Keywords: dynamic decoupling; model partitioning; efficient simulation code generation
Proceedings of the 5th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools; April 19; University of Nottingham; Nottingham; UK
 A. Antoulas. Approximation of large-scale dynamical systems; volume 6 of Advances in Design And Control. SIAM; 2005.
 A. Bartolini; A. Leva; and C. Maffezzoni. A process simulation environment based on visual programming and dynamic decoupling. Simulation; 71(3):183–193; 1998.
 F. Casella; A. Leva; and C.Maffezzoni. Dynamic simulation of a condensation plate column by dynamic decoupling. In Proc. EUROSIM ’98; Espoo 1998; pages 368–374; 1998.
 F. Casella and C. Maffezzoni. Exploiting weak interactions in object-oriented modeling. Simulation News Europe; 22:8–10; 1998.
 F. Cellier and E. Kofman. Continuous system simulation. Springer; 2006.
 J. Chen and S.-M. Kang. Model-order reduction of nonlinear MEMS devices through arclength-based Karhunen- Loeve decomposition. In The 2001 IEEE Int. Symp. on Circuits and Systems; volume 3; pages 457–460; 2001.
 J. Chen; S.-M. Kang; J. Zou; C. Liu; and J. Schutt-Aine. Reduced-order modeling of weakly nonlinear MEMS devices with Taylor-series expansion and Arnoldi approach. J. of Microelectromechanical Systems; 13(3):441– 451; 2004.
 P. Fritzson. Principles of Object-Oriented Modeling and Simulation with Modelica 2.1. Wiley; 2003.
 L. Goldberg and G. Ann. Efficient algorithms for listing combinatorial structures; volume 5. Cambridge Univ Pr; 2009.
 M. Innocent; P. Wambacq; S. Donnay; H. Tilmans; W. Sansen; and H. De Man. An analytic volterra-seriesbased model for a mems variable capacitor. IEEE Trans. on Computer-Aided Design of Integrated Circuits and Systems; 22(2):124–131; 2003.
 S. Lall; J. Marsden; and S. Glavaski. A subspace approach to balanced truncation for model reduction of nonlinear control systems. Int. J. of Robust and Nonlinear Control; 12:519–535; 2002.
 L. Mikelsons and T. Brandt. Symbolic model reduction for interval-valued scenarios. In ASME Conf. Proc.; volume 49002; pages 263–272. ASME; 2009.
 L.Mikelsons and T. Brandt. Generation of continuously adjustable vehicle models using symbolic reduction methods. Multibody System Dynamics; 26:153–173; 2011.
 A. V. Papadopoulos; J. Åkesson; F. Casella; and A. Leva. Automatic partitioning and simulation of weakly coupled systems. Technical report; Politecnico di Milano; 2013.
 J. R. Phillips. Projection frameworks for model reduction of weakly nonlinear systems. In Proc. of the 37th Annual Design Automation Conf.; DAC ’00; pages 184–189; New York; NY; USA; 2000. ACM.
 J. Scherpen. Balancing for nonlinear systems. Systems & Control Letters; 21(2):143–153; 1993.
 A. Schiela and H. Olsson. Mixed-mode integration for realtime simulation. In Modelica Workshop 2000 Proc.; pages 69–75; 2000.
 M. Sjölund; R. Braun; P. Fritzson; and P. Krus. Towards efficient distributed simulation in modelica using transmission line modeling. In 3rd Int. workshop on Equation-Based Object-Oriented Modeling Languages and Tools; pages 71– 80; 2010.
 R. Tarjan. Depth-first search and linear graph algorithms. SIAM J. on Computing; 1(2):146–160; 1971.
 R. Tarjan. Enumeration of the elementary circuits of a directed graph. SIAM J. on Computing; 2(3):211–216; 1972.