Published June 12, 2025 | Version v1.0.0
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Dataset of: "Model-based time super-sampling of turbulent flow field sequences"

  • 1. ROR icon Universidad Carlos III de Madrid

Description

Dataset of the article "Model-based time super-sampling of turbulent flow field sequences" (https://doi.org/10.1103/2lqd-g9mt)

This dataset supports the method presented in the article for increasing the temporal resolution of flow field sequences using Galerkin models. It includes the data required to reproduce the results and validate the methodology.

Code repository: https://github.com/erc-nextflow/GalerkinModel

 

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 949085, NEXTFLOW). Views and opinions expressed are, however, those of the authors only, and do not necessarily reflect those of the European Union or the ERC. Neither the European Union nor the granting authority can be held responsible for them.

Files

FluificPinball.zip

Files (9.6 GB)

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md5:6231f2170964f96f9c2a728b59bb6c3e
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md5:912b68403fbb76ada1dbe4c773ab4b88
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md5:d8596d8b3cc8893fc58d83600c1627aa
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Additional details

Identifiers

Funding

European Commission
NEXTFLOW - Next-generation flow diagnostics for control 949085

Software

Repository URL
https://github.com/erc-nextflow/GalerkinModel
Programming language
Python