Relevant bibliographies by topics / Modelica

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Modelica'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Modelica"

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A. Razak, Amir. "Overview of Wind Turbine Modeling in Modelica Language." International Journal of Engineering and Technology 4, no. 5 (2012): 551–53. http://dx.doi.org/10.7763/ijet.2012.v4.430.

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Tian, Guang Shu, and Li Chen Zhang. "Multi-Domain Modeling and Co-Simulation Based on Modelica and Simulink." Applied Mechanics and Materials 596 (July 2014): 927–30. http://dx.doi.org/10.4028/www.scientific.net/amm.596.927.

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A co-simulation solution based on multi-domain modeling with Modelica is proposed to achieve the co-simulation of multi-domain modeling and simulation environment with other simulation environment . Based on the connection mechanism of multi-domain Modelica models the co-simulation under S-function co-simulation framework is implemented using the converting principle between Modelica models and Simulink modules. A co-simulation example between MWorks which is a multi-domain physical system modeling and simulation tool based on Modelica and AMESim indicates that the method can extend the application of Modelica models and achieve the collaborative work with multi-domain modeling and simulation tools and other simulation software.
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PEREIRA REMELHE, MANUEL A., and SEBASTIAN ENGELL. "COMBINING MODELICA MODELS WITH DISCRETE EVENT FORMALISMS FOR SIMULATION USING THE DES/M ENVIRONMENT." International Journal of Software Engineering and Knowledge Engineering 15, no. 02 (April 2005): 349–55. http://dx.doi.org/10.1142/s0218194005001999.

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Technical systems that include complex physical dynamics as well as extensive discrete event control, require powerful modeling and simulation techniques. As the most adequate means for modeling hybrid physical systems, we advocate the use of object-oriented modeling languages such as Modelica. However, the discrete event models often require the use of dedicated graphical editors that cannot be defined appropriately using Modelica. The purpose of the DES/M modeling environment [10] is to provide such editors for different discrete event formalisms and to translate discrete event models automatically into Modelica components such that a discrete event controller can be integrated easily into Modelica models and simulated using standard Modelica software tools. This contribution presents the main concepts used for the representation of several discrete event formalisms in the Modelica language and discusses the class of discrete event formalisms that can be supported by the DES/M environment.
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Li, Zhi Hua, Hong Guang Yang, Jun Yu, and You Ping Gong. "Modeling and Simulation of the PMSM-Precision Reducer System with Modelica." Applied Mechanics and Materials 201-202 (October 2012): 202–7. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.202.

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There is still lack of effective modeling and simulation method for complex electromechanical coupling system. Modelica is a multi-domain unified modeling language to solve the modeling and simulation problems of the complex and heterogeneous physical systems. Dymola is a Modelica-based modeling and simulation platform for the complex physical systems. In this paper, the dynamics model of the permanent magnet synchronous motor (PMSM)-precision reducer system is established using Lagrange-Maxwell equation. The simulation model of this system is set up with Modelica language. The simulation of the system is realized in Dymola. Results show that the system can respond to good static and dynamic characteristics under a given speed for different loads. The dynamics model of the PMSM-precision reducer system can be further used in system control and optimization. The proposed modeling and simulation method based on Modelica may be commonly applied to other complex electromechanical systems.
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Mattsson, Sven Erik, Hilding Elmqvist, and Martin Otter. "Physical system modeling with Modelica." Control Engineering Practice 6, no. 4 (April 1998): 501–10. http://dx.doi.org/10.1016/s0967-0661(98)00047-1.

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Otter, Martin, Matthias Reiner, Jakub Tobolář, Leo Gall, and Matthias Schäfer. "Towards Modelica Models with Credibility Information." Electronics 11, no. 17 (August 30, 2022): 2728. http://dx.doi.org/10.3390/electronics11172728.

