Replication Data for: Improved super-resolution reconstruction of turbulent flows with spectral loss function

DOI

This repository contains the data and python code to build/train/test the super-resolution model (deep neural network).

Three tar.gz files are provided:

code: contains the code to build/train/test super-resolution models caseSettings: contains the configuration files for the training and testing datasets: contains all the training/validation/test datasets

Identifier
DOI https://doi.org/10.18419/DARUS-5497
Related Identifier IsCitedBy https://doi.org/10.1063/5.0258090
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-5497
Provenance
Creator Cheng, Ruyue ORCID logo
Publisher DaRUS
Contributor Kronenburg, Andreas
Publication Year 2026
Funding Reference China Scholarship Council 202206020071 ; DFG 513858356
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact Kronenburg, Andreas (University of Stuttgart)
Representation
Resource Type Dataset
Format application/gzip
Size 13891; 3985109; 56795016884
Version 1.0
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences; Fluid Mechanics; Heat Energy Technology, Thermal Machines, Fluid Mechanics; Mechanical and industrial Engineering; Mechanics; Mechanics and Constructive Mechanical Engineering; Natural Sciences; Physics; Thermal Engineering/Process Engineering