2025-09-10 –, 202
In a 2023 Modelica Conference paper, we proposed a novel method for the modular structural analysis of DAE systems, in which the structural analysis is not performed on flattened models, but rather at the class level. A new notion of structural interface was proposed, in which classes are enriched with context information. That paper developed our approach based on a few illustrative examples.
In this paper, we provide the details of our algorithm. Its performance depends on the system architecture: the analysis of models having a small number of classes (possi- bly instantiated many times), with a low treewidth system architecture, scales up very efficiently with this approach. We then present additional benchmarks, among which a urban heating network, a representative real-life example on which a near-logarithmic scaling up is shown.
Benoît Caillaud is head of the Hycomes team at the Inria center at the university of Rennes, France. His research is on hybrid systems modeling language design. He has contributed algorithms for the structural analysis of multimode DAE systems, with applications to the compilation of multimode Modelica and the health monitoring of multimode systems. His most recent work is focused on the scalability of Modelica tools.
