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Approximate Bayesian assisted inverse method for identification of parameters of variable stiffness composite laminates.

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Title: Approximate Bayesian assisted inverse method for identification of parameters of variable stiffness composite laminates.
Authors: Chen, Boxuan1,2 (AUTHOR), Zeng, Yang1,2 (AUTHOR), Wang, Hu1,2 (AUTHOR) wanghu@hnu.edu.cn, Li, Enying3 (AUTHOR)
Source: Composite Structures. Jul2021, Vol. 267, pN.PAG-N.PAG. 1p.
Subjects: Parameter identification, Laminated materials, Tikhonov regularization, Composite plates, Inverse problems, Sampling methods
Abstract: The uncertainties of parameters are important for the performance of Variable Stiffness (VS) composite laminate plates. When parameters of VS composite laminate are given, it is easy to investigate physical characteristics of VS composite laminate. However, it is difficult to identify values of parameters due to a typical ill-posed inverse problem. In order to address this problem, an innovative approximate Bayesian computation (ABC) is suggested to identify composite parameters by considering uncertainties in this study. Compared with traditional Bayesian framework, ABC can avoid the calculation of likelihood which makes inverse procedure more complex or even intractable in practice. Generally, four advanced techniques are integrated to satisfy demands of ABC method in this study. In the suggested framework, a powerful Auto-Encoder (AE) is used to reduce calculation of the response with little information loss. Sequentially, Tikhonov regularization is integrated into ABC. Furthermore, to reduce computational cost, a high sample accepted rate-adaptive nested sampling method and Neural Network (NN) used to construct the mapping between parameters and responses are utilized. Finally, the efficiency and flexibility of the proposed method are validated by three cases. [ABSTRACT FROM AUTHOR]
Copyright of Composite Structures 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
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DbLabel: Engineering Source
An: 150295315
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  Data: Approximate Bayesian assisted inverse method for identification of parameters of variable stiffness composite laminates.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Boxuan%22">Chen, Boxuan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zeng%2C+Yang%22">Zeng, Yang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Hu%22">Wang, Hu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> wanghu@hnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Enying%22">Li, Enying</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Composite+Structures%22">Composite Structures</searchLink>. Jul2021, Vol. 267, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Parameter+identification%22">Parameter identification</searchLink><br /><searchLink fieldCode="DE" term="%22Laminated+materials%22">Laminated materials</searchLink><br /><searchLink fieldCode="DE" term="%22Tikhonov+regularization%22">Tikhonov regularization</searchLink><br /><searchLink fieldCode="DE" term="%22Composite+plates%22">Composite plates</searchLink><br /><searchLink fieldCode="DE" term="%22Inverse+problems%22">Inverse problems</searchLink><br /><searchLink fieldCode="DE" term="%22Sampling+methods%22">Sampling methods</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The uncertainties of parameters are important for the performance of Variable Stiffness (VS) composite laminate plates. When parameters of VS composite laminate are given, it is easy to investigate physical characteristics of VS composite laminate. However, it is difficult to identify values of parameters due to a typical ill-posed inverse problem. In order to address this problem, an innovative approximate Bayesian computation (ABC) is suggested to identify composite parameters by considering uncertainties in this study. Compared with traditional Bayesian framework, ABC can avoid the calculation of likelihood which makes inverse procedure more complex or even intractable in practice. Generally, four advanced techniques are integrated to satisfy demands of ABC method in this study. In the suggested framework, a powerful Auto-Encoder (AE) is used to reduce calculation of the response with little information loss. Sequentially, Tikhonov regularization is integrated into ABC. Furthermore, to reduce computational cost, a high sample accepted rate-adaptive nested sampling method and Neural Network (NN) used to construct the mapping between parameters and responses are utilized. Finally, the efficiency and flexibility of the proposed method are validated by three cases. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Composite Structures 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:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.compstruct.2021.113853
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Parameter identification
        Type: general
      – SubjectFull: Laminated materials
        Type: general
      – SubjectFull: Tikhonov regularization
        Type: general
      – SubjectFull: Composite plates
        Type: general
      – SubjectFull: Inverse problems
        Type: general
      – SubjectFull: Sampling methods
        Type: general
    Titles:
      – TitleFull: Approximate Bayesian assisted inverse method for identification of parameters of variable stiffness composite laminates.
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            NameFull: Chen, Boxuan
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            NameFull: Zeng, Yang
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            NameFull: Wang, Hu
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          Name:
            NameFull: Li, Enying
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          Dates:
            – D: 01
              M: 07
              Text: Jul2021
              Type: published
              Y: 2021
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              Value: 02638223
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              Value: 267
          Titles:
            – TitleFull: Composite Structures
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