Academic literature on the topic 'Simulation tools'
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Journal articles on the topic "Simulation tools"
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.
Full textGrafton, 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.
Full textRitchie, 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.
Full textDean, 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.
Full textMukherjee, 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.
Full textReinhart, William F., and Charles J. C. Lloyd. "A Human Factors Simulation Tool for Stereoscopic Displays." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38, no. 19 (October 1994): 1290–94. http://dx.doi.org/10.1177/154193129403801909.
Full textMoshagen, 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.
Full textKyncl, 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.
Full textVolesky, 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.
Full textRauh, 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.
Full textDissertations / Theses on the topic "Simulation tools"
Ramaswamy, Deepak 1974. "Simulation tools for microelectromechanical systems." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8625.
Full textIncludes bibliographical references (p. 101-104).
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.
by Deepak Ramaswamy.
Ph.D.
Khalid, Ruzelan. "Component-Based Tools for Educational Simulations." Thesis, University of Canterbury. Computer Science and Software Engineering, 2013. http://hdl.handle.net/10092/8540.
Full textVogelsang, Stefan. "Monitoring Tools File Specification." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-199034.
Full textEl-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.
Full textSchalin, 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.
Full textA 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.
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.
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.
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.
Keywords:thermodynamic calculations, simulation, phasetransformations, equilibrium, solidification, solute drag,massive transformations
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.
Full textA 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.
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.
Full textSentausa, 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.
Full textBackground: 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.
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
simulations, there are differences between the tools.
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.
Mallory, Richard Smith. "Tools for explaining complex qualitative simulations /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.
Full textAdourian, 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.
Full textDes 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.
Books on the topic "Simulation tools"
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.
Full textSong, 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.
Full textSong, 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.
Full textStatistical tools for simulation practitioners. New York: M. Dekker, 1987.
Find full textAustria) International Seminar "AVL Simulation Tools--Practical Applications" (2011 Graz. AVL simulation tools: Practical applications. Lublin: Politechnika Lubelska, 2012.
Find full textWehrle, Klaus. Modeling and Tools for Network Simulation. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.
Find full textWehrle, 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.
Full textMacDougall, M. H. Simulating computer systems: Techniques and tools. Cambridge, Mass: MIT Press, 1987.
Find full textWiedemann, Markus. Simulation des Schwingungsverhaltens spanender Werkzeugmaschinen. Berlin: Springer-Verlag, 1993.
Find full textLaguna, Manuel, and José Luis González Velarde, eds. Computing Tools for Modeling, Optimization and Simulation. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4567-5.
Full textBook chapters on the topic "Simulation tools"
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.
Full textAdamski, 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.
Full textOrdys, 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.
Full textMahmoud, 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.
Full textDelgado, 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.
Full textPierce, 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.
Full textBrauburger, 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.
Full textCarstens, 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.
Full textKemp, Ian C. "Process-Systems Simulation Tools." In Modern Drying Technology, 261–305. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527631629.ch7.
Full textTerman, Christopher J. "Simulation Tools for VLSI." In The Kluwer International Series in Engineering and Computer Science, 57–103. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1985-6_3.
Full textConference papers on the topic "Simulation tools"
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.
Full textBloss, 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.
Full textGanley, 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.
Full textMacMillan, 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.
Full textZavoral, 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.
Full textDinavahi, 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.
Full textKlimeck, 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.
Full textGozard, 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.
Full textWeytjens, Lieve, and Griet Verbeeck. "Towards 'architect-friendly' energy evaluation tools." In the 2010 Spring Simulation Multiconference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878724.
Full textJackson, Mark, and R. McDonald. "Draper Simulation Analysis Tool (DSAT): Graphical Object Simulation Techniques and Tools for Simulink." In AIAA Modeling and Simulation Technologies Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.2004-5458.
Full textReports on the topic "Simulation tools"
Hamlet, Benjamin Roger. Ion trap simulation tools. Office of Scientific and Technical Information (OSTI), February 2009. http://dx.doi.org/10.2172/983695.
Full textLi, Xiaolin. Terascale Simulation Tools and Technologies. Office of Scientific and Technical Information (OSTI), March 2007. http://dx.doi.org/10.2172/900578.
Full textIwasaki, Masako. LCD ROOT Simulation and Analysis Tools. Office of Scientific and Technical Information (OSTI), February 2001. http://dx.doi.org/10.2172/784876.
Full textSnopok, Pavel. Advanced Simulation Tools for Muon-Based Accelerators. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1491786.
Full textMatei, 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.
Full textMatei, 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.
Full textBrocato, 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.
Full textBodner, 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.
Full textRatliff, 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.
Full textBoudreaux, 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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