Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.07205 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914969068503040 |
|---|---|
| author | Dias, João Paulo Ekwaro-Osire, Stephen Cunha Jr, Americo Dabetwar, Shweta Nispel, Abraham Alemayehu, Fisseha M. Endeshaw, Haileyesus B. |
| author_facet | Dias, João Paulo Ekwaro-Osire, Stephen Cunha Jr, Americo Dabetwar, Shweta Nispel, Abraham Alemayehu, Fisseha M. Endeshaw, Haileyesus B. |
| contents | This work proposes a parametric probabilistic approach to model damage accumulation using the double linear damage rule (DLDR) considering the existence of limited experimental fatigue data. A probabilistic version of DLDR is developed in which the joint distribution of the knee-point coordinates is obtained as a function of the joint distribution of the DLDR model input parameters. Considering information extracted from experiments containing a limited number of data points, an uncertainty quantification framework based on the Maximum Entropy Principle and Monte Carlo simulations is proposed to determine the distribution of fatigue life. The proposed approach is validated using fatigue life experiments available in the literature. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_07205 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Parametric probabilistic approach for cumulative fatigue damage using double linear damage rule considering limited data Dias, João Paulo Ekwaro-Osire, Stephen Cunha Jr, Americo Dabetwar, Shweta Nispel, Abraham Alemayehu, Fisseha M. Endeshaw, Haileyesus B. Computational Engineering, Finance, and Science 82D35 I.6.6 This work proposes a parametric probabilistic approach to model damage accumulation using the double linear damage rule (DLDR) considering the existence of limited experimental fatigue data. A probabilistic version of DLDR is developed in which the joint distribution of the knee-point coordinates is obtained as a function of the joint distribution of the DLDR model input parameters. Considering information extracted from experiments containing a limited number of data points, an uncertainty quantification framework based on the Maximum Entropy Principle and Monte Carlo simulations is proposed to determine the distribution of fatigue life. The proposed approach is validated using fatigue life experiments available in the literature. |
| title | Parametric probabilistic approach for cumulative fatigue damage using double linear damage rule considering limited data |
| topic | Computational Engineering, Finance, and Science 82D35 I.6.6 |
| url | https://arxiv.org/abs/2410.07205 |