The paper presents a contribution to a Modelica benchmark suite. Basic ideas for a tool independent benchmark suite based on Python scripting along with models for testing the performance of Modelica compilers regarding large systems of equation are given. The automation of running the benchmark suite is demonstrated followed by a selection of benchmark results to determine the current limits of Modelica tools and how they scale for an increasing number of equations.
This paper presents a survey on matching algorithms which are required to translate Modelica Models. Several implementations of matching algorithms are benchmarked on a set of physical models from mechanical systems in ODE and DAE representation. The major part of algorithms is based on the Augmenting Paths Method and one algorithm is based on the Push-Relabel Method. The algorithms are implemented in the programming language C and MetaModelica. In addition two cheap matching algorithms are used to jump-start the advanced matching process.
Simulation has become an essential tool in the development of construction machinery. In addition to the validation of technical features, the assessment of man-machine interaction has become more important within complex working environments. In cases where most attention is paid to the human as the operator, simulations have to fulfil special requirements. Allowing the user to interact with the system implies the need for real time simulation as well as flexible hardware integration and a powerful visualisation. Therefore a modular software framework called SAR-TURIS 3 has been developed meeting all these requirements. In order to support flexible multidomain modelling the Modelica language is being used. This paper presents SARTURIS and its applications, focusing on the integration of Modelica based on OpenModelica using the example of a wheel loader. Since OpenModelica is not yet able to deal with the Modelica Multibody library, a Python-based tool called PyMbs has been developed. It allows comfortable description of multibody systems and export to Modelica code as well as other formats.
This paper presents a graph theoretical interpretation of the well-known O(n) algorithm for Multibody systems. It enables Modelica compilers to solve for the unknown accelerations of a Multibody model without the need of inverting a dense mass matrix which would require O(n 3 ) operations.
Modelica is well suited for modelling complex physical systems due to the acausal description it is using. The causalisation of the model is carried out prior to each simulation. A significant part of the causalisation process is the symbolic manipulation and optimisation of the model. Despite the growing interest in Modelica, the capabilities of symbolic manipulation and optimisation are not fully utilized. This paper presents an approach to increase the customisability, access, and reuse of symbolic optimisation by a more modular and flexible design concept. An overview of the common symbolic manipulation and optimisation algorithms of a typical Modelica compiler is presented as well as a general modular design concept for a Modelica compiler backend. The modularisation concept will be implemented in a future version of the OpenModelica compiler.
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