Reliability Analysis of the Updated Probabilistic Model of RC Beams Shear Capacity combined with Bayesian-MCMC
To analyze shear capacity of reinforced concrete(RC)beams,this study utilizes Bayesian Markov Chain Monte Carlo(MCMC)method to update and revise the Chinese GB 50010-2010 code model.The paper involves considering factors such as material strength of concrete and stirrups,section dimensions,shear-span ratio,and reinforcement ratio,based on prior informa-tion from 100 sets of RC beam shear capacity test data from references.Subsequently,a reliability analysis of the probabilistic shear capacity model for RC beams is conducted using Monte Carlo simulation.The results validate the model's favorable computational accuracy and reliability.The findings indicate that the mean and standard deviation of the ratio K,representing the ratio between the mean value of the probabilistic model and the experimental value,are 1.013 and 0.171,respectively.The experimental values fall within the 95％confidence interval of the probabilistic model,with reliability indices distributed around 4.0.This suggests that the probabilistic model established in this study exhibits good predictive nature and reliability.
reinforced concrete beamsshear capacityBayesian Theorythe Markov Chain Monte Carlo methodprobabilistic model
万方数据
维普
