Python-Based eSES/MB Infrastructure

H. Folkerts


Abstract

The Python-based extended System Entity Structure / Model Base (eSES/MB) infrastructure has been developed by the research group Computational Engineering and Automation (CEA) at Wismar University of Applied Sciences. It is intended to automatically execute a number of simulation experiments using the components in the figure below. It extends the ideas of the SES/MB framework introduced by B.P. Zeigler with new modeling features, methods, and components. These extensions allow the automatic processing of SES as well as automatic model generation and execution.


Extended SES/MB Infrastructure for Modeling and Simulation.


Motivation

Today's simulation softwares provide powerful numerical methods for simulation, but lack comprehensive support for the conceptual modeling phase. In order to tackle this lack, the RG CEA developed the SES Toolbox for MATLAB/Simulink. The toolbox implements the components and methods of the eSES/MB framework and supports model generation for MATLAB/Simulink models, but lacks general interfaces for an Execution Unit and an Experiment Control as well as support for different simulation software. The Python toolset offered on this site provides general interfaces with special focus on the possibilty to support different simulation environments.

Software

The Python-based eSES/MB infrastructure consists of following tools available as OpenSource software at GitHub: The tools have a comprehensive documentation in the file "doc.pdf" in the main directory of each tool. In the documentation of SESToPy an introduction and background information to the eSES/MB infrastructure is given.
Currently SESMoPy supports the simulators Simulink, OpenModelica and Dymola. A general interface supported by a number of simulators is the Functional Mock-up Interface (FMI). Support for FMI in SESMoPy is currently in development.

Usage

For using this infrastructure the following steps need to be taken. Detailed information is provided in the respective documentation. Publications

Folkerts, H., Pawletta, T., Deatcu, C., and Hartmann, S. (2019). A Python Framework for Model Specification and Automatic Model Generation for Multiple Simulators. In: Proc. of ASIM Workshop 2019 - ARGESIM Report 57, ASIM Mitteilung AM 170. ARGESIM/ASIM Pub. TU Vienna, Austria, 02/2019, 69-75. (Print ISBN 978-3-901608-06-3)

2019/03, H. Folkerts