Simulation-based engineering

dc.citation.epage73en_US
dc.citation.spage39en_US
dc.contributor.authorÇakmakcı, Melihen_US
dc.contributor.authorSendur, G. K.en_US
dc.contributor.authorDurak, U.en_US
dc.contributor.editorMittal, S.
dc.contributor.editorDurak, U.
dc.contributor.editorÖren, T.
dc.date.accessioned2019-04-24T11:12:33Z
dc.date.available2019-04-24T11:12:33Z
dc.date.issued2017en_US
dc.departmentDepartment of Mechanical Engineeringen_US
dc.descriptionChapter 3
dc.description.abstractEngineers, mathematicians, and scientists were always interested in numerical solutions of real-world problems. The ultimate objective within nearly all engineering projects is to reach a functional design without violating any of the performance, cost, time, and safety constraints while optimizing the design with respect to one of these metrics. A good mathematical model is at the heart of each powerful engineering simulation being a key component in the design process. In this chapter, we review role of simulation in the engineering process, the historical developments of different approaches, in particular simulation of machinery and continuum problems which refers basically to the numerical solution of a set of differential equations with different initial/boundary conditions. Then, an overview of well-known methods to conduct continuum based simulations within solid mechanics, fluid mechanics and electromagnetic is given. These methods include FEM, FDM, FVM, BEM, and meshless methods. Also, a summary of multi-scale and multi-physics-based approaches are given with various examples. With constantly increasing demands of the modern age challenging the engineering development process, the future of simulations in the field hold great promise possibly with the inclusion of topics from other emerging fields. As technology matures and the quest for multi-functional systems with much higher performance increases, the complexity of problems that demand numerical methods also increases. As a result, large-scale effective computing continues to evolve allowing for efficient and practical performance evaluation and novel designs, hence the enhancement of our thorough understanding of the physics within highly complex systems.en_US
dc.identifier.doi10.1007/978-3-319-61264-5_3en_US
dc.identifier.doi10.1007/978-3-319-61264-5en_US
dc.identifier.eisbn9783319612645
dc.identifier.isbn9783319612638
dc.identifier.urihttp://hdl.handle.net/11693/50924
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.ispartofGuide to simulation-based disciplines: advancing our computational futureen_US
dc.relation.ispartofseriesSimulation Foundations, Methods and Applications
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-61264-5_3en_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-61264-5en_US
dc.subjectEngineering design cycleen_US
dc.subjectV-processen_US
dc.subjectWaterfall modelen_US
dc.subjectHardware-in-the-loop simulationsen_US
dc.subjectFeature-in-the-loop simulationsen_US
dc.subjectComponent-in-the-loop simulationsen_US
dc.subjectContinuum mechanicsen_US
dc.subjectComputational electromagneticsen_US
dc.subjectPartial differential equations (PDE)en_US
dc.subjectFinite element method (FEM)en_US
dc.subjectFinite-difference method (FDM)en_US
dc.subjectMulti-scale methodsen_US
dc.subjectLumped parameter modelsen_US
dc.subjectModel-based control system designen_US
dc.subjectVehicle dynamics modelsen_US
dc.subjectNetworked control systemsen_US
dc.subjectDiscretized systemsen_US
dc.subjectQuantizationen_US
dc.subjectObserver modelsen_US
dc.subjectIterative learningen_US
dc.titleSimulation-based engineeringen_US
dc.typeBook Chapteren_US

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