Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism
High damping rubber (HDR) bearings are extensively used in seismic design for bridges due to their remarkable energy dissipation capabilities, which is critical during earthquakes. A thorough assessment of crucial factors such as temperature, rate, experienced maximum amplitude, and the Mullins effe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Polymers |
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| Online Access: | https://www.mdpi.com/2073-4360/16/5/567 |
| _version_ | 1797264008923840512 |
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| author | Feng Li Tianbo Peng |
| author_facet | Feng Li Tianbo Peng |
| author_sort | Feng Li |
| collection | DOAJ |
| description | High damping rubber (HDR) bearings are extensively used in seismic design for bridges due to their remarkable energy dissipation capabilities, which is critical during earthquakes. A thorough assessment of crucial factors such as temperature, rate, experienced maximum amplitude, and the Mullins effect of HDR on the mechanics-based constitutive model of HDR is lacking. To address this issue, we propose a deep learning approach that integrates the Gate Recurrent Unit (GRU) and attention mechanism to identify time series characteristics from compression-shear test data of HDR specimens. It is shown that the combination of GRU and attention mechanism enables accurate prediction of the mechanical behavior of HDR specimens. Compared to the sole use of GRU, this suggested method significantly reduces model complexity and computation time while maintaining good prediction performance. Therefore, it offers a new approach to constructing the HDR constitutive model. Finally, the HDR constitutive model was used to analyze the impact of experienced maximum amplitudes and cycles on following processes. It was observed that maximum amplitudes directly influence the stress-strain relationship of HDR during subsequent processes. Consequently, a solid foundation is laid for evaluating the responses of HDR bearings under earthquakes. |
| first_indexed | 2024-04-25T00:22:05Z |
| format | Article |
| id | doaj.art-59023ef9e875470e947fa0d54e9a197d |
| institution | Directory Open Access Journal |
| issn | 2073-4360 |
| language | English |
| last_indexed | 2024-04-25T00:22:05Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Polymers |
| spelling | doaj.art-59023ef9e875470e947fa0d54e9a197d2024-03-12T16:53:15ZengMDPI AGPolymers2073-43602024-02-0116556710.3390/polym16050567Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention MechanismFeng Li0Tianbo Peng1College of Civil Engineering, Tongji University, Shanghai 200092, ChinaCollege of Civil Engineering, Tongji University, Shanghai 200092, ChinaHigh damping rubber (HDR) bearings are extensively used in seismic design for bridges due to their remarkable energy dissipation capabilities, which is critical during earthquakes. A thorough assessment of crucial factors such as temperature, rate, experienced maximum amplitude, and the Mullins effect of HDR on the mechanics-based constitutive model of HDR is lacking. To address this issue, we propose a deep learning approach that integrates the Gate Recurrent Unit (GRU) and attention mechanism to identify time series characteristics from compression-shear test data of HDR specimens. It is shown that the combination of GRU and attention mechanism enables accurate prediction of the mechanical behavior of HDR specimens. Compared to the sole use of GRU, this suggested method significantly reduces model complexity and computation time while maintaining good prediction performance. Therefore, it offers a new approach to constructing the HDR constitutive model. Finally, the HDR constitutive model was used to analyze the impact of experienced maximum amplitudes and cycles on following processes. It was observed that maximum amplitudes directly influence the stress-strain relationship of HDR during subsequent processes. Consequently, a solid foundation is laid for evaluating the responses of HDR bearings under earthquakes.https://www.mdpi.com/2073-4360/16/5/567high damping rubberconstitutive modeltime series characteristicGRUattention mechanism |
| spellingShingle | Feng Li Tianbo Peng Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism Polymers high damping rubber constitutive model time series characteristic GRU attention mechanism |
| title | Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism |
| title_full | Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism |
| title_fullStr | Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism |
| title_full_unstemmed | Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism |
| title_short | Developing a New Constitutive Model of High Damping Rubber by Combining GRU and Attention Mechanism |
| title_sort | developing a new constitutive model of high damping rubber by combining gru and attention mechanism |
| topic | high damping rubber constitutive model time series characteristic GRU attention mechanism |
| url | https://www.mdpi.com/2073-4360/16/5/567 |
| work_keys_str_mv | AT fengli developinganewconstitutivemodelofhighdampingrubberbycombininggruandattentionmechanism AT tianbopeng developinganewconstitutivemodelofhighdampingrubberbycombininggruandattentionmechanism |