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Comprehensive Bayesian structural identification using temperature variation
A modular Bayesian method is applied for structural identification of a reduced-scale aluminium bridge model subject to thermal loading. The deformation and temperature variations of the structure were measured using strain gauges and thermocouples. Feasibility of a practical, temperature-based, Bay...
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| Main Authors: | , , , |
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| Format: | Default Article |
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2017
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| Online Access: | https://hdl.handle.net/2134/19901782.v1 |
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| _version_ | 1818165963294507008 |
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| author | Andre Jesus Peter Brommer Yanjie Zhu Irwanda Laory |
| author_facet | Andre Jesus Peter Brommer Yanjie Zhu Irwanda Laory |
| author_sort | Andre Jesus (12381421) |
| collection | Figshare |
| description | A modular Bayesian method is applied for structural identification of a reduced-scale aluminium bridge model subject to thermal loading. The deformation and temperature variations of the structure were measured using strain gauges and thermocouples. Feasibility of a practical, temperature-based, Bayesian structural identification is highlighted. This methodology used multiple responses to identify existent discrepancies of a model, calibrate the stiffness of the bridge support and establish uncertainty of a predicted response. Results show that the inference of a structural parameter is successful even in the presence of substantial modelling discrepancies, converging to its true physical value. However measurements should have a high dependency on the calibration parameters. Usage of temperature variations to perform structural identification is highlighted. |
| format | Default Article |
| id | rr-article-19901782 |
| institution | Loughborough University |
| publishDate | 2017 |
| record_format | Figshare |
| spelling | rr-article-199017822017-03-19T00:00:00Z Comprehensive Bayesian structural identification using temperature variation Andre Jesus (12381421) Peter Brommer (1619815) Yanjie Zhu (838148) Irwanda Laory (12654727) Bayesian inference Model calibration Structural-identification Identifiability Temperature variation <p>A modular Bayesian method is applied for structural identification of a reduced-scale aluminium bridge model subject to thermal loading. The deformation and temperature variations of the structure were measured using strain gauges and thermocouples. Feasibility of a practical, temperature-based, Bayesian structural identification is highlighted. This methodology used multiple responses to identify existent discrepancies of a model, calibrate the stiffness of the bridge support and establish uncertainty of a predicted response. Results show that the inference of a structural parameter is successful even in the presence of substantial modelling discrepancies, converging to its true physical value. However measurements should have a high dependency on the calibration parameters. Usage of temperature variations to perform structural identification is highlighted.</p> 2017-03-19T00:00:00Z Text Journal contribution 2134/19901782.v1 https://figshare.com/articles/journal_contribution/Comprehensive_Bayesian_structural_identification_using_temperature_variation/19901782 CC BY-NC-ND 4.0 |
| spellingShingle | Bayesian inference Model calibration Structural-identification Identifiability Temperature variation Andre Jesus Peter Brommer Yanjie Zhu Irwanda Laory Comprehensive Bayesian structural identification using temperature variation |
| title | Comprehensive Bayesian structural identification using temperature variation |
| title_full | Comprehensive Bayesian structural identification using temperature variation |
| title_fullStr | Comprehensive Bayesian structural identification using temperature variation |
| title_full_unstemmed | Comprehensive Bayesian structural identification using temperature variation |
| title_short | Comprehensive Bayesian structural identification using temperature variation |
| title_sort | comprehensive bayesian structural identification using temperature variation |
| topic | Bayesian inference Model calibration Structural-identification Identifiability Temperature variation |
| url | https://hdl.handle.net/2134/19901782.v1 |