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- Titel:
Latent-Space Physics: Towards learning the temporal evolution of fluid flow. Liquid 2D data set with 1000 scenes.
- Dokumenttyp:
- Forschungsdaten
- Verantwortlich:
- Thuerey, Nils
- Autorinnen / Autoren:
- Wiewel, Steffen; Thuerey, Nils
- Institutionszugehörigkeit:
- TUM
- Herausgeber:
- TUM
- Enddatum der Datenerzeugung:
- 28.03.2019
- Fachgebiet:
- DAT Datenverarbeitung, Informatik
- Quellen der Daten:
- Simulationen / simulations
- Datentyp:
- Datenbanken / data bases
- Beschreibung:
- This archive contains a 2D data set of liquid simulations with resolution 64. It contains 1000 scenes, each with 100 frames of data over time. The data can be used to train the autoencoder and LSTM networks of the paper “Latent-space physics: Towards learning the temporal evolution of fluid flow”.
- Links:
- Schlagworte:
- Fluid Simulation; Physics-based Deep Learning; Navier-Stokes
- Technische Hinweise:
- Data format: numpy .npz file format, resolution per temporal frame: 64x64. Contained fields: velocity, surface position as levelset, and 3 pressure fields (full, dynamic, static).
View and download (1 file, 8GB)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1483096):
rsync rsync://m1483096@dataserv.ub.tum.de/m1483096/ - Sprache:
- en
- Rechte:
- by-sa, http://creativecommons.org/licenses/by-sa/4.0
- Horizon 2020:
- ERC StG 637014
BibTeX