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Qin, X., Tang, J., Feng, Y., Bachmann, B. & Fritzson, P. (2016). Efficient index reduction algorithm for large scale systems of differential algebraic equations. Applied Mathematics and Computation, 277, 10-22
Open this publication in new window or tab >>Efficient index reduction algorithm for large scale systems of differential algebraic equations
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2016 (English)In: Applied Mathematics and Computation, ISSN 0096-3003, E-ISSN 1873-5649, Vol. 277, p. 10-22Article in journal (Refereed) Published
Abstract [en]

In many mathematical models of physical phenomenons and engineering fields, such as electrical circuits or mechanical multibody systems, which generate the differential algebraic equations (DAEs) systems naturally. In general, the feature of DAEs is a sparse large scale system of fully nonlinear and high index. To make use of its sparsity, this paper provides a simple and efficient algorithm for index reduction of large scale DAEs system. We exploit the shortest augmenting path algorithm for finding maximum value transversal (MVT) as well as block triangular forms (BTFs). We also present the extended signature matrix method with the block fixed point iteration and its complexity results. Furthermore, a range of nontrivial problems are demonstrated by our algorithm. (C) 2015 Elsevier Inc. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE INC, 2016
Keywords
Differential algebraic equations; Sparsity; Shortest augmenting path; Block triangular forms; Structural analysis
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-125794 (URN)10.1016/j.amc.2015.11.091 (DOI)000369369700002 ()
Note

Funding Agencies|China 973 Project [NKBRPC-201103302402]; National Natural Science Foundation of China [61402537, 91118001]; Youth Innovation Promotion Association CAS [2012335]; China Postdoctoral Science Foundation [2012M521692]; Open Project of Chongqing Key Laboratory of Automated Reasoning and Cognition [CARC2014004]

Available from: 2016-03-08 Created: 2016-03-04 Last updated: 2018-03-26
Fritzson, P. (2015). Introducción al Modelado y Simulación de Sistemas Técnicos y Físicos con Modelica. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Introducción al Modelado y Simulación de Sistemas Técnicos y Físicos con Modelica
2015 (Spanish)Book (Other academic)
Abstract [es]

Domine el modelamiento y simulación usando Modelica, el nuevo poderoso y altamente versátil lenguaje de modelamiento basado en objetos.

Modelica, el nuevo lenguaje de modelamiento de software/hardware orientado a objetos que está ganando una rápida popularidad en el mundo entero, ofrece un acercamiento casi universal al modelamiento y simulación computacional de alto nivel. Modelica maneja un amplio rango de dominios de aplicación, por ejemplo, sistemas mecánicos, eléctricos, de control, y termodinámicos, y facilita el uso de notación general así como el uso de poderosas abstracciones e implementaciones eficientes. Usando el versátil lenguaje de Modelica y su tecnología asociada, este texto presenta un acercamiento orientado a objetos basado en componentes que le hace posible a los lectores dominar rápidamente las bases del modelamiento matemático basado en ecuaciones orientado a objetos (EOO por sus siglas en inglés) y simulación soportado por computadora.

A través de este texto Modelica se usa para ilustrar los diferentes aspectos del modelamiento y la simulación. A la vez, se explican varios conceptos claves del lenguaje Modelica con el uso de ejemplos de modelamiento y simulación. Este libro:

  • Examina los conceptos básicos tales como sistemas, modelos y simulaciones
  • Guía al lector a través del lenguaje Modelica con la ayuda de varios ejemplos paso a paso
  • Introduce el concepto de la clase Modelica y su uso en el modelamiento gráfico y basado en texto.
  • Explora las metodologías de modelamiento para sistemas continuos, discretos e híbridos
  • Presenta una revisión de la Librería Estándar de Modelica y las librerías clave de modelos de Modelica

Los lectores encontrarán una buena cantidad de ejemplos de modelos que simulan aplicaciones en distintos dominios así como ejemplos que combinan varios dominios. Todos los ejemplos y ejercicios en el texto están disponibles a través de DrModelica. Este programa de auto enseñanza electrónico, disponible gratuitamente en el sitio web  que acompaña al texto, guía a los lectores desde ejemplos introductorios y simples hasta ejercicios mas avanzados.

