Relevant bibliographies by topics / Simulation tools

Contents

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

Academic literature on the topic 'Simulation tools'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 June 2025

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Journal articles on the topic "Simulation tools"

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Grafton, Carl, and Anne Permaloff. "Microcomputer Simulations and Simulation Writing Tools." PS: Political Science and Politics 22, no. 2 (June 1989): 247. http://dx.doi.org/10.2307/419603.

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Grafton, Carl, and Anne Permaloff. "Microcomputer Simulations and Simulation Writing Tools." PS: Political Science & Politics 22, no. 02 (June 1989): 247–57. http://dx.doi.org/10.1017/s1049096500030560.

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Dean, T. D., and M. J. Haney. "FASTBUS simulation tools." IEEE Transactions on Nuclear Science 39, no. 4 (1992): 910–14. http://dx.doi.org/10.1109/23.159731.

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Mukherjee, S. S., S. V. Adve, T. Austin, J. Emer, and P. S. Magnusson. "Performance simulation tools." Computer 35, no. 2 (2002): 38–39. http://dx.doi.org/10.1109/2.982914.

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Ritchie, Nicholas W. M. "Spectrum Simulation in DTSA-II." Microscopy and Microanalysis 15, no. 5 (September 16, 2009): 454–68. http://dx.doi.org/10.1017/s1431927609990407.

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AbstractSpectrum simulation is a useful practical and pedagogical tool. Particularly with complex samples or trace constituents, a simulation can help to understand the limits of the technique and the instrument parameters for the optimal measurement. DTSA-II, software for electron probe microanalysis, provides both easy to use and flexible tools for simulating common and less common sample geometries and materials. Analytical models based on ϕ(ρz) curves provide quick simulations of simple samples. Monte Carlo models based on electron and X-ray transport provide more sophisticated models of arbitrarily complex samples. DTSA-II provides a broad range of simulation tools in a framework with many different interchangeable physical models. In addition, DTSA-II provides tools for visualizing, comparing, manipulating, and quantifying simulated and measured spectra.
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McClintock, Edwin, and Zhonghong Jiang. "Technology Tips: Spreadsheets: Powerful Tools for Probability Simulations." Mathematics Teacher 90, no. 7 (October 1997): 572–79. http://dx.doi.org/10.5951/mt.90.7.0572.

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The Curriculum and Evaluation Standards for School Mathematics (NCTM 1989) recommends that high school students extend their K-8 experiences with simulations and experimental probability to continue to improve their intuition and build more formal concepts of theoretical probability based on these experiences. In keeping with this idea, we use spreadsheets frequently in studying and investigating probabilistic situations with both high school students and preservice mathematics teachers. Our approach includes simulations but goes beyond the simulation process as a way of learning important concepts and principles of probability. We have found that spreadsheets are a very powerful tool for simulating probabilistic situations, not only for simple problems, such as simulating coin Ripping and die tossing, but also for rather complex problem situations. In this article, we illustrate the use of spreadsheets as a simulation tool for solving a collection of probability problems. The spreadsheet program we use is Microsoft Excel (1995), but other spreadsheet programs, such as Quattro Pro (Borland 1994), can be used with the same degree of effectiveness.
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Moshagen, Thilo. "Convergence of explicitly coupled simulation tools (co-simulations)." Journal of Numerical Mathematics 27, no. 1 (March 26, 2019): 23–36. http://dx.doi.org/10.1515/jnma-2017-0073.

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Abstract In engineering, it is a common desire to couple existing simulation tools together into one big system by passing information from subsystems as parameters into the subsystems under influence. As executed at fixed time points, this data exchange gives the global method a strong explicit component. Globally, such an explicit co-simulation schemes exchange time step can be seen as a step of an one-step method which is explicit in some solution components. Exploiting this structure, we give a convergence proof for such schemes. As flows of conserved quantities are passed across subsystem boundaries, it is not ensured that system-wide balances are fulfilled: the system is not solved as one single equation system. These balance errors can accumulate and make simulation results inaccurate. Use of higher-order extrapolation in exchanged data can reduce this problem but cannot solve it. The remaining balance error has been handled in past work by recontributing it to the input signal in next coupling time step, a technique labeled balance correction methods. Convergence for that method is proven. Further, the lack of stability for co-simulation schemes with and without balance correction is stated.
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Kyncl, Jiří. "Digital Factory Simulation Tools." Manufacturing Technology 16, no. 2 (April 1, 2016): 371–75. http://dx.doi.org/10.21062/ujep/x.2016/a/1213-2489/mt/16/2/371.

