Assimulo: A Unified Framework for ODE Solvers

Andersson, Christian; Führer, Claus; Åkesson, Johan (2014). Assimulo: A Unified Framework for ODE Solvers In Technical Report in Mathematical Sciences (1): Centre for Mathematical Sciences, Lund University
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Report | Submitted | English
Authors:
Andersson, Christian ; Führer, Claus ; Åkesson, Johan
Department:
Mathematics (Faculty of Engineering)
Numerical Analysis
Project:
LCCC
Research Group:
Numerical Analysis
Abstract:
During the last three decades, a vast variety of methods to numerically solve ordinary differential equations and differential algebraic equations has been developed and investigated. The methods are mostly freely available in different programming languages and with different interfaces. Accessing them using a unified interface is a need not only of the research community and for education purposes but also to make them available in industrial contexts.



An industrial model of a dynamic system is usually not just a set of differential equations. The models today may contain discrete controllers, impacts or friction resulting in discontinuities that need to be handled by a modern solver in a correct and efficient way. Additionally, the models may produce an enormous amount of data that puts strain on the simulation software.



In this paper, Assimulo is presented which provides a unified high-level interface to solvers of ordinary differential equations. Assimulo not only provides a direct interface but is additionally designed to satisfy the needs in research and in education together with the requirements for solving industrial models with discontinuities and data handling. It unifies original classical and modern solvers independent of their programming language by a well-structured Python / Cython interface. This allows to easily control parameter setting and discontinuity handling for a wide range of problem classes.
Keywords:
Simulation ; Ordinary differential equations ; Differential algebraic equations ; Functional mock-up interface ; Modelica ; Python
ISSN:
1403-9338
LUP-ID:
4329cb7b-ebc8-49b1-80e1-d38672506110 | Link: https://lup.lub.lu.se/record/4329cb7b-ebc8-49b1-80e1-d38672506110 | Statistics

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