Escrito por el Director del consorcio Open Source Modelica Consortium, Introducción al Modelamiento y Simulación de Sistemas Físicos y Técnicos con Modelica es un libro recomendado para ingenieros y estudiantes interesados en el diseño, modelamiento, simulación y análisis asistido por computador de sistemas técnicos y naturales. Partiendo de conceptos básicos, el texto es ideal para estudiantes quienes desean aprender del modelamiento y la simulación orientado a objetos.

Este libro está enfocado en la enseñanza del modelamiento y simulación usando Modelica para principiantes, o en cursos donde hay limitado espacio de tiempo para una introducción a Modelica. Para un cubrimiento con mayor profundidad de este tópico se recomienda el libro Principles of Object-Oriented Modeling and Simulation with Modelica 3.3: A Cyber-Physical Approach, el cual también incluye el material introductorio de este libro.

Abstract [en]

Master modeling and simulation using Modelica, the new powerful, highly versatile object-based modeling language

Modelica, the new object-based software/hardware modeling language that is quickly gaining popularity around the world, offers an almost universal approach to high-level computational modeling and simulation. It handles a broad range of application domains, for example mechanics, electrical systems, control, and thermodynamics, and facilitates general notation as well as powerful abstractions and efficient implementations. Using the versatile Modelica language and its associated technology, this text presents an object-oriented, component-based approach that makes it possible for readers to quickly master the basics of computer-supported equation-based object-oriented (EOO) mathematical modeling and simulation.

Throughout the text, Modelica is used to illustrate the various aspects of modeling and simulation. At the same time, a number of key concepts underlying the Modelica language are explained with the use of modeling and simulation examples. This book:

  • Examines basic concepts such as systems, models, and simulations

  • Guides readers through the Modelica language with the aid of several step-by-step examples

  • Introduces the Modelica class concept and its use in graphical and textual modeling

  • Explores modeling methodology for continuous, discrete, and hybrid systems

  • Presents an overview of the Modelica Standard Library and key Modelica model libraries

Readers will find plenty of examples of models that simulate distinct application domains as well as examples that combine several domains. All the examples and exercises in the text are available via DrModelica. This electronic self-teaching program, freely available on the text's companion website, guides readers from simple, introductory examples and exercises to more advanced ones.

Written by the Director of the Open Source Modelica Consortium, Introduction to Modeling and Simulation of Technical and Physical Systems with Modelica is recommended for engineers and students interested in computer-aided design, modeling, simulation, and analysis of technical and natural systems. By building on basic concepts, the text is ideal for students who want to learn modeling, simulation, and object orientation.

This book is aimed at teaching Modelica modeling and simulation to beginners, or in courses where there is only limited time for an introduction to Modelica. For more in-dept coverage of this topic, the book Principles of Object-Oriented Modeling and Simulation with Modelica 3.3: A Cyber-Physical Approach is recommended. That book also includes the introductory material of the small book.

This book is aimed at teaching Modelica modeling and simulation to beginners, or in courses where there is only limited time for an introduction to Modelica.

For more in-dept coverage of this topic, the book Principles of Object-Oriented Modeling and Simulation with Modelica 3.3: A Cyber-Physical Approach is recommended. That book also includes the introductory material of the small book.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. p. 215
Keywords
Modelamiento, Simulación, Sistemas Físicos
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Information Systems
Identifiers
urn:nbn:se:liu:diva-121342 (URN)978-91-7685-924-7 (ISBN)
Available from: 2015-09-15 Created: 2015-09-14 Last updated: 2018-01-11Bibliographically approved
Fritzson, P. (2015). Principles of object-oriented modeling and simulation with Modelica 3.3: a cyber-physical approach (2ed.). New York: John Wiley & Sons
Open this publication in new window or tab >>Principles of object-oriented modeling and simulation with Modelica 3.3: a cyber-physical approach
2015 (English)Book (Other academic)
Abstract [en]

The second edition features improvements and updates of the Modelica language including synchronous clocked constructs, examines basic concepts of cyber-physical, equation-based, object-oriented system modeling and simulation. Prof. Fritzson introduces the Modelica class concept and its use in graphical and textual modeling with several hundred examples from many application areas and explores modeling methodology for continuous, discrete, and hybrid systems; and more.