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Rauh, Jochen, and Alexander Eichberger. "Coupling of Simulation Tools." IFAC Proceedings Volumes 30, no. 8 (June 1997): 221–26. http://dx.doi.org/10.1016/s1474-6670(17)43827-4.

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Volesky, Bohumil. "Biosorption process simulation tools." Hydrometallurgy 71, no. 1-2 (October 2003): 179–90. http://dx.doi.org/10.1016/s0304-386x(03)00155-5.

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Dissertations / Theses on the topic "Simulation tools"

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Ramaswamy, Deepak 1974. "Simulation tools for microelectromechanical systems." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8625.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2001.<br>Includes bibliographical references (p. 101-104).<br>In this thesis efficient techniques to solve complex 3-D electromechanical problems are developed. Finite element discretization of complex structures such as the micromirror lead to thousands of internal degrees of freedom. Their mostly rigid motion is exploited leading to a mixed rigid-elastic formulation. This formulation's advantage is apparent when it is incorporated in an efficient coupled domain simulation technique and examples are presented exploring geometry effects on device behavior. Then for system level simulation where full device simulation costs add up we need models with much reduced order with little degradation in accuracy. We describe a model reduction formulation for the electromechanical problem based on implicit techniques which accurately capture the original model behavior.<br>by Deepak Ramaswamy.<br>Ph.D.
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Khalid, Ruzelan. "Component-Based Tools for Educational Simulations." Thesis, University of Canterbury. Computer Science and Software Engineering, 2013. http://hdl.handle.net/10092/8540.

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e-Learning is an effective medium for delivering knowledge and skills. In spite of improvements in electronic delivery technologies, e-Learning is still a long way away from offering anything close to efficient and effective learning environments. To improve e-Learning experiences, much literature supports simulation based e-Learning. This thesis begins identifying various types of simulation models and their features that induce experiential learning. We focus on designing and constructing an easy-to-use Discrete Event Simulation (DES) tool for building engaging and informative interactive DES models that allow learners to control the models’ parameters and visualizations through runtime interactions. DES has long been used to support analysis and design of complex systems but its potential to enhance learning has not yet been fully utilized. We first present an application framework and its resulting classes for better structuring DES models. However, importing relevant classes, establishing relationships between their objects and representing lifecycles of various types of active objects in a language that does not support concurrency demand a significant cognitive workload. To improve this situation, we utilize two design patterns to ease model structuring and logic representation (both in time and space) through a drag and drop component approach. The patterns are the Delegation Event Model, used for linking between components and delegating tasks of executing and updating active objects’ lifecycles, and the MVC (Model-View-Controller) pattern, used for connecting the components to their graphical instrumentations and GUIs. Components implementing both design patterns support the process-oriented approach, can easily be tailored to store model states and visualizations, and can be extended to design higher level models through hierarchical simulation development. Evaluating this approach with both teachers and learners using ActionScript as an implementation language in the Flash environment shows that the resulting components not only help model designers with few programming skills to construct DES models, but they also allow learners to conduct various experiments through interactive GUIs and observe the impact of changes to model behaviour through a range of engaging visualizations. Such interactions can motivate learners and make their learning an enjoyable experience.
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Vogelsang, Stefan. "Monitoring Tools File Specification." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-199034.

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This paper describes the format of monitoring data files that are collected for external measuring sites and at laboratory experiments at the Institute for Building Climatology (IBK). The Monitoring Data Files are containers for storing time series or event driven data collected as input for transient heat and moisture transport simulations. Further applications are the documentation of real world behaviour, laboratory experiments or the collection of validation data sets for simulation results ( whole building / energy consumption / HAM ). The article also discusses the application interface towards measurement data verification tools as well as data storage solutions that can be used to archive measurement data files conveniently and efficiently.
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El-Mounayri, Hazim A. "Generic solid modelling based machining process simulation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ30083.pdf.

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Schalin, Mikael. "Computational tools for simulation of phase transformations." Doctoral thesis, KTH, Materials Science and Engineering, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2779.

