|
Title |
The Risk Assessment and Prediction for the Mixed Deterioration in Cable Bridges Using a Stochastic Bayesian Modeling
|
|
Keywords |
MCMC ; 계층적 베이지언 추론 ; 현수교 ; 예측위험 ; MCMC ; Hierarchical Bayesian inference ; Suspension bridge ; Prediction risk |
|
Abstract |
The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.
|