This text is aimed at System Modeling and Simulation engineers, control engineers, mechanical engineers, those working with CAD (Computer Aided Design), virtual reality, biochemistry, embedded systems, and data communication.

Fritzson covers the Modelica language in impressive depth from the basic concepts such as cyber-physical, equation-base, object-oriented, system, model, and simulation, while also incorporating over a hundred exercises and their solutions for a tutorial, easy-to-read experience.

  • The only book with complete Modelica 3.3 coverage
  • Over one hundred exercises and solutions
  • Examines basic concepts such as cyber-physical, equation-based, object-oriented, system, model, and simulation

Place, publisher, year, edition, pages
New York: John Wiley & Sons, 2015. p. 1256 Edition: 2
Keywords
Modelica, Object-oriented methods (Computer science), Computer simulation, Databehandling, Datorsimulering, Objektorientering
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-109724 (URN)9781118859124 (ISBN)
Note

                     

Available from: 2014-08-26 Created: 2014-08-26 Last updated: 2018-03-26Bibliographically approved
Samlaus, R. & Fritzson, P. (2015). Semantic validation of physical models using role models. Simulation (San Diego, Calif.), 91(4), 383-399
Open this publication in new window or tab >>Semantic validation of physical models using role models
2015 (English)In: Simulation (San Diego, Calif.), ISSN 0037-5497, E-ISSN 1741-3133, Vol. 91, no 4, p. 383-399Article in journal (Refereed) Published
Abstract [en]

The complexity of models for the simulation of physical systems is steadily increasing. This makes the effective validation of models for different design aspects crucial. One of the many important aspects is the structural correctness and the behavior due to design parameters which are of particular concern for the modeling of wind turbines. This article presents a design and implementation of a role-based validation framework. The framework allows for the creation of validation rules for different design aspects. This is done by role models that are used to define restrictions for an aspect by roles and rules. Multiple role models can be combined to cover all design features during model development. Restrictions on how models can interact with each other can be defined, which broadens language-specific restriction capabilities. The resulting rules can then be tested on arbitrary models based on the Eclipse Modeling Framework, for which mapping between elements of the role model and elements of the validated modeling language must be provided. In the domain of wind turbines, this approach is evaluated by application to two kinds of modeling languages (Modelica and UML2). Role models and rules have shown to be easily described with the frameworks role model language and role model definitions are successfully re-used by the definition of mappings for both kinds of modeling languages.

Place, publisher, year, edition, pages
SAGE Publications (UK and US), 2015
Keywords
Modelica; OneModelica; role models; validation; semantic constraints
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-118063 (URN)10.1177/0037549715580174 (DOI)000353448600006 ()
Note

Funding Agencies|Federal Ministry for the Environment, Nature Conservation and Nuclear Safety of the Parliament of the Federal Republic of Germany; ELLIIT project; Swedish Strategic Research Foundation in the EDOp projects; Vinnova in the RTSIM project; Vinnova in the ITEA2 MODRIO project

Available from: 2015-05-20 Created: 2015-05-20 Last updated: 2018-01-11
Thiele, B. A., Knoll, A. & Fritzson, P. (2015). Towards Qualifiable Code Generation from a Clocked Synchronous Subset of Modelica. Modeling, Identification and Control, 36(1), 23-52
Open this publication in new window or tab >>Towards Qualifiable Code Generation from a Clocked Synchronous Subset of Modelica
2015 (English)In: Modeling, Identification and Control, ISSN 0332-7353, E-ISSN 1890-1328, Vol. 36, no 1, p. 23-52Article in journal (Refereed) Published
Abstract [en]

So far no qualifiable automatic code generators (ACGs) are available for Modelica. Hence, digital control applications can be modeled and simulated in Modelica, but require tedious additional efforts (e.g., manual reprogramming) to produce qualifiable target system production code. In order to more fully leverage the potential of a model-based development (MBD) process in Modelica, a qualifiable automatic code generator is needed. Typical Modelica code generation is a fairly complex process which imposes a huge development burden to any efforts of tool qualification. This work aims at mapping a Modelica subset for digital control function development to a well-understood synchronous data-flow kernel language. This kernel language allows to resort to established compilation techniques for data-flow languages which are understood enough to be accepted by certification authorities. The mapping is established by providing a translational semantics from the Modelica subset to the synchronous data-flow kernel language. However, this translation turned out to be more intricate than initially expected and has given rise to several interesting issues that require suitable design decisions regarding the mapping and the language subset.

