RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT)
To resolve the poor universality and low accuracy of the existing surrogate models for reliability analysis, a hybrid surrogate model based on radial basis function（RBF） and sparse polynomial chaotic expansion（SPCE） was proposed. It realized rapid and accurate prediction of performance functions to...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2023-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.05.014 |
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| _version_ | 1841534171406663680 |
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| author | ZHAO ZiDa ZHANG DeQuan OUYANG Heng WU ZePing |
| author_facet | ZHAO ZiDa ZHANG DeQuan OUYANG Heng WU ZePing |
| author_sort | ZHAO ZiDa |
| collection | DOAJ |
| description | To resolve the poor universality and low accuracy of the existing surrogate models for reliability analysis, a hybrid surrogate model based on radial basis function（RBF） and sparse polynomial chaotic expansion（SPCE） was proposed. It realized rapid and accurate prediction of performance functions to improve the engineering applicability and the accuracy of structural reliability analysis. Importantly, the orthogonal matching pursuit technology was applied to obtain the important terms in PCE, and an SPCE model could be established directly to form the RBF-SPCE model for improving the prediction accuracy of surrogate model. Subsequently, the reliability analysis of complex structures is carried out based on Monte Carlo simulation（MCS）. In this work, three simulation cases were implemented to compare the performance of the proposed method with the traditional RBF model and augmented RBF model. The results illustrated that the proposed method has higher accuracy and efficiency for structural reliability analysis. Finally, a vehicle side impact engineering example illustrated that the proposed method has good engineering applicability for complex problems. |
| format | Article |
| id | doaj-art-603191897ad44187bdc38f712331eb7e |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2023-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-603191897ad44187bdc38f712331eb7e2025-01-15T02:44:24ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692023-01-011108111644026234RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT)ZHAO ZiDaZHANG DeQuanOUYANG HengWU ZePingTo resolve the poor universality and low accuracy of the existing surrogate models for reliability analysis, a hybrid surrogate model based on radial basis function（RBF） and sparse polynomial chaotic expansion（SPCE） was proposed. It realized rapid and accurate prediction of performance functions to improve the engineering applicability and the accuracy of structural reliability analysis. Importantly, the orthogonal matching pursuit technology was applied to obtain the important terms in PCE, and an SPCE model could be established directly to form the RBF-SPCE model for improving the prediction accuracy of surrogate model. Subsequently, the reliability analysis of complex structures is carried out based on Monte Carlo simulation（MCS）. In this work, three simulation cases were implemented to compare the performance of the proposed method with the traditional RBF model and augmented RBF model. The results illustrated that the proposed method has higher accuracy and efficiency for structural reliability analysis. Finally, a vehicle side impact engineering example illustrated that the proposed method has good engineering applicability for complex problems.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.05.014Radial basis functionSparse polynomial chaotic expansionHybrid surrogate modelReliability analysisComputational efficiency |
| spellingShingle | ZHAO ZiDa ZHANG DeQuan OUYANG Heng WU ZePing RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT) Jixie qiangdu Radial basis function Sparse polynomial chaotic expansion Hybrid surrogate model Reliability analysis Computational efficiency |
| title | RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT) |
| title_full | RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT) |
| title_fullStr | RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT) |
| title_full_unstemmed | RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT) |
| title_short | RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT) |
| title_sort | reliability analysis on hybrid surrogate model of radial basis function and sparse polynomial chaos expansion mt |
| topic | Radial basis function Sparse polynomial chaotic expansion Hybrid surrogate model Reliability analysis Computational efficiency |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.05.014 |
| work_keys_str_mv | AT zhaozida reliabilityanalysisonhybridsurrogatemodelofradialbasisfunctionandsparsepolynomialchaosexpansionmt AT zhangdequan reliabilityanalysisonhybridsurrogatemodelofradialbasisfunctionandsparsepolynomialchaosexpansionmt AT ouyangheng reliabilityanalysisonhybridsurrogatemodelofradialbasisfunctionandsparsepolynomialchaosexpansionmt AT wuzeping reliabilityanalysisonhybridsurrogatemodelofradialbasisfunctionandsparsepolynomialchaosexpansionmt |