The consistent intialization of differential-algebraic systems
SIAM Journal on Scientific and Statistical Computing
Solving ordinary differential equations I (2nd revised. ed.): nonstiff problems
Solving ordinary differential equations I (2nd revised. ed.): nonstiff problems
Discrete-event simulation
Introduction to Physical Modeling with Modelica
Introduction to Physical Modeling with Modelica
Continuous System Modeling
Collision Detection Optimization in a Multi-particle System
ICCS '02 Proceedings of the International Conference on Computational Science-Part III
Integrating elementary computational modeling and programming principles (abstract only)
Proceedings of the 43rd ACM technical symposium on Computer Science Education
Developing computational models: some aspects of conceptualization and implementation
Proceedings of the 51st ACM Southeast Conference
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Modeling and simulation skills are two core competences of computational science and thus should be a central part of any curriculum. While there is a well-founded methodology for the design of simulation algorithms today the teaching of modeling skills carries some intrinsic problems. The reason is that modeling is still partly an art and partly a science. As an important consequence for university education, the concepts for teaching modeling must be quite different from those for teaching simulation algorithms. Experiences made with the courses on 'Modeling and Simulation' at the University of Siegen are summarized and some general concepts for the teaching of modeling skills are presented. In particular, three practical approaches to modeling education are discussed with several examples.