Place, publisher, year, edition, pages
Norsk Forening for Automatisering (Norwegian Society of Automatic Control), 2015
Keywords
Modelica; Automatic Code Generation; Model-Based Development; Safety-Relevant Systems
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-117266 (URN)10.4173/mic.2015.1.3 (DOI)000351718000003 ()
Note

Funding Agencies|German Aerospace Center (DLR)

Available from: 2015-04-22 Created: 2015-04-21 Last updated: 2018-01-11
Schamai, W., Buffoni, L. & Fritzson, P. (2014). An Approach to Automated Model Composition Illustrated in the Context of Design Verification. Modeling, Identification and Control, 35(2), 79-91
Open this publication in new window or tab >>An Approach to Automated Model Composition Illustrated in the Context of Design Verification
2014 (English)In: Modeling, Identification and Control, ISSN 1890-1328, Vol. 35, no 2, p. 79-91Article in journal (Refereed) Published
Abstract [en]

Building complex systems form models that were developed separately without modifying existing code is a challenging task faced on a regular basis in multiple contexts, for instance, in design verification. To address this issue, this paper presents a new approach for automating the dynamic system model composition. The presented approach aims to maximise information reuse, by defining the minimum set of information that is necessary to the composition process, to maximise decoupling by removing the need for explicit interfaces and to present a methodology with a modular and structured approach to composition. Moreover the presented approach is illustrated in the context of system design verification against requirements using a Modelica environment, and an approach for expressing the information necessary for automating the composition is formalized.

Place, publisher, year, edition, pages
Norwegian Society of Automatic Control, 2014
Keywords
Bindings, model composition, requirement formalization, design verification
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-109730 (URN)10.4173/mic.2014.2.2 (DOI)000344366300002 ()
Available from: 2014-08-27 Created: 2014-08-27 Last updated: 2014-12-09Bibliographically approved
Rogovchenko, O., Tundis, A., Zoheb Hossain, M., Nyberg, M. & Fritzson, P. (2014). An integrated toolchain for model based functional safety analysis. Journal of Computational Science, 5(3), 408-414
Open this publication in new window or tab >>An integrated toolchain for model based functional safety analysis
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2014 (English)In: Journal of Computational Science, ISSN 1877-7503, E-ISSN 1877-7511, Vol. 5, no 3, p. 408-414Article in journal (Refereed) Published
Abstract [en]

The significant increase in the complexity and autonomy of the hardware systems renders the verification of the functional safety of each individual component as well as of the entire system a complex task and underlines the need for integrated, model based tools that would assist this process. In this paper the authors present such a tool, coupled with an approach to functional safety analysis, based on the integration of functional tests into the model itself. The analysis of the resulting model is done through a stochastic Bayesian model. This approach strives to both bypass the necessity for costly hardware testing and integrate the functional safety analysis into an intuitive component development process.

Place, publisher, year, edition, pages
Elsevier, 2014
Keywords
Bayesian networks; Safety analysis; Model-based design; Functional testing
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-109200 (URN)10.1016/j.jocs.2013.08.009 (DOI)000337873700013 ()
Available from: 2014-08-12 Created: 2014-08-11 Last updated: 2018-01-11Bibliographically approved
Gebremedhin, M. & Fritzson, P. (2014). Automatic Task Based Analysis and Parallelization in the Context of Equation Based Languages. In: EOOLT '14 Proceedings of the 6th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools: . Paper presented at The 6th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools, (EOOLT'2014), Berlin, Germany, October 9. (pp. 49-52). New York: ACM
Open this publication in new window or tab >>Automatic Task Based Analysis and Parallelization in the Context of Equation Based Languages
2014 (English)In: EOOLT '14 Proceedings of the 6th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools, New York: ACM , 2014, p. 49-52Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an automatic parallelization approach for handling complex task systems with heavy dependencies, including methods of analyzing dependencies, representing them in a convenient way, and processing the resulting task graph representation. We present a library-based task system representation, clustering, profiling, and scheduling approach to simplify the otherwise tedious process of parallelizing complex task systems. We have implemented a flexible and robust task system handling library to manipulate and parallelize these complex task systems on shared memory multi-core and multi-processor systems. The implementation has been developed as part of the OpenModelica simulation environment. We demonstrate methods of extracting and utilizing parallelism in the context of mathematical modeling languages.