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Modeling and simulation is increasingly used in the design process for a wide span of applications. Rising demands and the complexity of modern products also increase the need for models and tools capable to cover areas such as virtual testing, design-space exploration or digital twins, and to provide measures of the quality of the models and the achieved results. The latter is also called credible simulation process. In an article at the International Modelica Conference 2021, we summarized the state of the art and best practice from the viewpoint of a Modelica language user, based on the experience gained in projects in which Modelica models were utilized in the design process. Furthermore, missing features and gaps in the used processes were identified. In this article, new proposals are presented to improve the quality of Modelica models, in particular by adding traceability, uncertainty, and calibration information of the parameters in a standardized way to Modelica models. Furthermore, the new open-source Modelica library Credibility is discussed together with examples to support the implementation of credible Modelica models.
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Proß, Sabrina, and Bernhard Bachmann. "An Advanced Environment for Hybrid Modeling of Biological Systems Based on Modelica." Journal of Integrative Bioinformatics 8, no. 1 (March 1, 2011): 1–34. http://dx.doi.org/10.1515/jib-2011-152.

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Summary Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process.The Modelica-models can be connected to Simulink-models for parameter optimization, sensitivity analysis and stochastic simulation in Matlab.The present paper illustrates the implementation of the Petri Net component models, their usage within the modeling process and the coupling between the Modelica-tool Dymola and Matlab/Simulink. The application is demonstrated by modeling the metabolism of Chinese Hamster Ovary Cells.
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Tundis, Andrea, Lena Buffoni, Peter Fritzson, and Alfredo Garro. "Model-Based Dependability Analysis of Physical Systems with Modelica." Modelling and Simulation in Engineering 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/1578043.

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Modelica is an innovative, equation-based, and acausal language that allows modeling complex physical systems, which are made of mechanical, electrical, and electrotechnical components, and evaluates their design through simulation techniques. Unfortunately, the increasing complexity and accuracy of such physical systems require new, more powerful, and flexible tools and techniques for evaluating important system properties and, in particular, the dependability ones such as reliability, safety, and maintainability. In this context, the paper describes some extensions of the Modelica language to support the modeling of system requirements and their relationships. Such extensions enable the requirement verification analysis through native constructs in the Modelica language. Furthermore, they allow exporting a Modelica-based system design as a Bayesian Network in order to analyze its dependability by employing a probabilistic approach. The proposal is exemplified through a case study concerning the dependability analysis of a Tank System.
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Liu, Jun, Guochen Wang, and Yanyan Luo. "Multi-Domain Modeling Based on Modelica." MATEC Web of Conferences 77 (2016): 07011. http://dx.doi.org/10.1051/matecconf/20167707011.

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Eborn, Jonas, Hubertus Tummescheit, and Karl Johan Åström. "Physical System Modeling with Modelica TM." IFAC Proceedings Volumes 32, no. 2 (July 1999): 6651–56. http://dx.doi.org/10.1016/s1474-6670(17)57136-0.

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Dissertations / Theses on the topic "Modelica"

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Waheed, Adnan. "Support for Modelica Action Code in ModelicaML Models." Thesis, Linköpings universitet, PELAB - Laboratoriet för programmeringsomgivningar, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72164.

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ModelicaML is a UML/Modelica profile to support model-driven development of combined software/hardware UML/Modelica models. In order to support the development and maintenance of large ModelicaML models this thesis work has developed advanced enhancements to the ModelicaML profile, to enable users to more conveniently edit textual parts, i.e., action code, of ModelicaML models. This approach covers many of the concepts present in advanced language editors, i.e., code completion, error markers, as well as indentation and code template user support for developing and maintaining complex models. In large and complex models it is hard to remember all the parameters and values given in textual parts of UML diagrams. It is also very difficult to remember the complete set of components of a ModelicaML model. The ModelicaML enhancements developed in this work now supports features to facilitate advanced usage by showing all the components in just one key press. Two levels of Error Marker support have been developed to help user to find errors anywhere in a model without knowing the details. Moreover, ModelicaML has been extended with features like Modelica syntax highlighting and code completion. Furthermore, this work included upgrading and porting ModelicaML to run on the new Papyrus [13] on the new Eclipse versions. For example, by using the new features introduced in ModelicaML in this work the users do not have to remember all the variables from used base classes and derived classes.
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Akhlagi, Ali. "A Modelica-based framework for modeling and optimization of microgrids." Thesis, KTH, Energiteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263037.

