Representative volume element for microscale analysis of additively manufactured composites (CROSBI ID 310949)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Gljušćić, Matej ; Franulović, Marina ; Lanc, Domagoj ; Žerovnik, Andrej
engleski
Representative volume element for microscale analysis of additively manufactured composites
The development of additive manufacturing technologies has been followed by an increase in material variety, especially by the introduction of numerous types of reinforcements to enhance the mechanical performance of basic polymers. Since the microstructure of these novel composites may vary in types, sizes, shapes, and ratios of reinforcements, it is necessary to optimize these parameters before conducting experimental validation. Hence, a microscale analysis based on representative volume element modeled according to the statistically significant constituent’s data acquired from the microscopic analysis is proposed. Moreover, to account for the weak fiber/matrix bounding in comparison with the ideal bond assumption, cohesive behavior can be prescribed at these interfaces. According to the type of reinforcement, three variations of RVE-s have been modeled in the Abaqus CAE environment utilizing periodic boundary conditions, and each was tested for longitudinal, transverse, and shear loading cases. The validation has been conducted on two unidirectional [0] and [90], as well as one multidirectional [45/−45]4s carbon fiber reinforced composite specimens. The experimental tests have been performed quasistatically and monitored using a digital image correlation system. Experimental and numerical results have been systematically compared with the published data, proposing a guideline for the protocol applicability and the necessity for further improvements.
Additive manufacturing ; Fiber reinforced composites ; Material behavior modeling ; Representative volume element ; Digital image correlation
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Podaci o izdanju
56
2022.
102902
13
objavljeno
2214-8604
2214-8604
10.1016/j.addma.2022.102902