Place, publisher, year, edition, pages
New York: ACM, 2014
Keywords
Task Parallel, Multi-core, Modeling, Simulation, Parallel Simulation, Modelica, OpenModelica
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-114208 (URN)10.1145/2666202.2666210 (DOI)978-1-4503-2953-8 (ISBN)
Conference
The 6th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools, (EOOLT'2014), Berlin, Germany, October 9.
Available from: 2015-02-13 Created: 2015-02-13 Last updated: 2015-05-20Bibliographically approved
Sjölund, M., Fritzson, P. & Pop, A. (2014). Bootstrapping a Compiler for an Equation-Based Object-Oriented Language. Modeling, Identification and Control, 35(1), 1-19
Open this publication in new window or tab >>Bootstrapping a Compiler for an Equation-Based Object-Oriented Language
2014 (English)In: Modeling, Identification and Control, ISSN 0332-7353, E-ISSN 1890-1328, Vol. 35, no 1, p. 1-19Article in journal (Refereed) Published
Abstract [en]

What does it mean to bootstrap a compiler, and why do it? This paper reports on the first bootstrapping of a full-scale EOO (Equation-based Object-Oriented) modeling language such as Modelica. Bootstrapping means that the compiler of a language can compile itself. However, the usual application area for the Modelica is modeling and simulation of complex physical systems. Fortunately it turns out that with some minor extensions, the Modelica language is well suited for the modeling of language semantics. We use the name MetaModelica for this slightly extended Modelica. This is a prerequisite for bootstrapping which requires that the language can be used to model and/or implement itself. The OpenModelica Compiler (OMC) has been written in this MetaModelica language. It originally supported only the standard Modelica language but has been gradually extended to also cover the MetaModelica language extensions. After substantial work, OMC is able to quickly compile itself and produces an executable with good performance. The benefits include a more extensible and maintainable compiler by introducing improved language constructs and a more powerful runtime that makes it easy to add functionality such as parser generators, debuggers, and profiling tools. Future work includes extracting and restructuring parts of OMC, making the compiler smaller and more modular and extensible. This will also make it easier to interface with OMC, making it possible to create more powerful and user-friendly OpenModelica-based tools. The compiler and its bootstrapping is a major effort -- it is currently about 330 000 lines of code, and the MetaModelica extensions are used routinely by approximately ten developers on a daily basis. 

Place, publisher, year, edition, pages
Norwegian Society of Automatic Control, 2014
Keywords
compilation, equation-based, object-oriented, meta-programming, modeling
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-104894 (URN)10.4173/mic.2014.1.1 (DOI)000333248800001 ()
Available from: 2014-03-02 Created: 2014-03-02 Last updated: 2018-01-11Bibliographically approved
Rogovchenko, O. & Fritzson, P. (2014). Expressing Requirements in Modelica. In: : . Paper presented at In Proceedings of the 55th Scandinavian Conference on Simulation and Modeling (SIMS’2014),Aalborg, Denmark, Oct 21-22..
Open this publication in new window or tab >>Expressing Requirements in Modelica
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

As cyber-physical systems grow increasingly complex, the need for methodologies and tool support for an automated requirement verification process becomes evident. Expressing requirements in a computable form becomes a crucial step in defining such a process. The equation based declarative nature of the Modelica language makes it an ideal candidate for modeling a large subset of system requirements. Moreover, modeling both the requirements and the system itself in the same language presents numerous advantages. However, a certain semantic gap subsists between the notions used in requirement modeling and the concepts of cyber-physical modeling that Modelica relies on. To bridge this gap, in this paper, we illustrate through the use of dedicated types, pseudo function calls and function block libraries, how the Modelica language can be tailored to fit the needs of requirement modeling engineers.

Keywords
Requirements, Equation-based modeling
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-114207 (URN)
Conference
In Proceedings of the 55th Scandinavian Conference on Simulation and Modeling (SIMS’2014),Aalborg, Denmark, Oct 21-22.
Available from: 2015-02-13 Created: 2015-02-13 Last updated: 2015-03-02Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3435-4996

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