OpenModelica is a unique large-scale integrated open-source Modelica-and FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica-UML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.
OpenModelica is currently the most complete opensource Modelica-and FMI-based modeling, simulation, optimization, and model-based development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica-UML integration; requirement verification; and generation of parallel code for multi-ore architectures. The environment is based on Modelica and uses an extended version of Modelica for its implementation. This overview paper intends to give an up-to-date brief description of the capabilities of the system, and the main vision behind its development.
We introduce an extension of the classic Discrete Event System Specification (DEVS) formalism that includes stochastic features. Based on the use of the probability spaces theory we define the stochastic DEVS (STDEVS) specification, which provides a formal framework for modeling and simulation of general non-deterministic discrete event systems. The main theoretical properties of the STDEVS framework are treated, including a new definition of legitimacy of models in the stochastic context and a proof of STDEVS closure under coupling. We also illustrate the new stochastic modeling capabilities introduced by STDEVS and their relation with those found in classic DEVS. Practical simulation examples are given involving performance analysis of computer systems and hybrid modeling of networked control systems, applications where the modeling of stochastic components is vital.
We introduce CD ++ Builder, an open-source environment that aims at providing easy-to-use graphical modeling tools to simplify the construction of models and the execution of simulations of complex Discrete Event System Specification (DEVS) models. The architecture and implementation of CD ++ Builder focuses on providing simple definition and reuse of components, offering easy extensibility to support new features. CD ++ Builder includes graphical editors for DEVScoupled models, DEVS-Graphs and C ++ atomic models; it provides code templates that are synchronized with their graphical versions, and it greatly simplifies the software installation and update procedures. We show how this environment can be used to build and simulate DEVS models, and we compare the process with previous versions and other simulation tools, showing that CD ++ Builder can improve model development by creating DEVS models in a completely assisted manner, including advanced graphical interfaces.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.