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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.
Object Type:
Article
System:
The UNT Digital Library
Laser-Assisted Machining (LAM) of Hard Tissues and Bones
Patent relating to a system and methods of machining hard tissues, such as bone.
Date:
March 17, 2014
Creator:
Dahotre, Narendra B. & Santhanakrishnan, Soundarapandian
Object Type:
Patent
System:
The UNT Digital Library