FMICore.jl implements the low-level equivalents of the C-functions and C-data types of the FMI-standard (fmi-standard.org) for the Julia programming language. FMICore.jl provides the foundation for the Julia packages FMIImport.jl and FMIExport.jl.
Please note: FMICore.jl is not meant to be used as it is, but as part of FMI.jl, FMIImport.jl, FMIExport.jl and FMIFlux.jl. However you can install FMICore.jl by following these steps.
1. Open a Julia-REPL, switch to package mode using ], activate your preferred environment.
2. Install FMICore.jl:
(@v1.6) pkg> add FMICore3. If you want to check that everything works correctly, you can run the tests bundled with FMICore.jl:
(@v1.6) pkg> test FMICore
To keep dependencies nice and clean, the original package FMI.jl had been split into new packages:
- FMI.jl: High level loading, manipulating, saving or building entire FMUs from scratch
- FMIImport.jl: Importing FMUs into Julia
- FMIExport.jl: Exporting stand-alone FMUs from Julia Code
- FMICore.jl: C-code wrapper for the FMI-standard
- FMIBuild.jl: Compiler/Compilation dependencies for FMIExport.jl
- FMIFlux.jl: Machine Learning with FMUs (differentiation over FMUs)
- FMIZoo.jl: A collection of testing and example FMUs
FMICore.jl is tested (and testing) under Julia Versions 1.6.6 LTS and latest on Windows latest, Ubuntu latest and MacOS latest. x64 and x86 architectures are tested.
Tobias Thummerer, Lars Mikelsons and Josef Kircher. 2021. NeuralFMU: towards structural integration of FMUs into neural networks. Martin Sjölund, Lena Buffoni, Adrian Pop and Lennart Ochel (Ed.). Proceedings of 14th Modelica Conference 2021, Linköping, Sweden, September 20-24, 2021. Linköping University Electronic Press, Linköping (Linköping Electronic Conference Proceedings ; 181), 297-306. DOI: 10.3384/ecp21181297
Tobias Thummerer, Johannes Stoljar and Lars Mikelsons. 2022. NeuralFMU: presenting a workflow for integrating hybrid NeuralODEs into real-world applications. Electronics 11, 19, 3202. DOI: 10.3390/electronics11193202
Tobias Thummerer, Johannes Tintenherr, Lars Mikelsons. 2021. Hybrid modeling of the human cardiovascular system using NeuralFMUs Journal of Physics: Conference Series 2090, 1, 012155. DOI: 10.1088/1742-6596/2090/1/012155