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Diagnostic et comportement des ponts à ossature bois
This paper deals with the behavior study of the timber bridge of Merle. This complex structure necessitates understanding its mechanical schema in order to predict the long-term behavior by taking into account the variable climate environment and validating the design hypotheses. Different usual displacement measures like LVDT sensors enable us to characterize displacements for singular points (beam deflections principally). In this context, a new image analysis method has been used. It allows us to obtain the displacement field of the whole bridge with a very high accuracy. In order to validate the design model, we present a 2D and 3D numeric modeling, employing the finite element method, in order to define boundaries, kinematic conditions and the global static mechanical properties by operating an inverse analysis method.
Diagnostic et comportement des ponts à ossature bois
This paper deals with the behavior study of the timber bridge of Merle. This complex structure necessitates understanding its mechanical schema in order to predict the long-term behavior by taking into account the variable climate environment and validating the design hypotheses. Different usual displacement measures like LVDT sensors enable us to characterize displacements for singular points (beam deflections principally). In this context, a new image analysis method has been used. It allows us to obtain the displacement field of the whole bridge with a very high accuracy. In order to validate the design model, we present a 2D and 3D numeric modeling, employing the finite element method, in order to define boundaries, kinematic conditions and the global static mechanical properties by operating an inverse analysis method.
Diagnostic et comportement des ponts à ossature bois
Dubois, Frédéric (author) / Petit, Christophe (author) / Sauvat, Nicolas (author) / Peuchot, Bernard (author)
Revue Européenne de Génie Civil ; 10 ; 191-208
2006-02-01
18 pages
Article (Journal)
Electronic Resource
Unknown
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