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Volume 43 Issue 8
Dec.  2014
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Article Contents
Liu Xiaoxiao, Wu Ziyan, Sun Hongbin, Wang Qiang. RESEARCH OF THE SEISMIC FRAGILITY OF STRUCTURE BASED ON LINEAR LOGISTIC REGRESSION MODEL[J]. INDUSTRIAL CONSTRUCTION, 2013, 43(8): 43-47,105. doi: 10.13204/j.gyjz201308009
Citation: Liu Xiaoxiao, Wu Ziyan, Sun Hongbin, Wang Qiang. RESEARCH OF THE SEISMIC FRAGILITY OF STRUCTURE BASED ON LINEAR LOGISTIC REGRESSION MODEL[J]. INDUSTRIAL CONSTRUCTION, 2013, 43(8): 43-47,105. doi: 10.13204/j.gyjz201308009

RESEARCH OF THE SEISMIC FRAGILITY OF STRUCTURE BASED ON LINEAR LOGISTIC REGRESSION MODEL

doi: 10.13204/j.gyjz201308009
  • Received Date: 2013-04-15
  • Publish Date: 2013-08-20
  • A fragility evaluation methodology for bridge is proposed, based on logistic regression model.The methodology incorporates randomness of structural physical parameters and statistical dependence among response values.Using Monte Carlo simulation and random time history analysis, randomness of structural physical parameters was considered.Statistical dependence among response values was plored by Beta-binomial distribution, then logistic regression model was set up to analyse structure fragility.A two-span continuous concrete girder bridge was used as an example to illustrate the approach.Structure physical parameters with design drawings were taken as mean, and an appropriate standard deviation was selected for Monte Carlo simulation which can obtain parameter samples.Random time history analysis was done to get the sample of maximum values of responses, moment estimation and least square were used to obtain respectively Beta-binomial distribution and the unknown parameters of the logistic regression model, then the structure fragility curve under each level failure state was got and compared with fragility curve based on cumulative limit state valve.The results show that the proposed method can achieve a conservative fragility estimation, and better ensure the rationality of the prediction results, providing theoretical evidence for bridge damage detection.
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