A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling
An efficient parametric reduced-order modeling method combined with substructural matrix interpolation and automatic sampling procedure is proposed. This approach is based on the fixed-interface Craig-Bampton component mode synthesis method (CMS). The novel parametric reduced-order models (PROMs) ar...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/6407437 |
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| _version_ | 1832550298844921856 |
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| author | Ying Liu Hongguang Li Yun Li Huanyu Du |
| author_facet | Ying Liu Hongguang Li Yun Li Huanyu Du |
| author_sort | Ying Liu |
| collection | DOAJ |
| description | An efficient parametric reduced-order modeling method combined with substructural matrix interpolation and automatic sampling procedure is proposed. This approach is based on the fixed-interface Craig-Bampton component mode synthesis method (CMS). The novel parametric reduced-order models (PROMs) are developed by interpolating substructural reduced-order matrices. To guarantee the compatibility of the coordinates, we develop a three-step adjustment procedure by reducing the local interface degrees of freedom (DOFs) and performing congruence transformation for the normal modes and interface reduced basis, respectively. In addition, an automatic sampling process is also introduced to dynamically fulfill the predefined error limits. It proceeds by first exploring the parameter space and identifying the sampling points with maximum error indicators for all the parameter-dependent substructures. The exact error of the assembled model at the optimal parameter point is subsequently calculated to determine whether the automatic sampling procedure reaches a desired error tolerance. The proposed framework is then applied to the moving coil of electrical-dynamic shaker to illustrate the advantage and validity. The results indicate that this new approach can significantly reduce both the offline database construction time and online calculation time. Besides, the automatic procedure can sample the parameter space efficiently and fulfill the stopping criterion dynamically with assurance of the resulting PROM accuracy. |
| format | Article |
| id | doaj-art-a972325ec1204e1e859c431bcd650a7b |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-a972325ec1204e1e859c431bcd650a7b2025-02-03T06:07:13ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/64074376407437A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic SamplingYing Liu0Hongguang Li1Yun Li2Huanyu Du3Institute of Vibration, Shock and Noise, State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, ChinaInstitute of Vibration, Shock and Noise, State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, ChinaInstitute of Vibration, Shock and Noise, State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, ChinaInstitute of Vibration, Shock and Noise, State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, ChinaAn efficient parametric reduced-order modeling method combined with substructural matrix interpolation and automatic sampling procedure is proposed. This approach is based on the fixed-interface Craig-Bampton component mode synthesis method (CMS). The novel parametric reduced-order models (PROMs) are developed by interpolating substructural reduced-order matrices. To guarantee the compatibility of the coordinates, we develop a three-step adjustment procedure by reducing the local interface degrees of freedom (DOFs) and performing congruence transformation for the normal modes and interface reduced basis, respectively. In addition, an automatic sampling process is also introduced to dynamically fulfill the predefined error limits. It proceeds by first exploring the parameter space and identifying the sampling points with maximum error indicators for all the parameter-dependent substructures. The exact error of the assembled model at the optimal parameter point is subsequently calculated to determine whether the automatic sampling procedure reaches a desired error tolerance. The proposed framework is then applied to the moving coil of electrical-dynamic shaker to illustrate the advantage and validity. The results indicate that this new approach can significantly reduce both the offline database construction time and online calculation time. Besides, the automatic procedure can sample the parameter space efficiently and fulfill the stopping criterion dynamically with assurance of the resulting PROM accuracy.http://dx.doi.org/10.1155/2019/6407437 |
| spellingShingle | Ying Liu Hongguang Li Yun Li Huanyu Du A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling Shock and Vibration |
| title | A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling |
| title_full | A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling |
| title_fullStr | A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling |
| title_full_unstemmed | A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling |
| title_short | A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling |
| title_sort | component based parametric reduced order modeling method combined with substructural matrix interpolation and automatic sampling |
| url | http://dx.doi.org/10.1155/2019/6407437 |
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