An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation
In this paper, an inverse method is proposed for measuring the elastoplastic properties of metallic materials using a spherical indentation experiment. In the new method, the elastoplastic parameters are correlated with sub-space coordinates of indentation imprints using proper orthogonal decomposit...
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| Format: | Article |
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MDPI AG
2021-11-01
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| Online Access: | https://www.mdpi.com/1996-1944/14/23/7105 |
| _version_ | 1797507555396681728 |
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| author | Mingzhi Wang Weidong Wang |
| author_facet | Mingzhi Wang Weidong Wang |
| author_sort | Mingzhi Wang |
| collection | DOAJ |
| description | In this paper, an inverse method is proposed for measuring the elastoplastic properties of metallic materials using a spherical indentation experiment. In the new method, the elastoplastic parameters are correlated with sub-space coordinates of indentation imprints using proper orthogonal decomposition (POD), and inverse identification of material properties is solved using a statistical Bayesian framework. The advantage of the method is that model parameters in the numerical optimization process are treated as the stochastic variables, and potential uncertainties can be considered. The posterior results obtained from the measuring method can provide valuable probabilistic information of the estimated elastoplastic properties. The proposed method is verified by the application on 2099-T83 Al-Li alloys. Results indicate that posterior distribution of material parameters exhibits more than one peak region when indentation load is not large enough. In addition, using the weighting imprints under different loads can facilitate the uniqueness in identification of elastoplastic parameters. The influence of the weighting coefficient on posterior identification results is analyzed. The elastoplastic properties identified by indentation and tensile experiment show good agreement. Results indicate that the established measuring method is effective and reliable. |
| first_indexed | 2024-03-10T04:50:05Z |
| format | Article |
| id | doaj.art-2dbc5a32b96245fda544ea042e2b2383 |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-10T04:50:05Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
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| series | Materials |
| spelling | doaj.art-2dbc5a32b96245fda544ea042e2b23832023-11-23T02:38:21ZengMDPI AGMaterials1996-19442021-11-011423710510.3390/ma14237105An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical IndentationMingzhi Wang0Weidong Wang1School of Mechano-Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Mechano-Electronic Engineering, Xidian University, Xi’an 710071, ChinaIn this paper, an inverse method is proposed for measuring the elastoplastic properties of metallic materials using a spherical indentation experiment. In the new method, the elastoplastic parameters are correlated with sub-space coordinates of indentation imprints using proper orthogonal decomposition (POD), and inverse identification of material properties is solved using a statistical Bayesian framework. The advantage of the method is that model parameters in the numerical optimization process are treated as the stochastic variables, and potential uncertainties can be considered. The posterior results obtained from the measuring method can provide valuable probabilistic information of the estimated elastoplastic properties. The proposed method is verified by the application on 2099-T83 Al-Li alloys. Results indicate that posterior distribution of material parameters exhibits more than one peak region when indentation load is not large enough. In addition, using the weighting imprints under different loads can facilitate the uniqueness in identification of elastoplastic parameters. The influence of the weighting coefficient on posterior identification results is analyzed. The elastoplastic properties identified by indentation and tensile experiment show good agreement. Results indicate that the established measuring method is effective and reliable.https://www.mdpi.com/1996-1944/14/23/7105indentation experimentmetallic materialselastoplastic propertiesmechanical measurementBayesian modelinverse problem |
| spellingShingle | Mingzhi Wang Weidong Wang An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation Materials indentation experiment metallic materials elastoplastic properties mechanical measurement Bayesian model inverse problem |
| title | An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation |
| title_full | An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation |
| title_fullStr | An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation |
| title_full_unstemmed | An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation |
| title_short | An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation |
| title_sort | inverse method for measuring elastoplastic properties of metallic materials using bayesian model and residual imprint from spherical indentation |
| topic | indentation experiment metallic materials elastoplastic properties mechanical measurement Bayesian model inverse problem |
| url | https://www.mdpi.com/1996-1944/14/23/7105 |
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