenge that, to our knowledge, no existing alternative successfully tackles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_09847 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Data-driven modeling of multiscale phenomena with applications to fluid turbulence Choi, Brandon Ugliotti, Matteo Reynoso, Mateo Gurevich, Daniel R. Grigoriev, Roman O. Fluid Dynamics Computational Physics This paper introduces a novel data driven framework for constructing accurate and general equivariant models of multiscale phenomena which does not rely on specific assumptions about the underlying physics. This framework is illustrated using incompressible fluid turbulence as an example that is representative, practically important, reasonably simple, and exceedingly well studied. We use direct numerical simulations of freely decaying turbulence in two spatial dimensions to infer an effective field theory comprising explicit, interpretable evolution equations for both the large (resolved) and small (modeled) scales. The resulting closed system of equations is capable of accurately describing the effect of small scales, including backscatter -- the flow of energy from small to large scales, which is particularly pronounced in two dimensions -- which is an outstanding challenge that, to our knowledge, no existing alternative successfully tackles. |
| title | Data-driven modeling of multiscale phenomena with applications to fluid turbulence |
| topic | Fluid Dynamics Computational Physics |
| url | https://arxiv.org/abs/2511.09847 |