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Microgrids have lately drawn much attention due to their considerable financial benefits and the increasing concerns about environmental issues. A solution that can address different engineering problems - from design to operation - is desired for practical reasons and to ensure consistency of the analyses. In this thesis, the capabilities of a Modelicabased framework is investigated for various microgrid optimization problems. Various sizing and scheduling problems are successfully formulated and optimized using nonlinear and physical component models, covering both electrical and thermal domains. Another focus of the thesis is to test the optimization platform when varying the problem formulation; performance and robustness tests have been performed with different boundary conditions and system setups. The results show that the technology can effectively handle complex scheduling strategies such as Model Predictive Control and Demand Charge Management. In sizing problems, although the platform can efficiently size the components while simultaneously solving for the economical load dispatch for short horizons (weekly or monthly), the implemented approach would require adaptations to become efficient on longer horizons (yearly).
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Hakam, Imran. "ModelicaML Graphical Modeling Environment Based on Eclipse MDT Papyrus." Thesis, Linköpings universitet, PELAB - Laboratoriet för programmeringsomgivningar, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72112.

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The ModelicaML graphicalModeling Language and Modelica/UML profile is a language for the description of continuous-time and discrete-time/event-based system dynamics. Modelica ML uses Papyrus as modelling tool implementation platform which is used for editing models. These models may be expressed in UML withoptional textual statements in Modelica as action language code. For the new version ModelicaML 2.0, the need for support in the new Papyrus M1 version was essential. In this master thesis project, new plug-in functionality was developed that has enhanced the existing functionality of the ModelicaML modelling environment within the Papyrus Eclipse plug-in. This includes handling Modelica modifiers as well as new views and component tree views which provides complete list of components for a selected class.
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Eriksson, Henrik. "Advanced OpenModelica plotting package for Modelica." Thesis, Linköping University, Linköping University, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15075.

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OpenModelica is an open-source based development environment for Modelica coordinated by the Programming Environments Laboratory (PELAB) at Linköpings Universitet. Previously an external tool, PtPlot, has been used to create graphics from simulation data. This tool is poorly integrated with OMNotebook, the OpenModelica Notebook, which is a tool for creating interactive documents where Modelica code can be edited and evaluated. This thesis develops and implements a plotting API accessible from Modelica algorithmic code and extends OMNotebook to allow creation of diagrams and other forms of graphics without an external application.These diagrams are more customizable than those generated by PtPlot and allow for example logarithmic scaling. The new Modelica API for graphic programming allows access of graphic functionality from within Modelica models and Modelica functions.

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Hagernäs, Mikael. "Att lösa reglertekniska problem med Modelica." Thesis, Linköping University, Department of Electrical Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54214.

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The purpose of this thesis is to examine and present the oportunities of solving

control problems using Modelica. This is done by creating some demonstration

examples with exercises. These examples should cover as many types of control

problems as possible. The exercises are aimed for people with basic knowledge

in modeling and automatic control engineering but with little or no knowledge

in Modelica. There are different types of Modelica implementations and the ones

used in this thesis are OpenModelica and MathModelica.

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Ali, Abdul-Amir Ahmed. "Att lösa reglertekniska problem med Modelica." Thesis, Linköpings universitet, Reglerteknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-60744.

