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刘圣宾,丁自豪,张永兵,余波.钢筋混凝土柱抗弯承载力的概率模型与校准分析
Probabilistic model and calibration of flexure strength of reinforced concrete columns[J].计算力学学报,2020,37(3):316~325
钢筋混凝土柱抗弯承载力的概率模型与校准分析
Probabilistic model and calibration of flexure strength of reinforced concrete columns
Probabilistic model and calibration of flexure strength of reinforced concrete columns
投稿时间:2019-06-11  修订日期:2019-08-07
DOI:10.7511/jslx20190611001
中文关键词:  钢筋混凝土柱  抗弯承载力  不确定性  概率模型  概率校准
英文关键词:reinforced concrete columns  flexure strength  uncertainties  probabilistic model  probabilistic calibration
基金项目:国家自然科学基金(51668008;51738004);广西自然科学基金(2018GXNSFAA281344)资助项目.
作者单位E-mail
刘圣宾 广西大学 土木建筑工程学院, 南宁 530004
南京市市政设计研究院有限责任公司, 南京 210008 
 
丁自豪 广西大学 土木建筑工程学院, 南宁 530004  
张永兵 广西大学 土木建筑工程学院, 南宁 530004  
余波 广西大学 土木建筑工程学院, 南宁 530004
工程防灾与结构安全教育部重点实验室, 南宁 530004
广西防灾减灾与工程安全重点实验室, 南宁 530004 
gxuyubo@gxu.edu.cn 
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中文摘要:
      为了克服传统确定性抗弯承载力模型和校准方法无法合理考虑不确定性所存在的缺陷,分别建立了钢筋混凝土(RC)柱的概率抗弯承载力模型与概率校准方法。首先,基于RC柱正截面受弯承载力的基本假定,结合偏心受压RC柱的截面内力平衡条件,分别建立了大(小)偏心受压RC柱的确定性抗弯承载力模型;然后,综合考虑固有不确定性和认知不确定性的影响,分别建立了大(小)偏心受压RC柱概率抗弯承载力模型的解析表达式,进而结合贝叶斯理论和MCMC法确定了概率模型参数的后验分布信息,从而建立了RC柱的概率抗弯承载力模型;最后,基于概率抗弯承载力模型所确定的概率密度函数、置信区间和置信水平,提出了传统确定性抗弯承载力模型的概率校准方法。研究结果表明,所建立的概率抗弯承载力模型不仅可以合理描述RC柱抗弯承载力的概率分布特性,而且可以校准传统确定性抗弯承载力模型的计算精度和置信水平。
英文摘要:
      A probabilistic model and a calibration method for flexure strength of reinforced concrete (RC) columns were proposed to overcome the disadvantage that traditional deterministic flexure strength models and calibration methods cannot rationally consider the influence of uncertainties.Based on the basic assumption of flexure strength analysis of RC members,deterministic flexure strength models for large (small) eccentric compression RC columns were established firstly according to the force balance condition of eccentric compression RC columns.Then analytical expressions for probabilistic flexure strength models of RC columns were developed by considering the influences of both aleatory and epistemic uncertainties.Subsequently,probabilistic models were established by determining the posterior distribution information of probabilistic model parameters based on the Bayesian theory and the Markov Chain Monte Carlo(MCMC)method.Finally,probabilistic calibration methods of traditional deterministic flexure strength models were proposed based on the probability density function,confidence interval and confidence level determined by the proposed probabilistic models.Analysis results show that the probabilistic flexure strength models not only can reasonably describe the probabilistic characteristics of flexure strength,but also provide an efficient way to calibrate the accuracy and confidence level of traditional deterministic flexure strength models of RC columns.
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