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Classement pour la résistance mécanique du chêne par méthodes vibratoires et par mesure des orientations des fibres

Abstract : Hardwoods are the majority in France, with a substantial amount of small, low grade oaks. This resource could be an alternative of typical construction materials. However, mechanical properties can change a lot depending on timber defects. Thus, it is necessary to verify the good quality of each board in order it can be used in structural applications. The efficiency of grading methods is one of principal challenges to promote the use of oak in structures. The present work aims to provide new grading machine solutions relative to low grade oak which could replace the traditional and downgrading method based on visual sorting by an operator.Indeed, two models have been developed during this thesis, based on nondestructive measurements following by destructive tests to validate them. The first one is an analytical model based on grain angle scanning measurements. From grain angle data maps, local values of modulus of elasticity and resistance were computed, then the global mechanical properties were computed. The second one is a statistical model based on the analysis of longitudinal and transversal vibrational measurements. The results show that the longitudinal vibrational method based on the first longitudinal eigen frequency, which is mostly employed in softwood industry, is not suited for oak grading. However, the efficiency of the methods based on transversal vibrations is pretty good but it needs additional efforts for industrial application. In this work, the model based on grain angle scanning offer the best and the more robust grading efficiency for all grades.
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Submitted on : Thursday, March 29, 2018 - 12:18:07 PM
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  • HAL Id : tel-01749503, version 1


Younes Faydi. Classement pour la résistance mécanique du chêne par méthodes vibratoires et par mesure des orientations des fibres. Mécanique des matériaux [physics.class-ph]. Ecole nationale supérieure d'arts et métiers - ENSAM, 2017. Français. ⟨NNT : 2017ENAM0051⟩. ⟨tel-01749503⟩



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