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Modelica is a multi-domain and equation-based modeling language. Modelica is based on object-oriented principles and non-causal modeling. The language is constructed to facilitate reuse and decompose models. The models and the modellibrary can modified to design a new nonlinear components. Object-oriented modeling is an excellent way to analyze and study large complex heterogeneous physical systems. The object-oriented modeling approach build on reusing and decomposition of models and non-causal modeling. Modeling physical systems often leads to a DAE system with index 2 or 3. It is required to use automated symbolic manipulation of the DAE system to do the simulation. Modelica need a compiler tool to run the simulation. Dymola is the dominating tool on the market. Through a graphic editor the user can easily model and simulate the physical system.
Objektorienterad modellering är ett utmärkt sätt att analysera och modellera fysikaliska system. Den ger möjlighet att hantera stora, komplexa och blandade system. Modelica är ett exempel på ett multidomän modelleringsspråk som är ekvationsbaserat och hanterar modeller från olika fysikaliska domäner. Det är baserat på principer från objektorientering och hanterar icke-kausala problem. Modelicas struktur gör att befintliga modeller kan delas upp i delmodeller som kan designas och testas oberoende av de andra delmodellerna. Det ger överskådlig bild av fysikaliska systemet. Modellbibliotek i Modelica kan enkelt modifieras för att designa nya komponenter. Modellering av fysikaliska system, speciellt mekaniska eller mekatroniska system ger upphov till DAE system med index 2 eller 3. Det resulterar svårigheter vid simulering av modeller. En automatiserad symbolisk manipulering av DAE systemen behövs för att underlätta simuleringen. För att simulera modeller skrivna i Modelica, behövs en kompilator och ett simuleringsverktyg. Dymola är det dominerande verktyget för dessa ändamål. Man har tillgång till Modelicas standardbibliotek via ett grafiskt gränssnitt. Vid simulering kontrolleras modellen så att Modelicas syntax är uppfylld. Sedan kompileras och simuleras modellen.
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Andersson, Conny. "Design of the Modelica Library VehProLib with Non-ideal Gas Models in Engines." Thesis, Linköpings universitet, Fordonssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121817.

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This thesis covers the reconstruction and the redesign of the modeling library VehProLib,which is constructed in the modeling language Modelica with help of the modeling toolWolfram SystemModeler. The design choices are discussed and implemented. This thesisalso includes the implementation of a turbocharger package and an initial study of the justificationof the ideal gas law in vehicle modeling. The study is made with help of Van derWaals equation of states as a reference of non-ideal gas model. It will be shown that for themean-value-engine-model, the usage of ideal gas law is justified.
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Hemmati, Moghadam Afshin. "Modelica PARallel benchmark suite (MPAR) - a test suite for evaluating the performance of parallel simulations of Modelica models." Thesis, Linköpings universitet, PELAB - Laboratoriet för programmeringsomgivningar, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72685.

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Using the object-oriented, equation-based modeling language Modelica, it is possible to model and simulate computationally intensive models. To reduce the simulation time, a desirable approach is to perform the simulations on parallel multi-core platforms. For this purpose, several works have been carried out so far, the most recent one includes language enhancements with explicit parallel programing language constructs in the algorithmic parts of the Modelica language. This extension automatically generates parallel simulation code for execution on OpenCL-enabled platforms, and it has been implemented in the open-source OpenModelica environment. However, to ensure that this extension as well as future developments regarding parallel simulations of Modelica models are feasible, performing a systematic benchmarking with respect to a set of appropriate Modelica models is essential, which is the main focus of study in this thesis. In this thesis a benchmark test suite containing computationally intensive Modelica models which are relevant for parallel simulations is presented. The suite is used in this thesis as a means for evaluating the feasibility and performance measurements of the generated OpenCL code when using the new Modelica language extension. In addition, several considerations and suggestions on how the modeler can efficiently parallelize sequential models to achieve better performance on OpenCL-enabled GPUs and multi-coreCPUs are also given. The measurements have been done for both sequential and parallel implementations of the benchmark suite using the generated code from the OpenModelica compiler on different hardware configurations including single and multi-core CPUs as well as GPUs. The gained results in this thesis show that simulating Modelica models using OpenCL as a target language is very feasible. In addition, it is concluded that for models with large data sizes and great level of parallelism, it is possible to achieve considerable speedup on GPUs compared to single and multi-core CPUs.
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Nouidui, Thierry Stephane. "Entwicklung einer objektorientierten Modellbibliothek zur Ermittlung und Optimierung des hygrothermischen und hygienischen Komforts in Räumen." [S.l. : s.n.], 2008. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-37291.

