Data‐driven simulation of functional fatigue in shape memory alloy wires
(2024) In PAMM - Proceedings in Applied Mathematics and Mechanics 24(2).- Abstract
- Data-driven mechanics offers great potential in engineering applications, where the efficient simulation of complex and, in particular, path-dependent material behavior is often challenging. Within this approach, conventional material models are replaced by data sets containing snapshots of stress, strain and the history of both assumed to be sufficiently accurate representations of the underlying material behavior. Based on these snapshots and on physical admissibility, a distance function is built which is minimized to yield the boundary value problems' solution. The aim of this paper is to apply this framework to accurately simulate the complex behavior of shape memory alloy wires under cyclic loading, under which these materials... (More)
- Data-driven mechanics offers great potential in engineering applications, where the efficient simulation of complex and, in particular, path-dependent material behavior is often challenging. Within this approach, conventional material models are replaced by data sets containing snapshots of stress, strain and the history of both assumed to be sufficiently accurate representations of the underlying material behavior. Based on these snapshots and on physical admissibility, a distance function is built which is minimized to yield the boundary value problems' solution. The aim of this paper is to apply this framework to accurately simulate the complex behavior of shape memory alloy wires under cyclic loading, under which these materials exhibit a degradation of their features, denoted functional fatigue. The constructed synthetic data sets are enriched by real experimental data, showcasing that the data-driven method is capable of combining both approaches of classic material modeling and modern methods which directly incorporate experimental data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/18556f30-6113-4712-bea5-c9fc0451f7a6
- author
- Harnisch, Marius ; Bartel, Thorsten ; Weyergraf, Lukas ; Menzel, Andreas LU and Schweizer, Ben
- organization
- publishing date
- 2024-08-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PAMM - Proceedings in Applied Mathematics and Mechanics
- volume
- 24
- issue
- 2
- pages
- 8 pages
- publisher
- John Wiley & Sons Inc.
- ISSN
- 1617-7061
- DOI
- 10.1002/pamm.202400079
- language
- English
- LU publication?
- yes
- id
- 18556f30-6113-4712-bea5-c9fc0451f7a6
- date added to LUP
- 2026-01-20 14:01:17
- date last changed
- 2026-01-29 11:57:57
@article{18556f30-6113-4712-bea5-c9fc0451f7a6,
abstract = {{Data-driven mechanics offers great potential in engineering applications, where the efficient simulation of complex and, in particular, path-dependent material behavior is often challenging. Within this approach, conventional material models are replaced by data sets containing snapshots of stress, strain and the history of both assumed to be sufficiently accurate representations of the underlying material behavior. Based on these snapshots and on physical admissibility, a distance function is built which is minimized to yield the boundary value problems' solution. The aim of this paper is to apply this framework to accurately simulate the complex behavior of shape memory alloy wires under cyclic loading, under which these materials exhibit a degradation of their features, denoted functional fatigue. The constructed synthetic data sets are enriched by real experimental data, showcasing that the data-driven method is capable of combining both approaches of classic material modeling and modern methods which directly incorporate experimental data.}},
author = {{Harnisch, Marius and Bartel, Thorsten and Weyergraf, Lukas and Menzel, Andreas and Schweizer, Ben}},
issn = {{1617-7061}},
language = {{eng}},
month = {{08}},
number = {{2}},
publisher = {{John Wiley & Sons Inc.}},
series = {{PAMM - Proceedings in Applied Mathematics and Mechanics}},
title = {{Data‐driven simulation of functional fatigue in shape memory alloy wires}},
url = {{http://dx.doi.org/10.1002/pamm.202400079}},
doi = {{10.1002/pamm.202400079}},
volume = {{24}},
year = {{2024}},
}