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Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression

Functionally Graded Materials (FGM) is the advanced material that covers the advantages of both metal and ceramic which contain FGM. Due to the perfect combination, FGM plate is widely developed with the requirement for the practical application to avoid the difficulties from conventional approaches...

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Main Authors: Huan, Thanh Duong, Hieu, Chi Phan, Tien, Thinh Le
Format: Bài trích
Language:English
Published: Springer 2022
Subjects:
Functionally graded material
Buckling analysis
Online Access:https://link.springer.com/chapter/10.1007/978-3-030-92574-1_30
https://dlib.phenikaa-uni.edu.vn/handle/PNK/5716
https://doi.org/10.1007/978-3-030-92574-1_30
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spelling oai:localhost:PNK-57162022-08-17T05:54:50Z Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression Huan, Thanh Duong Hieu, Chi Phan Tien, Thinh Le Functionally graded material Buckling analysis Functionally Graded Materials (FGM) is the advanced material that covers the advantages of both metal and ceramic which contain FGM. Due to the perfect combination, FGM plate is widely developed with the requirement for the practical application to avoid the difficulties from conventional approaches. Consequently, the study establishes the database from analytical model and uses it for developing a machine learning model in the desire of finding an alternative model to predict critical buckling load of the plate. Such a machine learning model is crucial for predicting critical buckling load of the FGM plate without complexity of analytical developments or finite element resources. The Gaussian Process Regression model has been developed based on the database containing 1000 labeled samples created from the analytical model. The Gaussian Process Regression models with and without optimization process are compared and the outstanding of the model with the optimization algorithm is revealed. The proposed model is validated on both train and test set with the R-square values larger than 0.99 and errors are significantly low indicating that the proposed model exhibits the required ability. 2022-05-05T07:26:11Z 2022-05-05T07:26:11Z 2022 Bài trích https://link.springer.com/chapter/10.1007/978-3-030-92574-1_30 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5716 https://doi.org/10.1007/978-3-030-92574-1_30 en Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic Functionally graded material
Buckling analysis
spellingShingle Functionally graded material
Buckling analysis
Huan, Thanh Duong
Hieu, Chi Phan
Tien, Thinh Le
Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression
description Functionally Graded Materials (FGM) is the advanced material that covers the advantages of both metal and ceramic which contain FGM. Due to the perfect combination, FGM plate is widely developed with the requirement for the practical application to avoid the difficulties from conventional approaches. Consequently, the study establishes the database from analytical model and uses it for developing a machine learning model in the desire of finding an alternative model to predict critical buckling load of the plate. Such a machine learning model is crucial for predicting critical buckling load of the FGM plate without complexity of analytical developments or finite element resources. The Gaussian Process Regression model has been developed based on the database containing 1000 labeled samples created from the analytical model. The Gaussian Process Regression models with and without optimization process are compared and the outstanding of the model with the optimization algorithm is revealed. The proposed model is validated on both train and test set with the R-square values larger than 0.99 and errors are significantly low indicating that the proposed model exhibits the required ability.
format Bài trích
author Huan, Thanh Duong
Hieu, Chi Phan
Tien, Thinh Le
author_facet Huan, Thanh Duong
Hieu, Chi Phan
Tien, Thinh Le
author_sort Huan, Thanh Duong
title Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression
title_short Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression
title_full Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression
title_fullStr Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression
title_full_unstemmed Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression
title_sort critical buckling load evaluation of functionally graded material plate using gaussian process regression
publisher Springer
publishDate 2022
url https://link.springer.com/chapter/10.1007/978-3-030-92574-1_30
https://dlib.phenikaa-uni.edu.vn/handle/PNK/5716
https://doi.org/10.1007/978-3-030-92574-1_30
_version_ 1751856279088791552
score 8.891145

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