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Magnusson, Henrik. "Integrated generic 3D visualization of Modelica models." Thesis, Linköping University, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15453.

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OpenModelica is a complete environment for developing and simulatingModelica models based on free software. It is promoted and developed bythe OpenModelica Consortium. This thesis details a method for describingand consequently displaying visualizations of Modelica models in OMNote-book, an application in the OpenModelica suite where models can be writtenand simulated in a document mixed with text, images and plots. Two dif-ferent approaches are discussed; one based on Modelica annotations and onebased on creating a simple object hierarchy which can be connected to exist-ing models. Trial implementations are done which make it possible to discardthe annotation approach, and show that an object based solution is the onebest suited for a complete implementation. It is expanded into a working 3Dvisualization solution, embedded in OMNotebook.

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Books on the topic "Modelica"

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Tiller, Michael. Introduction to Physical Modeling with Modelica. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1561-6.

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Introduction to physical modeling with Modelica. Boston: Kluwer Academic Publishers, 2001.

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Fritzson, Peter. Principles of Object Oriented Modeling and Simulation with Modelica 3.3. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118989166.

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Principles of object-oriented modeling and simulation with Modelica 2.1. Piscataway, N.J: IEEE Press, 2004.

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Fritzson, Peter. Introduction to Modeling and Simulation of Technical and Physical Systems with Modelica. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118094259.

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Introduction to modeling and simulation of technical and physical systems with Modelica. Hoboken, N.J: Wiley, 2011.

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Fritzson, Peter A. Principles of object oriented modeling and simulation with Modelica 3.3: A cyber-physical approach. Piscataway, New Jersey: IEEE Press/Wiley, 2015.

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Lesh, Richard, Peter L. Galbraith, Christopher R. Haines, and Andrew Hurford, eds. Modeling Students' Mathematical Modeling Competencies. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6271-8.

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Lesh, Richard, Peter L. Galbraith, Christopher R. Haines, and Andrew Hurford, eds. Modeling Students' Mathematical Modeling Competencies. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-0561-1.

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McDuffie, Amy Roth, ed. Mathematical Modeling and Modeling Mathematics. Reston, VA: National Council of Teachers of Mathematics, 2016.

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Book chapters on the topic "Modelica"

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Schmitt, Thomas Lienhard, and Markus Andres. "Modelica." In Methoden zur Modellbildung und Simulation mechatronischer Systeme, 403–92. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-25089-8_7.

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Kral, Christian. "Modelica." In Modelica - Objektorientierte Modellbildung von Drehfeldmaschinen, 35–87. München: Carl Hanser Verlag GmbH & Co. KG, 2018. http://dx.doi.org/10.3139/9783446457331.002.

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Schmitt, Thomas Lienhard, and Markus Andres. "Modelica." In Methoden zur Modellbildung und Simulation mechatronischer Systeme, 429–536. Wiesbaden: Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-42761-0_7.

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Campbell, Stephen L., and Ramine Nikoukhah. "Modelica Support." In Modeling and Simulation with Compose and Activate, 387–413. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04885-3_14.

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Kral, Christian. "Modelica Standard Library." In Modelica - Objektorientierte Modellbildung von Drehfeldmaschinen, 319–26. München: Carl Hanser Verlag GmbH & Co. KG, 2018. http://dx.doi.org/10.3139/9783446457331.008.

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Bruder, Frederic, and Lars Mikelsons. "Towards Grey Box Modeling in Modelica." In Robotics and Mechatronics, 203–15. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30036-4_17.

