Bayesian calibration of continuum damage model parameters for an oxide-oxide ceramic matrix composite using inhomogeneous experimental data.
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| Title: | Bayesian calibration of continuum damage model parameters for an oxide-oxide ceramic matrix composite using inhomogeneous experimental data. |
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| Authors: | Generale, Adam P.1 (AUTHOR) agenerale3@gatech.edu, Hall, Richard B.2 (AUTHOR) richard.hall.16@us.af.mil, Brockman, Robert A.3 (AUTHOR) Robert.Brockman@udri.udayton.edu, Joseph, V. Roshan4 (AUTHOR) roshan@gatech.edu, Jefferson, George2 (AUTHOR) george.jefferson.1@us.af.mil, Zawada, Larry2,5 (AUTHOR), Pierce, Jennifer2,3 (AUTHOR) Jennifer.Pierce@udri.udayton.edu, Kalidindi, Surya R.1,6 (AUTHOR) surya.kalidindi@me.gatech.edu |
| Source: | Mechanics of Materials. Dec2022, Vol. 175, pN.PAG-N.PAG. 1p. |
| Subjects: | Damage models, Continuum damage mechanics, Calibration, Bayesian field theory, Partial least squares regression, Markov chain Monte Carlo |
| Abstract: | The calibration of continuum damage mechanics (CDM) models is often performed by least-squares regression through the design of specifically crafted experiments to identify a deterministic solution of model parameters minimizing the squared error between the model prediction and the corresponding experimental result. Specifically, this work demonstrates a successful application of Bayesian inference for the simultaneous estimation of eleven material parameters of a viscous multimode CDM model conditioned upon a small inhomogeneous multiaxial experimental dataset. The stochastic treatment of CDM model parameters provides uncertainty estimates, enables the propagation of uncertainty into further analyses, and provides for principled decision making regarding informative subsequent experimental tests of value. The methodology presented in this work is also broadly applicable to various mechanical models with high-dimensional parameter sets. • High-dimensional viscous multimode continuum damage model parameters identified through Bayesian inference. • Mixed effects statistical model enables simultaneous calibration against inhomogeneous experimental dataset. • Posterior distribution can guide informative additional experimental runs. [ABSTRACT FROM AUTHOR] |
| Copyright of Mechanics of Materials is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 160979166 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Bayesian calibration of continuum damage model parameters for an oxide-oxide ceramic matrix composite using inhomogeneous experimental data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Generale%2C+Adam+P%2E%22">Generale, Adam P.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> agenerale3@gatech.edu</i><br /><searchLink fieldCode="AR" term="%22Hall%2C+Richard+B%2E%22">Hall, Richard B.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> richard.hall.16@us.af.mil</i><br /><searchLink fieldCode="AR" term="%22Brockman%2C+Robert+A%2E%22">Brockman, Robert A.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> Robert.Brockman@udri.udayton.edu</i><br /><searchLink fieldCode="AR" term="%22Joseph%2C+V%2E+Roshan%22">Joseph, V. Roshan</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> roshan@gatech.edu</i><br /><searchLink fieldCode="AR" term="%22Jefferson%2C+George%22">Jefferson, George</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> george.jefferson.1@us.af.mil</i><br /><searchLink fieldCode="AR" term="%22Zawada%2C+Larry%22">Zawada, Larry</searchLink><relatesTo>2,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pierce%2C+Jennifer%22">Pierce, Jennifer</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> Jennifer.Pierce@udri.udayton.edu</i><br /><searchLink fieldCode="AR" term="%22Kalidindi%2C+Surya+R%2E%22">Kalidindi, Surya R.</searchLink><relatesTo>1,6</relatesTo> (AUTHOR)<i> surya.kalidindi@me.gatech.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Mechanics+of+Materials%22">Mechanics of Materials</searchLink>. Dec2022, Vol. 175, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Damage+models%22">Damage models</searchLink><br /><searchLink fieldCode="DE" term="%22Continuum+damage+mechanics%22">Continuum damage mechanics</searchLink><br /><searchLink fieldCode="DE" term="%22Calibration%22">Calibration</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+field+theory%22">Bayesian field theory</searchLink><br /><searchLink fieldCode="DE" term="%22Partial+least+squares+regression%22">Partial least squares regression</searchLink><br /><searchLink fieldCode="DE" term="%22Markov+chain+Monte+Carlo%22">Markov chain Monte Carlo</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The calibration of continuum damage mechanics (CDM) models is often performed by least-squares regression through the design of specifically crafted experiments to identify a deterministic solution of model parameters minimizing the squared error between the model prediction and the corresponding experimental result. Specifically, this work demonstrates a successful application of Bayesian inference for the simultaneous estimation of eleven material parameters of a viscous multimode CDM model conditioned upon a small inhomogeneous multiaxial experimental dataset. The stochastic treatment of CDM model parameters provides uncertainty estimates, enables the propagation of uncertainty into further analyses, and provides for principled decision making regarding informative subsequent experimental tests of value. The methodology presented in this work is also broadly applicable to various mechanical models with high-dimensional parameter sets. • High-dimensional viscous multimode continuum damage model parameters identified through Bayesian inference. • Mixed effects statistical model enables simultaneous calibration against inhomogeneous experimental dataset. • Posterior distribution can guide informative additional experimental runs. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Mechanics of Materials is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.mechmat.2022.104487 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Damage models Type: general – SubjectFull: Continuum damage mechanics Type: general – SubjectFull: Calibration Type: general – SubjectFull: Bayesian field theory Type: general – SubjectFull: Partial least squares regression Type: general – SubjectFull: Markov chain Monte Carlo Type: general Titles: – TitleFull: Bayesian calibration of continuum damage model parameters for an oxide-oxide ceramic matrix composite using inhomogeneous experimental data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Generale, Adam P. – PersonEntity: Name: NameFull: Hall, Richard B. – PersonEntity: Name: NameFull: Brockman, Robert A. – PersonEntity: Name: NameFull: Joseph, V. Roshan – PersonEntity: Name: NameFull: Jefferson, George – PersonEntity: Name: NameFull: Zawada, Larry – PersonEntity: Name: NameFull: Pierce, Jennifer – PersonEntity: Name: NameFull: Kalidindi, Surya R. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 01676636 Numbering: – Type: volume Value: 175 Titles: – TitleFull: Mechanics of Materials Type: main |
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