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<p>A new software package, Thermite, for thermodynamiccalculations and process simulation is developed around theThermo-Calc databank. Thermite is a computational toolbox forequilibrium calculations and simulation of phasetransformations. It provides graphic visualisation and allowsmanipulation of the presented data.</p><p>Two types of phase transformations have been implemented inthe software. First, it was used to simulate solidification ofalloys using the Gulliver-Scheil model. Simulations were madewith both Gulliver-Scheil model and with the DICTRA softwareand the predictions were compared with experimentalinformation. The interpretation of experimental cooling curveswas examined in detail and the role of back diffusion in thesolidified material has been considered. It was shown thatcooling curves with respect to time could be calculated fromenthalpy by integrating over the solidified layers.</p><p>Secondly, it was used to study the role of phase interfacesfor solid-solid transformations. The Hillert-Sundman treatmentof solute drag has been extended to multi-component systems.Using this extended treatment, the influences of the differentmodel parameters for partitionless transformation wereinvestigated and a comparison was made with earlier work. Theeffect of solute drag on the movement of grain boundaries wasstudied.</p><p>A technique was also developed to interface Thermo-Calc withother programs. This technique was used to link the DICTRAsoftware to the Thermite software package. The whole Thermitepackage is strictly organised in independent libraries toenable the substitution of each library. In particular, alibrary called Thermo-Calc C library has been designed tosupply thermodynamic calculations to many differentapplications.</p><p><b>Keywords:</b>thermodynamic calculations, simulation, phasetransformations, equilibrium, solidification, solute drag,massive transformations</p>
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Gentry, Retha D., Lisa Ousley, and Candice Short. "Innovative Dermatology Tools for Use in Simulation." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/etsu-works/8373.

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Figueiredo, Sérgio Miguel Calafate de. "Evaluation of network simulation and modelimg tools." Master's thesis, Universidade de Aveiro, 2008. http://hdl.handle.net/10773/1964.

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Mestrado em Engenharia Electrónica e Telecomunicações<br>A crescente globalização da Internet e consequente procura de largura de banda nas redes IP existentes fez emergir a necessidade de um melhor planeamento das redes de telecomunicações. Tendo em vista esse fim foram criadas ferramentas aptas a auxiliar a gestão de redes, como software de monitorização, e em particular os simuladores de redes. Estes permitem a obtenção de resultados preciosos sem a consumo de recursos que a criação de uma testbed real requer. Um desses simuladores é o Opnet Modeler, um software comercial que possibilita a configuração de cenários a vários níveis, como as características dos protocolos, perfis de utilizadores e de mobilidade, ou a estrutura e dimensão da rede. Esta dissertação propôe-se a numa primeira parte a analisar vários aspectos respeitantes à utilização do Opnet Modeler no prisma do gestor de redes, em especial em redes à escala de Campus, explorando algumas das vantagens e lacunas na sua utilização para diversos fins, tais como o design ou restruturação de redes e a análise da qualidade de serviço de diferentes aplicações. Uma componente indispensável à gestão de redes é a previsão de qualidade de serviço. O facto do comportamento do tráfego numa rede variar devido a factores como a alteração do número de utilizadores ou dos seus perfis de tráfego, leva a que seja várias vezes necessário estimar o comportamento da rede sem o perfeito conhecimento desta ou dos seus recursos. O nível de tráfego actualmente desperdiçado devido a uma incorrecta estimativa por parte dos ISP’s da utilização de redes mais complexas representa ao mesmo tempo custos desnecessários e recursos subaproveitados. A procura de um modelo de tráfego que possibilite uma aproximação mais exacta dos parâmetros previstos em relação à realidade leva a que haja uma maior investigação nesta área. Nesta dissertação é testado um framework modelador que se baseia apenas em medições (ou resultados de simulações) de tráfego e correspondentes parâmetros de qualidade de serviço dos pontos de acesso da rede, sem o conhecimento a priori da matriz de tráfego e da topologia da rede, para prever a qualidade de serviço em condições distintas. ABSTRACT: The growing Internet globalization and consequent demand for bandwidth in the existing IP networks lead to the emerging need of a better network telecommunications planning. In order to accomplish that, apt network management tools were created, like monitoring software and network simulators, in particular. These allow the collection of precious results exempt of the resources consumption that the use of a real testbed would require. One of those simulators is Opnet Modeler, commercial software that allows to configure the scenarios at multiple levels, like protocol characteristics, profiles and mobility profiles, or the network size and structure. This dissertation proposes to analyze various aspects related to Opnet Modeler use in a network manager perspective, in particular in Campus scale networks, aiming to explore its advantages and gaps when used for goals such as network design or restructuration and for different services’ QoS analysis. One essential component in network management is QoS prediction. The fact that the network traffic behavior varies due to details like the change in the number of users or their traffic profiles, many times leads to the need of assessing the network behavior without the perfect knowledge of the network or its resources. The currently wasted bandwidth by the ISP’s and network managers due to an incorrect assessment of the utilization in more complex networks represents unnecessary costs and wasted resources. The pretension to obtain a traffic model that allows a more exact approximation of the predicted parameters relatively to the reality lead to a major increase in the research in this area. In this dissertation, the evluation of a modeling framework is performed; that model, based only in traffic measurements (or simulation results) and corresponding QoS parameters at the network access points, that is, without the a priori knowledge of the network’s traffic matrix and topology, is able to predict the network’s QoS for different conditions.
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Sentausa, Erwin. "Time course simulation replicability of SBML-supporting biochemical network simulation tools." Thesis, University of Skövde, School of Humanities and Informatics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-33.

