The Complexity Crisis - Using Modeling and Simulation for System Level Analysis and Design

This paper discusses the current state of the art of modeling and simulation environments and proposes a set of enhancements that will be necessary for such environments to meet future demands. Modeling and simulation are categorized in accordance with the size of the models to be handled: component level modeling, device level modeling, and system level modeling. It is shown that the requirements that modeling and simulation environments need to satisfy in order to meet the demands of modelers are vastly different at these three

[1]  François E. Cellier,et al.  Linearly implicit quantization-based integration methods for stiff ordinary differential equations , 2013, Simul. Model. Pract. Theory.

[2]  Ernesto Kofman,et al.  Quantization-Based Simulation of Differential Algebraic Equation Systems , 2003, Simul..

[3]  François E. Cellier.  Combined continuous/discrete system simulation by use of digital computers , 1979 .

[4]  Hilding Elmqvist,et al.  Object-oriented modeling of hybrid systems , 1993 .

[5]  François E. Cellier,et al.  Quantization-Based New Integration Methods for Stiff ODEs. , 2012 .

[6]  Ernesto Kofman,et al.  Quantized state simulation of spiking neural networks , 2012, Simul..

[7]  C. Pantelides.  The consistent intialization of differential-algebraic systems , 1988 .

[8]  Johannes F. Broenink,et al.  Modelica: An International Effort to Design the Next Generation Modelling Language , 1997 .

[9]  Dirk Zimmer,et al.  Equation-based modeling of variable-structure systems , 2010 .

[10]  Hans Olsson,et al.  Balanced Models in Modelica 3.0 for Increased Model Quality , 2008 .

[11]  Robert Braun,et al.  Towards Efficient Distributed Simulation in Modelica using Transmission Line Modeling , 2010, EOOLT.

[12]  E. Hairer,et al.  Stiff differential equations solved by Radau methods , 1999 .

[13]  Paul W. Tuinenga,et al.  SPICE: A Guide to Circuit Simulation and Analysis Using PSpice , 1988 .

[14]  A. D. A. Bueno.  Inductive reasoning and reconstruction analysis: two complementary tools for qualitative fault monitoring of large-scale systems , 1997 .

[15]  Hilding Elmqvist,et al.  DYMOLA - A Structured Model Language for Large Continuous Systems , 1978 .

[16]  Martin Otter,et al.  Hybrid modeling in Modelica based on the synchronous data flow principle , 1999, Proceedings of the 1999 IEEE International Symposium on Computer Aided Control System Design (Cat. No.99TH8404).

[17]  R. R. Ryan,et al.  ADAMS — Multibody System Analysis Software , 1990 .

[18]  François E. Cellier,et al.  A novel parallelization technique for DEVS simulation of continuous and hybrid systems , 2013, Simul..

[19]  Hans Olsson,et al.  Dynamic Selection of States in Dymola , 2000 .

[20]  Kilian Link,et al.  Deficiencies of Modelica and its simulation environments for large fluid systems , 2009 .

[21]  François E. Cellier,et al.  Simulating Modelica models with a Stand-Alone Quantized State Systems Solver , 2012 .

[22]  Peter Fritzson.  The Modelica Standard Library , 2011 .

[23]  Bernhard Bachmann,et al.  Fast Simulation of Fluid Models with Colored Jacobians , 2012 .

[24]  Jean-Marc Jézéquel,et al.  Meta-model Pruning , 2009, MoDELS.

[25]  Adeel Asghar,et al.  Static and Dynamic Debugging of Modelica Models , 2012 .

[26]  François E. Cellier,et al.  Continuous system modeling , 1991 .

[27]  Hilding Elmqvist,et al.  Methods for Tearing Systems of Equations in Object-Oriented Modeling , 1994 .

[28]  H. Elmqvist,et al.  Automated formula manipulation supports object-oriented continuous-system modeling , 1993, IEEE Control Systems.

[29]  David J. Murray-Smith,et al.  Continuous System Simulation , 1994 .