Redirigiendo al acceso original de articulo en 22 segundos...
Inicio  /  Buildings  /  Vol: 13 Par: 6 (2023)  /  Artículo
ARTÍCULO
TITULO

Application of Bayesian Update Method in the Construction Control of Continuous Rigid Frame Bridge Girders with High Piers and Large Spans

Xiaolong Zhou    
Taoxin Deng    
Li Chen    
Jie Chen    
Ao Li    
Qijie Yuan    
Wei Fang and Jianfeng Gu    

Resumen

In the construction process of large-scale bridges, there are uncertainties and time-varying factors in the environment and construction loads. It is difficult to make accurate estimates of the theoretical calculation models of construction control in advance. In view of this situation, Bayesian dynamic updating method is introduced to re-estimate the predicted results of the theoretical model. When applying this method, first, the finite element calculation model is determined based on the response surface method, and its calculation results are used as prior information. Then, combined with the actual detection data during the construction process, the Bayesian update formula is derived based on the conjugate prior distribution to correct the theoretical prediction results of bridge construction monitoring. Finally, the actual stress detection data of the control section of high-pier and large-span continuous rigid frame bridges during the construction process illustrate the application process of Bayesian updating in improving the theoretical prediction model. Results indicate that the internal force of the bridge control section obtained by re-evaluating by Bayesian theory not only incorporates the priori information models but also actual monitors sample information during the construction process. The predicted results reflect the true deformation and stress state of the bridge during the bridge construction process and improve the precision of construction monitoring.

 Artículos similares

       
 
Behrouz Pirouz, Aldo Pedro Ferrante, Behzad Pirouz and Patrizia Piro    
Many complex problems require a multi-criteria decision, such as the COVID-19 pandemic that affected nearly all activities in the world. In this regard, this study aims to develop a multi-criteria decision support system considering the sustainability, f... ver más

 
Clara Pereira, Ana Silva, Cláudia Ferreira, Jorge de Brito, Inês Flores-Colen and José D. Silvestre    
In the field of building inspection and diagnosis, uncertainty is common and surveyors are aware of it, although it is not easily measured. This research proposes a model to quantify uncertainty based on the inspection of rendered façades. A Bayesian net... ver más
Revista: Infrastructures

 
Filippo Landi, Francesca Marsili, Noemi Friedman and Pietro Croce    
In civil and mechanical engineering, Bayesian inverse methods may serve to calibrate the uncertain input parameters of a structural model given the measurements of the outputs. Through such a Bayesian framework, a probabilistic description of parameters ... ver más
Revista: Infrastructures

 
Cássio G. Rampinelli, Ian Knack and Tyler Smith    
Many hydrologic studies that are the basis for water resources planning and management rely on streamflow information. Calibration and use of hydrologic models to extend flow series based on rainfall data, perform flood frequency analysis, or develop flo... ver más
Revista: Water

 
Jiping Jiang, Yasong Chen and Baoyu Wang    
It is important to identify source information after a river chemical spill incident occurs. Among various source inversion approaches, a Bayesian-based framework is able to directly characterize inverse uncertainty using a probability distribution and h... ver más
Revista: Hydrology