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<p>Background: Modelling and simulation are important tools for understanding biological systems. Numerous modelling and simulation software tools have been developed for integrating knowledge regarding the behaviour of a dynamic biological system described in mathematical form. The Systems Biology Markup Language (SBML) was created as a standard format for exchanging biochemical network models among tools. However, it is not certain yet whether actual usage and exchange of SBML models among the tools of different purpose and interfaces is assessable. Particularly, it is not clear whether dynamic simulations of SBML models using different modelling and simulation packages are replicable.</p><p>Results: Time series simulations of published biological models in SBML format are performed using four modelling and simulation tools which support SBML to evaluate whether the tools correctly replicate the simulation results. Some of the tools do not successfully integrate some models. In the time series output of the successful</p><p>simulations, there are differences between the tools.</p><p>Conclusions: Although SBML is widely supported among biochemical modelling and simulation tools, not all simulators can replicate time-course simulations of SBML models exactly. This incapability of replicating simulation results may harm the peer-review process of biological modelling and simulation activities and should be addressed accordingly, for example by specifying in the SBML model the exact algorithm or simulator used for replicating the simulation result.</p>
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Mallory, Richard Smith. "Tools for explaining complex qualitative simulations /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Adourian, Chahe. "Bidirectional integration of geometric and dynamic simulation tools." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=96756.

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Mechanisms to share information from Mechanical Computer Assisted Design (MCAD) to simulation model have been demonstrated using various approaches. However, in all cases the information sharing is unidirectional - from the MCAD to Multi-Body Systems (MBS) simulation - which lacks the bidirectional mapping required in a concurrent engineering context where both models need to develop in parallel while remaining consistent.We present a modelling library and a model mapping that permits and encourages parallel development of the mechanical assembly in both the MBS simulation and MCAD environments while supporting both bidirectional initial full transfer and incremental updates. Furthermore, with the adopted approach and with a careful selection of the simulation language, MCAD parts can be extended with non-mechanical behaviour in the simulation tool.<br>Des mécanismes pour partager l'information entre un modèle CAD et un modèle de simulation ont été démontrés utilisant divers approches. Pourtant, dans tous les cas, le partage d'information était unidirectionnel - allant du modèle CAD vers le modèle de simulation - donc ne possédant pas les qualités bidirectionnelles nécessaires dans le contexte de l'ingénierie collaborative ou les modèles doivent rester consistantes en permanence.Nous présentons notre librairie de modélisation et de transformations entre modèles qui permettent et encouragent le développement parallèle de l'assemblage mécanique dans les deux environnements de simulation de conception. Notre approche supporte le partage et la synchronisation des deux modèles dans les deux sens et de façon incrémentale si nécessaire. En complément, avec l'approche que nous avons adopté, les modèles mécaniques peuvent être associés a des modèles comportementales non mécanique dans l'outil de simulation.
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Books on the topic "Simulation tools"

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Song, Houbing, and Dingde Jiang, eds. Simulation Tools and Techniques. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72795-6.

