Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem
ObjectiveMulti-fidelity surrogate (MFS) modeling technology can reduce simulation costs in the design process of engineering products. In order to relax the hierarchical relationship between low-fidelity (LF) analysis models and broaden the engineering application of MFS, this paper proposes an MFS...
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| Format: | Article |
| Language: | English |
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Editorial Office of Chinese Journal of Ship Research
2024-12-01
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| Series: | Zhongguo Jianchuan Yanjiu |
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| Online Access: | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03980 |
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| author | Meng CHENG Qi ZHOU Xiao WEI Jian WANG Wei CHEN |
| author_facet | Meng CHENG Qi ZHOU Xiao WEI Jian WANG Wei CHEN |
| author_sort | Meng CHENG |
| collection | DOAJ |
| description | ObjectiveMulti-fidelity surrogate (MFS) modeling technology can reduce simulation costs in the design process of engineering products. In order to relax the hierarchical relationship between low-fidelity (LF) analysis models and broaden the engineering application of MFS, this paper proposes an MFS modelling method based on variance-weighted sum (VWS-MFS) for the fusion of multiple non-hierarchical LF data. MethodThe proposed method builds LF surrogate models using Kriging technology. By quantifying the uncertainty of the LF surrogate models with variance, the non-hierarchical LF data is weighted to construct a trend function. In addition, the improved hierarchical Kriging (IHK) model is introduced to fuse the high-fidelity (HF) and LF data, enabling the correction coefficient of the trend function to change throughout the design space. The proposed method is then tested on nine typical examples and applied to the performance prediction of a vibration isolator. ResultsAccording to the experimental results, the proposed method shows higher prediction accuracy than similar methods by more than 85%, and its vibration isolator performance prediction is significantly improved by more than 60% compared with the static prediction method. ConclusionThe proposed method integrates the HF analysis model and multiple non-hierarchical LF analysis models. While the hierarchical relationship between LF analysis models is relaxed, the information of LF data is mined to the maximum extent. |
| format | Article |
| id | doaj-art-bb8f3f9a8dd743438bafcb9eeb348dc7 |
| institution | Kabale University |
| issn | 1673-3185 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Editorial Office of Chinese Journal of Ship Research |
| record_format | Article |
| series | Zhongguo Jianchuan Yanjiu |
| spelling | doaj-art-bb8f3f9a8dd743438bafcb9eeb348dc72025-01-02T00:51:28ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852024-12-01196829610.19693/j.issn.1673-3185.03980ZG3980Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problemMeng CHENG0Qi ZHOU1Xiao WEI2Jian WANG3Wei CHEN4China Ship Development and Design Center, Wuhan 430064, ChinaSchool of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaChina Ship Development and Design Center, Wuhan 430064, ChinaChina Ship Development and Design Center, Wuhan 430064, ChinaChina Ship Development and Design Center, Wuhan 430064, ChinaObjectiveMulti-fidelity surrogate (MFS) modeling technology can reduce simulation costs in the design process of engineering products. In order to relax the hierarchical relationship between low-fidelity (LF) analysis models and broaden the engineering application of MFS, this paper proposes an MFS modelling method based on variance-weighted sum (VWS-MFS) for the fusion of multiple non-hierarchical LF data. MethodThe proposed method builds LF surrogate models using Kriging technology. By quantifying the uncertainty of the LF surrogate models with variance, the non-hierarchical LF data is weighted to construct a trend function. In addition, the improved hierarchical Kriging (IHK) model is introduced to fuse the high-fidelity (HF) and LF data, enabling the correction coefficient of the trend function to change throughout the design space. The proposed method is then tested on nine typical examples and applied to the performance prediction of a vibration isolator. ResultsAccording to the experimental results, the proposed method shows higher prediction accuracy than similar methods by more than 85%, and its vibration isolator performance prediction is significantly improved by more than 60% compared with the static prediction method. ConclusionThe proposed method integrates the HF analysis model and multiple non-hierarchical LF analysis models. While the hierarchical relationship between LF analysis models is relaxed, the information of LF data is mined to the maximum extent.http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03980naval architecturestructural analysismulti-fidelity surrogate modelingkriging modelmetamaterial vibration isolatorperformance prediction |
| spellingShingle | Meng CHENG Qi ZHOU Xiao WEI Jian WANG Wei CHEN Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem Zhongguo Jianchuan Yanjiu naval architecture structural analysis multi-fidelity surrogate modeling kriging model metamaterial vibration isolator performance prediction |
| title | Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem |
| title_full | Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem |
| title_fullStr | Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem |
| title_full_unstemmed | Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem |
| title_short | Research on multi-fidelity surrogate modeling method for non-hierarchical low-fidelity analysis model problem |
| title_sort | research on multi fidelity surrogate modeling method for non hierarchical low fidelity analysis model problem |
| topic | naval architecture structural analysis multi-fidelity surrogate modeling kriging model metamaterial vibration isolator performance prediction |
| url | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03980 |
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