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221 to 230 of 188,324 Results
01_json_schema_address.schema.json
Sep 10, 2026 - Replication data for: Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach
JSON - 580 B - MD5: 577af37d520a9d885510471fa7f60793
Replication Data for: Numerical Investigation of Flash Evaporation of the Combined Injection of Liquid Oxygen and Gaseous Methane/Hydrogen
Sep 9, 2026 - Institute for Reactive Flows (IRST)
Sessler, Christian; Gärtner, Jan Wilhelm; Kronenburg, Andreas, 2026, "Replication Data for: Numerical Investigation of Flash Evaporation of the Combined Injection of Liquid Oxygen and Gaseous Methane/Hydrogen", https://doi.org/10.18419/DARUS-5667, DaRUS, V1
General Information This dataset contains the OpenFOAM case files to generate the published data in: C. Sessler, J. W. Gärtner and A. Kronenburg, "Numerical Investigation of Flash Evaporation of the Combined Injection of Liquid Oxygen and Gaseous Methane/Hydrogen", Multiphase Science and Technology, Volume 37, Issue 4, 2025, pp. 1-19, doi: 10.1615/...
SESSLER_ICMF_2025.tar.zst
Sep 9, 2026 - Replication Data for: Numerical Investigation of Flash Evaporation of the Combined Injection of Liquid Oxygen and Gaseous Methane/Hydrogen
Unknown - 82.4 GB - MD5: 2779162a7303e307fdc2cd077180631c
Data
TAR archive
Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Sep 9, 2026 - Projects without PN Affiliation
Herkert, Robin, 2026, "Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation", https://doi.org/10.18419/DARUS-6155, DaRUS, V2
This dataset includes the code and numerical data to reproduce the results from the paper titled "Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation" (2026). The data were generated by the provided Python scripts from Hamiltonian test systems and are organized according to the corresp...
auxFunctions.py
Sep 9, 2026 - Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Python Source Code - 1.6 KB - MD5: cebc576cf59b39041dfa80c759309759
auxFunctions.py
Sep 9, 2026 - Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Python Source Code - 1.2 KB - MD5: 90c626c3ace81090ebde9564fc097c8c
data.py
Sep 9, 2026 - Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Python Source Code - 10.7 KB - MD5: b920078a94f74b38ad4180c84324c259
data.py
Sep 9, 2026 - Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Python Source Code - 17.9 KB - MD5: 0abcee37f6e300562eb7c5637f288056
DirectParamPendulumData_dT=0.025
Sep 9, 2026 - Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Unknown - 5.7 MB - MD5: 576b9b62d5862e0f01124ce4e53dcde3
DirectParamPendulumData_dT=0.05
Sep 9, 2026 - Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation
Unknown - 5.7 MB - MD5: fcc9503d000a7601a9135d6f31b1ca3d
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