Details
| Original language | English |
|---|---|
| Article number | 117134 |
| Journal | Computer Methods in Applied Mechanics and Engineering |
| Volume | 429 |
| Early online date | 8 Jul 2024 |
| Publication status | Published - 1 Sept 2024 |
Abstract
Shape memory alloys are remarkable ‘smart’ materials used in a broad spectrum of applications, ranging from aerospace to robotics, thanks to their unique thermomechanical coupling capabilities. Given the complex properties of shape memory alloys, which are largely influenced by thermal and mechanical loads, as well as their loading history, predicting their behavior can be challenging. Consequently, there exists a pronounced demand for an efficient material model to simulate the behavior of these alloys. This paper introduces a material model rooted in Hamilton's principle. The key advantages of the presented material model encompass a more accurate depiction of the internal variable evolution and heightened robustness. As such, the proposed material model signifies an advancement in the realistic and efficient simulation of shape memory alloys.
Keywords
- Finite element method, Phase transformation, Shape memory alloy, Thermo-mechanical coupling, Variational modeling
ASJC Scopus subject areas
- Engineering(all)
- Computational Mechanics
- Engineering(all)
- Mechanics of Materials
- Engineering(all)
- Mechanical Engineering
- Physics and Astronomy(all)
- General Physics and Astronomy
- Computer Science(all)
- Computer Science Applications
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In: Computer Methods in Applied Mechanics and Engineering, Vol. 429, 117134, 01.09.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - An energy-based material model for the simulation of shape memory alloys under complex boundary value problems
AU - Erdogan, Cem
AU - Bode, Tobias
AU - Junker, Philipp
N1 - Publisher Copyright: © 2024 The Author(s)
PY - 2024/9/1
Y1 - 2024/9/1
N2 - Shape memory alloys are remarkable ‘smart’ materials used in a broad spectrum of applications, ranging from aerospace to robotics, thanks to their unique thermomechanical coupling capabilities. Given the complex properties of shape memory alloys, which are largely influenced by thermal and mechanical loads, as well as their loading history, predicting their behavior can be challenging. Consequently, there exists a pronounced demand for an efficient material model to simulate the behavior of these alloys. This paper introduces a material model rooted in Hamilton's principle. The key advantages of the presented material model encompass a more accurate depiction of the internal variable evolution and heightened robustness. As such, the proposed material model signifies an advancement in the realistic and efficient simulation of shape memory alloys.
AB - Shape memory alloys are remarkable ‘smart’ materials used in a broad spectrum of applications, ranging from aerospace to robotics, thanks to their unique thermomechanical coupling capabilities. Given the complex properties of shape memory alloys, which are largely influenced by thermal and mechanical loads, as well as their loading history, predicting their behavior can be challenging. Consequently, there exists a pronounced demand for an efficient material model to simulate the behavior of these alloys. This paper introduces a material model rooted in Hamilton's principle. The key advantages of the presented material model encompass a more accurate depiction of the internal variable evolution and heightened robustness. As such, the proposed material model signifies an advancement in the realistic and efficient simulation of shape memory alloys.
KW - Finite element method
KW - Phase transformation
KW - Shape memory alloy
KW - Thermo-mechanical coupling
KW - Variational modeling
UR - http://www.scopus.com/inward/record.url?scp=85197554688&partnerID=8YFLogxK
U2 - 10.1016/j.cma.2024.117134
DO - 10.1016/j.cma.2024.117134
M3 - Article
AN - SCOPUS:85197554688
VL - 429
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
SN - 0045-7825
M1 - 117134
ER -