Computation-Effective Structural Performance Assessment Using Gaussian Process-Based Finite Element Model Updating and Reliability Analysis
| Autor: | Tommy H.T. Chan, Andre Jesus, Hans Moravej, Khac Duy Nguyen |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
Applied Mathematics Mechanical Engineering Computation Probabilistic logic Aerospace Engineering Box girder 020101 civil engineering Ocean Engineering 02 engineering and technology Building and Construction Finite element method 0201 civil engineering Reliability engineering Discrepancy function symbols.namesake 020303 mechanical engineering & transports 0203 mechanical engineering symbols Structural health monitoring Uncertainty quantification Gaussian process Civil and Structural Engineering |
| Zdroj: | International Journal of Structural Stability and Dynamics. 20:2042003 |
| ISSN: | 1793-6764 0219-4554 |
| DOI: | 10.1142/s0219455420420031 |
| Popis: | Structural health monitoring data has been widely acknowledged as a significant source for evaluating the performance and health conditions of structures. However, a holistic framework that efficiently incorporates monitored data into structural identification and, in turn, provides a realistic life-cycle performance assessment of structures is yet to be established. There are different sources of uncertainty, such as structural parameters, computer model bias and measurement errors. Neglecting to account for these factors results in unreliable structural identifications, consequent financial losses, and a threat to the safety of structures and human lives. This paper proposes a new framework for structural performance assessment that integrates a comprehensive probabilistic finite element model updating approach, which deals with various structural identification uncertainties and structural reliability analysis. In this framework, Gaussian process surrogate models are replaced with a finite element model and its associate discrepancy function to provide a computationally efficient and all-round uncertainty quantification. Herein, the structural parameters that are most sensitive to measured structural dynamic characteristics are investigated and used to update the numerical model. Sequentially, the updated model is applied to compute the structural capacity with respect to loading demand to evaluate its as-is performance. The proposed framework’s feasibility is investigated and validated on a large lab-scale box girder bridge in two different health states, undamaged and damaged, with the latter state representing changes in structural parameters resulted from overloading actions. The results from the box girder bridge indicate a reduced structural performance evidenced by a significant drop in the structural reliability index and an increased probability of failure in the damaged state. The results also demonstrate that the proposed methodology contributes to more reliable judgment about structural safety, which in turn enables more informed maintenance decisions to be made. |
| Databáze: | OpenAIRE |
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