Damage behavior analysis of Al/TiC particulate composite by acoustic emission monitoring and peridynamic modeling
The aim of this study is to characterize different damage mechanisms in an Aluminum (Al)/TiC particulate composite using acoustic emission (AE) monitoring, microstructure-based peridynamic (PD) modeling, and scanning electron microscope (SEM) observations. The Al/TiC composite with a 20% volume frac...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/08922f56c14d4efbb8f18ee08733d4a6 |
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| Sumario: | The aim of this study is to characterize different damage mechanisms in an Aluminum (Al)/TiC particulate composite using acoustic emission (AE) monitoring, microstructure-based peridynamic (PD) modeling, and scanning electron microscope (SEM) observations. The Al/TiC composite with a 20% volume fraction of TiC particles was produced using hot extrusion. Several representative volume elements (RVEs) were extracted from the SEM images by image processing, and the effect of particle morphology on the composite behavior was investigated. Rise time, energy, peak amplitude, and duration of the AE signals were utilized for clustering and relating the AE signals to deformation and damage mechanisms. PD modeling results and SEM pictures revealed that the damage mechanisms were initiated in the narrow TiC particles, Al matrix between close particles, and interface of the particle/matrix. The distribution of the particles had more effect on the damage initiation pattern than elastoplastic deformation before the damage initiation. Four sources of the AE signals were detected, i.e., plastic deformation of the Al, Al/Tic debonding, Al cracking, and fracture of the Tic particle. The AE signals of each mechanism were clustered by properties of waveform and by considering the predicted time interval of occurrence of each mechanism by PD modeling. PD model and AE technique predict the same sequence time of deformation and damage mechanisms, but the AE technique predicts the occurring time of each mechanism slightly earlier than the PD model. |
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