Simultaneous identification of the parameters in the plasticity function for power hardening materials : A Bayesian approach
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929618610552832 |
|---|---|
| author | Tatar, Salih BenSalah, Mohamed |
| author_facet | Tatar, Salih BenSalah, Mohamed |
| contents | In this paper, we study simultaneous determination of the strain hardening exponent, the shear modulus and the yield stress in an inverse problem. First, we analyze the direct and the inverse problems. Then we formulate the inverse problem in the Bayesian framework. After solving the direct problem by an iterative approach, we propose a numerical method based on a Bayesian approach for the numerical solution of the inverse problem. Numerical examples with noisy data illustrate applicability and accuracy of the proposed method to some extent.\ |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_05241 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Simultaneous identification of the parameters in the plasticity function for power hardening materials : A Bayesian approach Tatar, Salih BenSalah, Mohamed Numerical Analysis Analysis of PDEs In this paper, we study simultaneous determination of the strain hardening exponent, the shear modulus and the yield stress in an inverse problem. First, we analyze the direct and the inverse problems. Then we formulate the inverse problem in the Bayesian framework. After solving the direct problem by an iterative approach, we propose a numerical method based on a Bayesian approach for the numerical solution of the inverse problem. Numerical examples with noisy data illustrate applicability and accuracy of the proposed method to some extent.\ |
| title | Simultaneous identification of the parameters in the plasticity function for power hardening materials : A Bayesian approach |
| topic | Numerical Analysis Analysis of PDEs |
| url | https://arxiv.org/abs/2412.05241 |