Probabilistic Damage Identification of the Dowling Hall Footbridge Using Bayesian FE Model Updating

Author(s):  
Iman Behmanesh ◽  
Babak Moaveni
2011 ◽  
Vol 291-294 ◽  
pp. 1572-1577
Author(s):  
Rui Zhao ◽  
Yi Gang Zhang

The discrete finite element (FE) model often cannot reflect structure characteristics accurately due to imply more idealistic assumptions and simplifications. Therefore, it is necessary to update FE model for structural damage identification, response calculation, safety evaluation, optimization design, and so on. This article will illustrate respectively three key steps of updating parameters selection, target function selection and optimization method in process of dynamic FE model updating of footbridge structures based on ambient excitation, and put forward a feasible updating method: combine empirical method with sensitivity analysis method to select updating parameters; joint natural frequencies, MAC and modal flexibility as target function; adopt optimization algorithm based on the optimization theory.


2021 ◽  
Vol 11 (4) ◽  
pp. 1622
Author(s):  
Gun Park ◽  
Ki-Nam Hong ◽  
Hyungchul Yoon

Structural members can be damaged from earthquakes or deterioration. The finite element (FE) model of a structure should be updated to reflect the damage conditions. If the stiffness reduction is ignored, the analysis results will be unreliable. Conventional FE model updating techniques measure the structure response with accelerometers to update the FE model. However, accelerometers can measure the response only where the sensor is installed. This paper introduces a new computer-vision based method for structural FE model updating using genetic algorithm. The system measures the displacement of the structure using seven different object tracking algorithms, and optimizes the structural parameters using genetic algorithm. To validate the performance, a lab-scale test with a three-story building was conducted. The displacement of each story of the building was measured before and after reducing the stiffness of one column. Genetic algorithm automatically optimized the non-damaged state of the FE model to the damaged state. The proposed method successfully updated the FE model to the damaged state. The proposed method is expected to reduce the time and cost of FE model updating.


Author(s):  
Ali Vasallo Belver ◽  
Stana Zivanovic ◽  
HiepVu Dang ◽  
Melania Istrate ◽  
Antolin Lorenzana Iban

2001 ◽  
Author(s):  
Jeroen Deweer ◽  
Tom Van Langenhove ◽  
Scott Grinker

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