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Characterize traction–separation relation and interfacial imperfections by data-driven machine learning models
This article combines machine learning (ML), finite element analysis (FEA), and empirical experiments to develop data-driven models that characterize interfacial mechanical properties precisely. It also provides a code package containing trained ML models, allowing other researchers to establish T–S relations for different material interfaces.
Date:
July 12, 2021
Creator:
Ferdousi, Sanjida; Chen, Qiyi; Soltani, Mehrzad; Zhu, Jiadeng; Cao, Pengfei; Choi, Wonbong et al.
System:
The UNT Digital Library
Theories and analyses of functionally graded circular plates
This article presents the governing equations and analytical solutions of the classical and shear deformation theories of functionally graded axisymmetric circular plates.
Date:
June 12, 2021
Creator:
Reddy, J. N.; Ruocco, Eugenio; Loya, Jose Antonio & Neves, Ana M. A.
System:
The UNT Digital Library