Details
| Original language | English |
|---|---|
| Title of host publication | Carbon Nanotube-Reinforced Polymers |
| Subtitle of host publication | From Nanoscale to Macroscale |
| Publisher | Elsevier Inc. |
| Pages | 465-477 |
| Number of pages | 13 |
| ISBN (Electronic) | 9780323482226 |
| ISBN (Print) | 9780323482219 |
| Publication status | Published - 5 Jan 2018 |
Abstract
This chapter provides an overview on multiscale approaches applied to carbon nanotube-reinforced polymers (CNRPs). Multiscale methods can be classified into hierarchical or sequential multiscale methods, semiconcurrent multiscale methods, and concurrent multiscale methods. Hierarchical multiscale methods transfer information only from the fine scale to the coarse scale. Classical approaches are computational homogenization or the Cauchy-Born rule; the latter one is usually based on a periodic structure and hence not applicable for CNRPs. In semiconcurrent multiscale methods, information is transferred also back from the coarse scale to the fine scale during the course of the simulation. They seem computationally more feasible for nonlinear responses, as they account only for states that actually occur in the simulation. Many semiconcurrent multiscale methods, such as the FE2 approach are based on representative volume elements. In concurrent multiscale methods, the fine scale is directly embedded into the coarse scale. Many interesting results predicting mechanical, thermal, electrical, or chemical properties of CNRPs have been studied with hierarchical multiscale approaches. Far less work on the more complex semiconcurrent or concurrent multiscale methods for CNRPs in turn can be found in the literature. However, these methods promise to address many unresolved aspects, such as fracture.
Keywords
- Carbon nanotube-reinforced polymers (CNRPs), Cauchy-Born rule, Concurrent multiscale methods, Handshake coupling methods, Hierarchical multiscale methods, Semiconcurrent multiscale methods
ASJC Scopus subject areas
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Carbon Nanotube-Reinforced Polymers: From Nanoscale to Macroscale. Elsevier Inc., 2018. p. 465-477.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Computational multiscale modeling of carbon nanotube-reinforced polymers
AU - Silani, Mohammad
AU - Rabczuk, Timon
AU - Zhuang, Xiaoying
PY - 2018/1/5
Y1 - 2018/1/5
N2 - This chapter provides an overview on multiscale approaches applied to carbon nanotube-reinforced polymers (CNRPs). Multiscale methods can be classified into hierarchical or sequential multiscale methods, semiconcurrent multiscale methods, and concurrent multiscale methods. Hierarchical multiscale methods transfer information only from the fine scale to the coarse scale. Classical approaches are computational homogenization or the Cauchy-Born rule; the latter one is usually based on a periodic structure and hence not applicable for CNRPs. In semiconcurrent multiscale methods, information is transferred also back from the coarse scale to the fine scale during the course of the simulation. They seem computationally more feasible for nonlinear responses, as they account only for states that actually occur in the simulation. Many semiconcurrent multiscale methods, such as the FE2 approach are based on representative volume elements. In concurrent multiscale methods, the fine scale is directly embedded into the coarse scale. Many interesting results predicting mechanical, thermal, electrical, or chemical properties of CNRPs have been studied with hierarchical multiscale approaches. Far less work on the more complex semiconcurrent or concurrent multiscale methods for CNRPs in turn can be found in the literature. However, these methods promise to address many unresolved aspects, such as fracture.
AB - This chapter provides an overview on multiscale approaches applied to carbon nanotube-reinforced polymers (CNRPs). Multiscale methods can be classified into hierarchical or sequential multiscale methods, semiconcurrent multiscale methods, and concurrent multiscale methods. Hierarchical multiscale methods transfer information only from the fine scale to the coarse scale. Classical approaches are computational homogenization or the Cauchy-Born rule; the latter one is usually based on a periodic structure and hence not applicable for CNRPs. In semiconcurrent multiscale methods, information is transferred also back from the coarse scale to the fine scale during the course of the simulation. They seem computationally more feasible for nonlinear responses, as they account only for states that actually occur in the simulation. Many semiconcurrent multiscale methods, such as the FE2 approach are based on representative volume elements. In concurrent multiscale methods, the fine scale is directly embedded into the coarse scale. Many interesting results predicting mechanical, thermal, electrical, or chemical properties of CNRPs have been studied with hierarchical multiscale approaches. Far less work on the more complex semiconcurrent or concurrent multiscale methods for CNRPs in turn can be found in the literature. However, these methods promise to address many unresolved aspects, such as fracture.
KW - Carbon nanotube-reinforced polymers (CNRPs)
KW - Cauchy-Born rule
KW - Concurrent multiscale methods
KW - Handshake coupling methods
KW - Hierarchical multiscale methods
KW - Semiconcurrent multiscale methods
UR - http://www.scopus.com/inward/record.url?scp=85054888367&partnerID=8YFLogxK
U2 - 10.1016/b978-0-323-48221-9.00018-2
DO - 10.1016/b978-0-323-48221-9.00018-2
M3 - Contribution to book/anthology
AN - SCOPUS:85054888367
SN - 9780323482219
SP - 465
EP - 477
BT - Carbon Nanotube-Reinforced Polymers
PB - Elsevier Inc.
ER -