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Tiller, Michael. "Introduction." In Introduction to Physical Modeling with Modelica, 3–15. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1561-6_1.

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Tiller, Michael. "Multi-Domain Modeling." In Introduction to Physical Modeling with Modelica, 231–53. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1561-6_10.

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Tiller, Michael. "Block Diagrams vs. Acausal Modeling." In Introduction to Physical Modeling with Modelica, 255–64. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1561-6_11.

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Tiller, Michael. "Building Libraries." In Introduction to Physical Modeling with Modelica, 265–78. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1561-6_12.

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Conference papers on the topic "Modelica"

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Tiller, Michael, Cleon Davis, Hubertus Tummescheit, and Nizar Trigui. "Powertrain Modeling With Modelica." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-2352.

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Abstract In this paper we will describe the development of models for prediction of powertrain performance. Our goal is to develop a library of components to model combustion, gas dynamics and mechanical response. We will also demonstrate the ease with which we can replace traditional component models (e.g., mechanically actuated valves) with non-traditional component models (e.g., electro-mechanically actuated valves) without having to change or reformulate any of the other components in our system. The models were developed using the Modelica modeling language (Modelica Design Group, 1999) which allows component-based descriptions of behavior for complex engineering systems. Modelica is particularly well suited for creating behavioral models that are typical for powertrain plant models In addition to writing component models, the freely available Modelica Standard Library contains basic models from various engineering disciplines (e.g., resistors, shafts, springs). With this approach, models can be symbolically preprocessed to improve computational performance. In addition, code can be generated from the Modelica model which can be used as either a stand alone analysis tool, imported into Simulink as an S-function or downloaded for use in real-time hardware in the loop experiments.
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Baharev, Ali, and Arnold Neumaier. "Chemical Process Modeling in Modelica." In 9th International MODELICA Conference, Munich, Germany. Linköping University Electronic Press, 2012. http://dx.doi.org/10.3384/ecp12076955.

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Harman, Peter, and Michael Tiller. "Building Modelica Tools using the Modelica SDK." In The 7 International Modelica Conference, Como, Italy. Linköping University Electronic Press, 2009. http://dx.doi.org/10.3384/ecp09430046.

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Liu Chan, Chen Liping, Qu Yan, Zhou Fanli, and Qian Yikai. "Modelica-Based Modeling on LEO Satellite Constellation." In 14th Modelica Conference 2021. Linköping University Electronic Press, 2021. http://dx.doi.org/10.3384/ecp21181163.

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Brück, Dag. "Modelica models in SSP." In 15th International Modelica Conference 2023, Aachen, October 9-11. Linköping University Electronic Press, 2023. http://dx.doi.org/10.3384/ecp204375.

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This is a proposed optional extension for SSP 2.0 that defines how Modelica models can be referenced in SSP. It specifies the mapping of key Modelica concepts to SSP, which necessitates a few small extensions. The purpose is to broaden the scope of SSP to embrace the more powerful modeling concepts of Modelica, for environments that can support it.
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Radil, Lukas, Petr Mastny, and Jan Machacek. "Modeling Vanadium Redox Battery in Modelica." In 2014 15th International Scientific Conference on Electric Power Engineering (EPE). IEEE, 2014. http://dx.doi.org/10.1109/epe.2014.6839505.

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Hailiang Zhang, Zhuoping Yu, Zaimin Zhong, Bonian Wu, and Xinbo Chen. "Modelica based modeling of automotive transmission." In 2014 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific). IEEE, 2014. http://dx.doi.org/10.1109/itec-ap.2014.6940686.

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Drogies, Stefan, and Michael Bauer. "Modeling Road Vehicle Dynamics with Modelica." In SAE 2002 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2002. http://dx.doi.org/10.4271/2002-01-1219.

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Binder, William, Christiaan Paredis, and Humberto Garcia. "Hybrid Energy System Modeling in Modelica." In the 10th International Modelica Conference, March 10-12, 2014, Lund, Sweden. Linköping University Electronic Press, 2014. http://dx.doi.org/10.3384/ecp14096979.