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Song, Houbing, and Dingde Jiang, eds. Simulation Tools and Techniques. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72792-5.

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Jiang, Dingde, and Houbing Song, eds. Simulation Tools and Techniques. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97124-3.

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Song, Houbing, and Dingde Jiang, eds. Simulation Tools and Techniques. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32216-8.

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Guisado-Lizar, José-Luis, Agustín Riscos-Núñez, María-José Morón-Fernández, and Gabriel Wainer, eds. Simulation Tools and Techniques. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57523-5.

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Juan, Angel A., José-Luis Guisado-Lizar, María-José Morón-Fernández, and Elena Perez-Bernabeu, eds. Simulation Tools and Techniques. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-87345-4.

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Austria) International Seminar "AVL Simulation Tools--Practical Applications" (2011 Graz. AVL simulation tools: Practical applications. Lublin: Politechnika Lubelska, 2012.

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Wehrle, Klaus, Mesut Güneş, and James Gross, eds. Modeling and Tools for Network Simulation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12331-3.

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Wehrle, Klaus. Modeling and Tools for Network Simulation. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Wiedemann, Markus. Simulation des Schwingungsverhaltens spanender Werkzeugmaschinen. Berlin: Springer-Verlag, 1993.

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Book chapters on the topic "Simulation tools"

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Lantuéjoul, Christian. "Variographic tools." In Geostatistical Simulation, 21–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04808-5_3.

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Ordys, Andrzej W., A. W. Pike, Michael A. Johnson, Reza M. Katebi, and Michael J. Grimble. "Simulation Tools." In Modelling and Simulation of Power Generation Plants, 87–116. London: Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-2114-5_3.

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Mahmoud, Magdi S. "Simulation Tools." In Fuzzy Control, Estimation and Diagnosis, 633–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54954-5_12.

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Adamski, Dirk. "Simulation Tools." In Simulation in Chassis Technology, 73–87. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-30678-6_5.

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Delgado, João M. P. Q., Eva Barreira, Nuno M. M. Ramos, and Vasco Peixoto de Freitas. "Hygrothermal Simulation Tools." In Hygrothermal Numerical Simulation Tools Applied to Building Physics, 21–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35003-0_3.

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Raveendranathan, K. C. "System Simulation Tools." In Signal Processing Techniques for Communication, 15–41. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003527589-2.

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Pierce, Jim, Michael D. Smith, and Trevor Mudge. "Instrumentation Tools." In Fast Simulation of Computer Architectures, 47–86. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2361-1_3.

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Carstens, Deborah Sater, and Gary L. Richardson. "Simulation Modeling." In Project Management Tools and Techniques, 395–418. Second Edition. | Boca Raton : CRC Press, 2019. | Revised edition of Project management tools and techniques, [2013]: CRC Press, 2019. http://dx.doi.org/10.1201/9780429263163-25.

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Brauburger, R. A. "Simulation Tools for Chrysler Product Development." In Maritime Simulation, 67–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-82560-6_8.

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Albers, Karsten, Benjamin Bolte, Max-Arno Meyer, Axel Terfloth, and Anna Wißdorf. "Tool Support for Co-Simulation-Based Analysis." In Model-Based Engineering of Collaborative Embedded Systems, 269–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62136-0_13.

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AbstractThe development of collaborative embedded systems (CESs) requires the validation of their runtime behavior during design time. In this context, simulation-based analysis methods play a key role in the development of such systems. Simulations of CESs tend to become complex. One cause is that CESs work in collaborative system groups (CSGs) within a dynamic context., which is why CESs must be simulated as participants of a CSG. Another cause stems from the fact that CES simulations cover various cyber-physical domains. The models incorporated are often managed by different tools that are specialized for specific simulation disciplines and must be jointly executed in a cosimulation. Besides the methodological aspects, the interoperability of models and tools within such a co-simulation is a major challenge. This chapter focusses on the tool integration aspect of enabling co-simulations. It motivates the need for co-simulation for CES development and describes a general tool architecture. The chapter presents the advantages and limitations of adopting existing standards such as FMI and DCP, as well as best practices for integrating simulation tools and models for CESs and CSGs.
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Conference papers on the topic "Simulation tools"

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Van Blaricum, Vicki L., Vincent F. Hock, Dan Ursino, Mark D. Brooks, and Kent W. Smothers. "Utility System Modeling and Simulation Tools." In CORROSION 2003, 1–12. NACE International, 2003. https://doi.org/10.5006/c2003-03272.

