000022303 001__ 22303
000022303 005__ 20170622150006.0
000022303 04107 $$aeng
000022303 046__ $$k2015-05-25
000022303 100__ $$aPlevris, Vagelis
000022303 24500 $$aANISOTROPIC FAILURE CRITERION FOR BRITLE MATERIALS USING ARTIFICIAL NEURAL NETWORKS

000022303 24630 $$n5.$$pComputational Methods in Structural Dynamics and Earhquake Engineering
000022303 260__ $$bNational Technical University of Athens, 2015
000022303 506__ $$arestricted
000022303 520__ $$2eng$$aBrittle materials are complex composite materials and a model is necessitated to realistically predict their load carrying capacity under any stress-state. During the last decades, a lot of failure criteria have been proposed for these materials in the literature. However, the majority of these models may substantially over-estimate the strength of the failure surface envelope. To overcome this problem a new approach is proposed which is based on Artificial Neural Networks (ANNs) techniques. The proposed approach is applied to a characteristic brittle anisotropic material such as the masonry material. The Neural Network managed to produce closed failure curves extending in all four quadrants of principal stresses, thus fully covering the compression and the tension stress areas. The comparison of the derived results with experimental findings demonstrates the promising potential of using ANNs for the reliable and robust approximation of the failure surface under biaxial stress state.

000022303 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000022303 653__ $$aAnisotropy, brittle material, failure criterion, Artificial Neural Network.

000022303 7112_ $$aCOMPDYN 2015 - 5th International Thematic Conference$$cCrete (GR)$$d2015-05-25 / 2015-05-27$$gCOMPDYN2015
000022303 720__ $$aPlevris, Vagelis$$iAsteris, Panagiotis
000022303 8560_ $$ffischerc@itam.cas.cz
000022303 8564_ $$s719258$$uhttps://invenio.itam.cas.cz/record/22303/files/C3648.pdf$$yOriginal version of the author's contribution as presented on CD, section: 
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000022303 962__ $$r22030
000022303 980__ $$aPAPER