Work

Benchmarking the Modular Structural Analysis Algorithm

Year: 2025

Type: conference-paper

Abstract: In a 2023 Modelica Conference paper, we proposed a novelmethod for the modular structural analysis of DAE systems,in which the structural analysis is not performed onflattened models, but rather at the class level. A newnotion of structural interface was proposed, in whichclasses are enriched with context information. That paperdeveloped our approach based on a few illustrative examples.In this paper, we provide the details of our algorithm. Itsperformance depends on the system architecture: theanalysis of models having a small number of classes (possi-bly instantiated many times), with a low treewidth systemarchitecture, scales up very efficiently with thisapproach. We then present additional benchmarks, amongwhich a urban heating network, a representative real-lifeexample on which a near-logarithmic scaling up is shown.

Source: Linköping electronic conference proceedings

DOI: 10.3384/ecp218175

Authors: Benoît Caillaud, Albert Benveniste, Mathias Malandain

Institution: Centre Inria de l'Université de Rennes

Language: English

Topic: Modeling and Simulation Systems

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4415503495

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