2020
DOI: 10.1016/j.commatsci.2019.109329
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A meshless multiscale approach to modeling severe plastic deformation of metals: Application to ECAE of pure copper

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Cited by 11 publications
(6 citation statements)
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“…As is observed (Figure 16), the overall shape of the shockwave that is generated at exact and identical time-steps for the two different methods is in good agreement. Kumar et al [161] developed a meshless multi-scale approach to modeling severe plastic deformation of copper in equal-channel angular extrusion. They used a vertical homogenization approach based on a maximum-entropy meshless formulation on the macroscale.…”
Section: Meshless Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…As is observed (Figure 16), the overall shape of the shockwave that is generated at exact and identical time-steps for the two different methods is in good agreement. Kumar et al [161] developed a meshless multi-scale approach to modeling severe plastic deformation of copper in equal-channel angular extrusion. They used a vertical homogenization approach based on a maximum-entropy meshless formulation on the macroscale.…”
Section: Meshless Methodsmentioning
confidence: 99%
“…Figure17. Schematic illustration of the vertical scale-bridging approach, a Taylor recrystallization model, and a crystal plasticity model (reproduced with permission from Reference[161]; copyright © 2020 Elsevier).…”
mentioning
confidence: 99%
“…In FLIGA, we employ the material point integration strategy, which is well known from meshless methods, see e.g. Kumar et al [11,34]. This technique attributes to the quadrature points a Lagrangian particle character in the sense of (10).…”
Section: Materials Point Integrationmentioning
confidence: 99%
“…In FLIGA, we employ the material point integration strategy, which is well known from meshless methods, see, e.g. Kumar et al (2019Kumar et al ( , 2020a. This technique attributes to the quadrature points a Lagrangian particle character in the sense of (10).…”
Section: Materials Point Integrationmentioning
confidence: 99%

Floating Isogeometric Analysis

Hille,
Kumar,
De Lorenzis
2021
Preprint
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