Release of FMIFlux v0.13

FMIFlux allows the integration of FMUs into the SciML ecosystem of Julia. Consequently, the generation of PenODEs or Physics-informed neural networks with FMUs containing the physical equations becomes possible.

FMIFlux makes FMUs available in the Julia programming language as differentiable objects. The required derivatives are either computed directional derivatives from the FMI standard or sampled usinh finite differences. Moreover, this differentation is integrated with the Julia AD tools.

Same as for the Julia programming language, thus platform independent.

See star gazers.

FMIFlux is released under the MIT licence.