Doctoral thesis (Dissertations and theses)
A strain smoothing method in finite nelements for structural analysis
NGUYEN, Xuan Hung
2008
 

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Keywords :
Computational mechanics
Abstract :
[en] This thesis further developments strain smoothing techniques in finite elementmethods for structural analysis. Two methods are investigated and analyzed both theoretically and numerically. The first is a smoothed finite element method (SFEM) where an assumed strain field is derived from a smoothed operator of the compatible strain field via smoothing cells in the element.The second is a nodally smoothed finite element method (N-SFEM),where an assumed strain field is evaluated using the strain smoothing in neighbouring domains connected with nodes.For the SFEM, 2D, 3D, plate and shell problems are studied in details. Twoissues based on a selective integration and a stabilization approach for volumetric locking are considered. It is also shown that the SFEM in 2D with asingle smoothing cell is equivalent to a quasi-equilibrium model.For the N-SFEM, a priori error estimation is established and the convergence is confirmed numerically by benchmark problems. In addition, a quasi-equilibrium model is obtained and as a result a dual analysis is very promising to estimate an upper bound of the global error in finite elements.It is also expected that two present approaches are being incorporated withthe extended finite element methods to improve the discontinuous solution offracture mechanics.
Disciplines :
Mechanical engineering
Author, co-author :
NGUYEN, Xuan Hung ;  Université de Liège - ULiège > SAAM - FSA - Département d'aérospatiale et de mécanique
Language :
English
Title :
A strain smoothing method in finite nelements for structural analysis
Defense date :
05 May 2008
Institution :
Université de Liège
Degree :
Doctorat en sciences de l'ingénieur
Promotor :
DUYSINX, Pierre  
NGUYEN, Dang Hung
President :
BECKERS, Pierre
Jury member :
DEBONGNIE, Jean-François
BOUILLARD, Philippe
BORDAS, Stéphane
CESCOTTO, Serge
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since 27 March 2024

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