modelOverview
Extends from Modelica.Icons.Information (Icon for general information packages).
Information
SMArtInt Library
The SMArtInt Library is designed to integrate various artificial intelligence (AI) models seamlessly into Modelica-based simulation tools. SMArtInt, short for Simple Modelica Artificial Intelligence Interface, provides a user-friendly interface that bridges advanced AI capabilities with the power of Modelica simulations, enhancing both modeling efficiency and simulation accuracy.
Currently, it supports the following tools:
- Dymola
- OpenModelica
- Modelon Impact
- MWorks Sysplorer
With:
- TensorFlow models exported as TFLite
- ONNX models
The repository contains a compiled version of the interface for usage in windows. As a starting point open the Modelica Library. It contains some ready to run examples Tester which demonstrate the usage. The corresponding python files which create the TF-Lite and ONNX models are located in Resources.
Hints for usage in Dymola:
Currently, only a 64-bit version is available. If the variable Advanced.CompileWith64 is set on its default value 0, Dymola will automatically compile a 64-bit Dymosim.exe after giving a remark in the translate log file. In case Advanced.CompileWith64=2 a 64-bit dymosim.exe is created anyway and in case of Advanced.CompileWith64=1 compilation will fail.
Copyright:
SMArtInt uses other software - the source code is included as submodule and/or as compiled version for direct usage:
- Tensorflow (https://github.com/tensorflow/tensorflow)
License: https://github.com/tensorflow/tensorflow/blob/master/LICENSE - Bazel.exe (https://github.com/bazelbuild/bazel)
License: https://github.com/bazelbuild/bazel/blob/master/LICENSE - ClaRa Delay (https://github.com/xrg-simulation/ClaRaDelay)
License: https://github.com/xrg-simulation/ClaRaDelay/blob/main/CSource/LICENSE - ONNX Runtime (https://github.com/microsoft/onnxruntime)
License: https://github.com/microsoft/onnxruntime/blob/main/LICENSE
This work was carried out within the framework of the research project DIZPROVI, supported by the Federal Ministry of Education and Research (number 03WIR0105E).