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Abstract Sensor-enabled dynamic utility system modeling software can be used to diagnose and analyze hydraulic and water-quality problems in water distribution systems. It can also rapidly model consequences and risks of potential responses to contamination or system damage. Dynamic modeling software will be described, and examples of its use will be given.
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Da Mota, Benoit, Pascal Nicolas, and Igor Stephan. "A new parallel architecture for QBF tools." In Simulation (HPCS). IEEE, 2010. http://dx.doi.org/10.1109/hpcs.2010.5547114.

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Ganley, M. D. "Simulation tools for EMC." In IEE Colloquium on "Hows" and "Whys" of EMC Design. IEE, 1999. http://dx.doi.org/10.1049/ic:19990005.

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Bloss, Adrienne, Michael Keenan, and Kimberly Johnson. "Tools for functional simulation." In the 25th conference. New York, New York, USA: ACM Press, 1993. http://dx.doi.org/10.1145/256563.256799.

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MacMillan, D. J., J. L. Pletcher, and S. A. Bourgeois. "Practical Tools To Assist History Matching." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 1999. http://dx.doi.org/10.2118/51888-ms.

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Zavoral, F., D. Bednárek, J. Yaghob, and J. Dokulil. "Automatic Extraction of Navigation Structure in Scheduling Tools." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.696-095.

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Klimeck, Gerhard. "NanoHUB.org Tutorial: Education Simulation Tools." In 2007 2nd IEEE International Conference on Nano/Micro Engineered and Molecular Systems. IEEE, 2007. http://dx.doi.org/10.1109/nems.2007.351992.

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Dinavahi, V., M. Steurer, K. Strunz, and J. A. Martinez. "Interfacing techniques for simulation tools." In Energy Society General Meeting (PES). IEEE, 2009. http://dx.doi.org/10.1109/pes.2009.5275553.

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Lata, Suman, and Dheerendra Singh. "Cloud simulation tools: A survey." In INNOVATIONS IN COMPUTATIONAL AND COMPUTER TECHNIQUES: ICACCT-2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0109181.

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Gozard, Patrick, Emmanuel Bret, and Thierry Cathala. "Virtual simulation tools for artillery." In SPIE Defense and Security Symposium, edited by Ivan Kadar. SPIE, 2008. http://dx.doi.org/10.1117/12.780359.

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Reports on the topic "Simulation tools"

1

Hamlet, Benjamin Roger. Ion trap simulation tools. Office of Scientific and Technical Information (OSTI), February 2009. http://dx.doi.org/10.2172/983695.

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Li, Xiaolin. Terascale Simulation Tools and Technologies. Office of Scientific and Technical Information (OSTI), March 2007. http://dx.doi.org/10.2172/900578.

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Iwasaki, Masako. LCD ROOT Simulation and Analysis Tools. Office of Scientific and Technical Information (OSTI), February 2001. http://dx.doi.org/10.2172/784876.

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Snopok, Pavel. Advanced Simulation Tools for Muon-Based Accelerators. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1491786.

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Brocato, Robert Wesley. FDTD simulation tools for UWB antenna analysis. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/920838.

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Matei, Ion, and Conrad Bock. An analysis of solver-based simulation tools. Gaithersburg, MD: National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.ir.7846.

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Matei, Ion, and Conrad E. Bock. SysML Extension for Dynamical System Simulation Tools. Gaithersburg, MD: National Institute of Standards and Technology, October 2012. http://dx.doi.org/10.6028/nist.ir.7888.

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Bodner, Doug, and Bill Rouse. A Framework and Tools for Organizational Simulation. Fort Belvoir, VA: Defense Technical Information Center, August 2009. http://dx.doi.org/10.21236/ada519108.

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Ratliff, Barbara, Andrew Reiman, and Alice Orrell. Distributed Wind Representation in Modeling and Simulation Tools: An Assessment of Existing Tools. Office of Scientific and Technical Information (OSTI), February 2020. http://dx.doi.org/10.2172/1647220.

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Boudreaux, Philip R., Joshua Ryan New, Som S. Shrestha, Mark B. Adams, and Simon B. Pallin. State-of-the-Art for Hygrothermal Simulation Tools. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1407999.

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