2026-05-27T23:51:32Z
https://www.fdr.uni-hamburg.de/oai2d
oai:fdr.uni-hamburg.de:17687
2026-05-04T07:03:31Z
user-qcfd
user-uhh
true
3.1
UHH.FDR
10.25592/uhhfdm.17687
Nis-luca van Hülst
0009-0004-9893-3614
Universität Hamburg
Pia Siegl
0000-0003-2249-8121
German Aerospace Center
Paul Over
0000-0001-7436-5254
Hamburg University of Technology
Sergio Bengoechea
0009-0001-8205-5878
Hamburg University of Technology
Tomohiro Hashizume
0000-0002-7154-5417
University of Queensland, University of Strathclyde, Universität Hamburg
Mario Guillaume Cecile
0000-0002-2076-6236
CY Cergy Paris University, University of Mauritius
Thomas Rung
0000-0002-3454-1804
Hamburg University of Technology
Dieter Jaksch
0000-0002-9704-3941
University of Hamburg, University of Oxford
Quantum-Inspired Tensor-Network Fractional-Step Method for Incompressible Flow in Curvilinear Coordinates
Universität Hamburg
2025
QCFD
Tensor Networks
Tensor Trains
CFD
Curvilinear Coordinates
Body-Fitted Grids
Fluid Dynamics
MPS
DMRG
2025-07-07
https://www.fdr.uni-hamburg.de/record/oai:fdr.uni-hamburg.de:17687
10.25592/uhhfdm.17686
Creative Commons Attribution 4.0 International
Open Access
<p>Publication data accompanying the paper “Quantum-Inspired Tensor-Network Fractional-Step Method for Incompressible Flow in Curvilinear Coordinates”, published in Computer Physics Communications (DOI: 10.1016/j.cpc.2026.110169). The publication and this dataset are associated with the European Union’s Horizon Europe research and innovation programme (HORIZON-CL4-2021-DIGITAL-EMERGING-02-10) under grant agreement No. 101080085, QCFD (https://doi.org/10.3030/101080085). The dataset contains the simulation data used in the publication, including reference finite-difference results and matrix-product-state (MPS) results for curvilinear incompressible flow benchmarks, covering non-rotating and rotating cylinder cases in steady and transient regimes, as well as additional validation data.</p>