FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2781636343> ?p ?o ?g. }

• W2781636343 abstract "As ever more challenging designs are required in present-day industries, the traditional trial-and-error procedure frequently used for designing mechanical parts slows down the design process and yields suboptimal designs, so that new approaches are needed to obtain a competitive advantage. With the ascent of the Finite Element Method (FEM) in the engineering community in the 1970s, structural shape optimization arose as a promising area of application. However, due to the iterative nature of shape optimization processes, the handling of large quantities of numerical models along with the approximated character of numerical methods may even dissuade the use of these techniques (or fail to exploit their full potential) because the development time of new products is becoming ever shorter. This Thesis is concerned with the formulation of a 3D methodology based on the Cartesian-grid Finite Element Method (cgFEM) as a tool for efficient and robust numerical analysis. This methodology belongs to the category of embedded (or fictitious) domain discretization techniques in which the key concept is to extend the structural analysis problem to an easy-to-mesh approximation domain that encloses the physical domain boundary.The use of Cartesian grids provides a natural platform for structural shape optimization because the numerical domain is separated from a physical model, which can easily be changed during the optimization procedure without altering the background discretization. Another advantage is the fact that mesh generation becomes a trivial task since the discretization of the numerical domain and its manipulation, in combination with an efficient hierarchical data structure, can be exploited to save computational effort.However, these advantages are challenged by several numerical issues. Basically, the computational effort has moved from the use of expensive meshing algorithms towards the use of, for example, elaborate numerical integration schemes designed to capture the mismatch between the geometrical domain boundary and the embedding finite element mesh. To do this we used a stabilized formulation to impose boundary conditions and developed novel techniques to be able to capture the exact boundary representation of the models.To complete the implementation of a structural shape optimization method an adjunct formulation is used for the differentiation of the design sensitivities required for gradient-based algorithms. The derivatives are not only the variables required for the process, but also compose a powerful tool for projecting information between different designs, or even projecting the information to create h-adapted meshes without going through a full h-adaptive refinement process.The proposed improvements are reflected in the numerical examples included in this Thesis. These analyses clearly show the improved behavior of the cgFEM technology as regards numerical accuracy and computational efficiency, and consequently the suitability of the cgFEM approach for shape optimization or contact problems." @default.
• W2781636343 created "2018-01-12" @default.
• W2781636343 creator A5088282250 @default.
• W2781636343 date "2017-09-01" @default.
• W2781636343 modified "2023-09-26" @default.
• W2781636343 title "Structural Shape Optimization Based On The Use Of Cartesian Grids" @default.
• W2781636343 doi "https://doi.org/10.4995/thesis/10251/86195" @default.
• W2781636343 hasPublicationYear "2017" @default.
• W2781636343 type Work @default.
• W2781636343 sameAs 2781636343 @default.
• W2781636343 citedByCount "0" @default.
• W2781636343 crossrefType "dissertation" @default.
• W2781636343 hasAuthorship W2781636343A5088282250 @default.
• W2781636343 hasBestOaLocation W27816363431 @default.
• W2781636343 hasConcept C11413529 @default.
• W2781636343 hasConcept C126255220 @default.
• W2781636343 hasConcept C127413603 @default.
• W2781636343 hasConcept C134306372 @default.
• W2781636343 hasConcept C135628077 @default.
• W2781636343 hasConcept C16038011 @default.
• W2781636343 hasConcept C181145010 @default.
• W2781636343 hasConcept C187691185 @default.
• W2781636343 hasConcept C2524010 @default.
• W2781636343 hasConcept C29513896 @default.
• W2781636343 hasConcept C33923547 @default.
• W2781636343 hasConcept C34972735 @default.
• W2781636343 hasConcept C36503486 @default.
• W2781636343 hasConcept C41008148 @default.
• W2781636343 hasConcept C43173174 @default.
• W2781636343 hasConcept C62354387 @default.
• W2781636343 hasConcept C66938386 @default.
• W2781636343 hasConcept C73000952 @default.
• W2781636343 hasConcept C78519656 @default.
• W2781636343 hasConceptScore W2781636343C11413529 @default.
• W2781636343 hasConceptScore W2781636343C126255220 @default.
• W2781636343 hasConceptScore W2781636343C127413603 @default.
• W2781636343 hasConceptScore W2781636343C134306372 @default.
• W2781636343 hasConceptScore W2781636343C135628077 @default.
• W2781636343 hasConceptScore W2781636343C16038011 @default.
• W2781636343 hasConceptScore W2781636343C181145010 @default.
• W2781636343 hasConceptScore W2781636343C187691185 @default.
• W2781636343 hasConceptScore W2781636343C2524010 @default.
• W2781636343 hasConceptScore W2781636343C29513896 @default.
• W2781636343 hasConceptScore W2781636343C33923547 @default.
• W2781636343 hasConceptScore W2781636343C34972735 @default.
• W2781636343 hasConceptScore W2781636343C36503486 @default.
• W2781636343 hasConceptScore W2781636343C41008148 @default.
• W2781636343 hasConceptScore W2781636343C43173174 @default.
• W2781636343 hasConceptScore W2781636343C62354387 @default.
• W2781636343 hasConceptScore W2781636343C66938386 @default.
• W2781636343 hasConceptScore W2781636343C73000952 @default.
• W2781636343 hasConceptScore W2781636343C78519656 @default.
• W2781636343 hasLocation W27816363431 @default.
• W2781636343 hasOpenAccess W2781636343 @default.
• W2781636343 hasPrimaryLocation W27816363431 @default.
• W2781636343 hasRelatedWork W1622862312 @default.
• W2781636343 hasRelatedWork W1666417893 @default.
• W2781636343 hasRelatedWork W1842306809 @default.
• W2781636343 hasRelatedWork W1986814656 @default.
• W2781636343 hasRelatedWork W2032559642 @default.
• W2781636343 hasRelatedWork W2273806827 @default.
• W2781636343 hasRelatedWork W2749023310 @default.
• W2781636343 hasRelatedWork W2765833305 @default.
• W2781636343 hasRelatedWork W2773783620 @default.
• W2781636343 hasRelatedWork W2794466035 @default.
• W2781636343 hasRelatedWork W2811419614 @default.
• W2781636343 hasRelatedWork W2890821315 @default.
• W2781636343 hasRelatedWork W2990555893 @default.
• W2781636343 hasRelatedWork W3036295894 @default.
• W2781636343 hasRelatedWork W3044036095 @default.
• W2781636343 hasRelatedWork W3045337257 @default.
• W2781636343 hasRelatedWork W3113213628 @default.
• W2781636343 hasRelatedWork W3136100330 @default.
• W2781636343 hasRelatedWork W3145247344 @default.
• W2781636343 hasRelatedWork W2065534487 @default.
• W2781636343 isParatext "false" @default.
• W2781636343 isRetracted "false" @default.
• W2781636343 magId "2781636343" @default.
• W2781636343 workType "dissertation" @default.