.. .. La-ddi-en-pratique,

D. .. Données-d'entrée-pour-la, 122 6.1.1.1 A partir des essais expérimentaux, p.122

. .. Données-numériques, , p.123

D. .. Sorties-de-la,

. .. , 126 6.2.2 Faut-il comparer les résultats avec ceux issus de méthodes avec lois de comportement ?, Méthodes utilisées pour valider la mesure de contrainte par la DDI . . 126 6.2.1 Retrouver l'isotropie du matériau

, Calcul de la densité d'énergie de déformation élastique, p.128

.. .. Bilan-Énergétique,

. .. , Identification des contraintes par la méthode DDI sur le RTVt

. .. Champs-de-contrainte-mesurés, , p.130

, Appariement entre les états mécaniques et les états matériau

.. .. Isotropie,

. .. Énergie-de-déformation-Élastique,

, Densité d'énergie pour l'essai sur membrane perforée 134

, Comparaison avec les données TU et incertitudes, p.135

. .. , Diversité des états de déformation, p.137

.. .. Bilan-Énergétique,

, Identification des contraintes par la méthode DDI sur le RTVb, p.140

.. .. Conclusion,

. .. Modèle-Éléments-finis, , p.146

D. .. Paramètres-intrinsèques-de-la, , p.148

. .. , 151 7.1.2.1 Influence des paramètres intrinsèques sur l'erreur de mesure de contrainte

?. .. Quel-choix-de-paramètres, , p.153

, Conception d'éprouvettes bi-matériaux, p.155

, Essais de traction avec mesure de champs, p.156

, Mesures de déplacement par corrélation d'images, p.157

, Perspectives : vers l'identification de la réponse des matériaux anélastiques158 7.3.1 Qualité

, Séparation algorithmique des matériaux, p.160

.. .. Conclusion,

. .. Modèle-Éléments-finis, , p.166

D. .. Paramètres-intrinsèques-de-la, , p.167

D. .. Résultats-de-la, 168 8.1.2.1 Influence des paramètres intrinsèques sur l'erreur de mesure de contrainte

, Notion de richesse des modes de déformation, p.169

. .. Conception-d'éprouvette, , p.171

. .. Essais, , p.172

. .. Champs-de-contrainte-identifiés, 175 8.2.2.2 Vérification du moment résultant, p.175

. .. Richesse-des-déformations, , p.177

, Perspectives : qualité de l'identification « à la demande, p.178

.. .. Conclusion,

, de simulation sans loi de comportement comme la DDCM, l'ajustement des paramètres d'une loi de comportement sur des données complexes, ou encore l'étude qualitative du matériau, telle que son isotropie mécanique. Deux contributions mineures peuvent également être mises en exergue. Tout d'abord, l'étude complète de la DDI permet de mieux comprendre son fonctionnement, ainsi que sa sensibilité aux paramètres intrinsèques et aux données parcellaires. D'autre part, une gestion systématique des données manquantes dans les résultats expérimentaux issus de mesures de champs est proposée : elle permet d'assurer l'admissibilité mécanique dans un problème d'identification. Même si ici elle a été utilisée dans le cas de l'identification data-driven, matériau qui échantillonnent sa réponse mécanique. Cette base de données peut être utilisée pour plusieurs applications : les techniques

, Ici, nous nous limiterons à celles issues des études proposées dans les deux derniers chapitres de cette thèse. D'une part, l'utilisation d'un bi-matériau ouvre la voie à l'identification de la réponse de matériaux anélastiques : avec un bi-matériau, la réponse en contrainte n'est plus en relation bijective avec la déformation. D'autre part, l'étude des sollicitations multiaxiales pose la question de la richesse des données permettant une qualité d, Concernant les perspectives, les approches data-driven en mécanique n'en étant qu'à leurs balbutiements, énormément d'études sont envisageables

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