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Kuric, Muhamed, Nedim Osmic, and Adnan Tahirovic. "Multirotor Aerial Vehicle modeling in Modelica." In The 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017. Linköping University Electronic Press, 2017. http://dx.doi.org/10.3384/ecp17132373.

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Reports on the topic "Modelica"

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Wetter, Michael, Wangda Zuo, and Thierry Stephane Nouidui. Modeling of Heat Transfer in Rooms in the Modelica "Buildings" Library. Office of Scientific and Technical Information (OSTI), November 2011. http://dx.doi.org/10.2172/1168737.

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Greenwood, Michael Scott, Sacit M. Cetiner, Thomas J. Harrison, and David Fugate. A Templated Approach for Multi-Physics Modeling of Hybrid Energy Systems in Modelica. Office of Scientific and Technical Information (OSTI), August 2017. http://dx.doi.org/10.2172/1427611.

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Frick, Konor L. Status Report on the NuScale Module Developed in the Modelica Framework. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1569288.

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Frick, Konor, Shannon Bragg-Sitton, and Marisol Garrouste. Validation and Verification for INL Modelica-based TEDS models Via Experimental Results. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1836100.

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Kim, Jong Suk, Shannon M. Bragg-Sitton, and Richard D. Boardman. Status Report on the High-Temperature Steam Electrolysis Plant Model Developed in the Modelica Framework (FY17). Office of Scientific and Technical Information (OSTI), August 2017. http://dx.doi.org/10.2172/1408745.

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Frick, Konor, Shannon Bragg-Sitton, and Cristian Rabiti. Development of the INL Thermal Energy Distribution System (TEDS) in the Modelica Eco-System for Validation and Verification. Office of Scientific and Technical Information (OSTI), July 2020. http://dx.doi.org/10.2172/1668777.

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Kim, Jong Suk, and Konor Frick. Status Report on the Component Models Developed in the Modelica Framework: Reverse Osmosis Desalination Plant & Thermal Energy Storage. Office of Scientific and Technical Information (OSTI), May 2018. http://dx.doi.org/10.2172/1468648.

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Suk Kim, Jong, Michael McKellar, Shannon M. Bragg-Sitton, and Richard D. Boardman. Status on the Component Models Developed in the Modelica Framework: High-Temperature Steam Electrolysis Plant & Gas Turbine Power Plant. Office of Scientific and Technical Information (OSTI), October 2016. http://dx.doi.org/10.2172/1333156.

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Terry, Stephen, and J. Doster. Final Technical Report - Creation of Multiple Effect Evaporator and Combined Cycle Modelica Modules, and Optimization of Potable Water Generation from Saltwater Sources. Office of Scientific and Technical Information (OSTI), April 2023. http://dx.doi.org/10.2172/1971652.

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Modlo, Yevhenii O., Serhiy O. Semerikov, Ruslan P. Shajda, Stanislav T. Tolmachev, and Oksana M. Markova. Methods of using mobile Internet devices in the formation of the general professional component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3878.

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Abstract:
The article describes the components of methods of using mobile Internet devices in the formation of the general professional component of bachelor in electromechanics competency in modeling of technical objects: using various methods of representing models; solving professional problems using ICT; competence in electric machines and critical thinking. On the content of learning academic disciplines “Higher mathematics”, “Automatic control theory”, “Modeling of electromechanical systems”, “Electrical machines” features of use are disclosed for Scilab, SageCell, Google Sheets, Xcos on Cloud in the formation of the general professional component of bachelor in electromechanics competency in modeling of technical objects. It is concluded that it is advisable to use the following software for mobile Internet devices: a cloud-based spreadsheets as modeling tools (including neural networks), a visual modeling systems as a means of structural modeling of technical objects; a mobile computer mathematical system used at all stages of modeling; a mobile communication tools for organizing joint modeling activities.
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