Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction me...Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.展开更多
为研究基础结构的材料属性和尺寸对单桩式海上风机基础可靠性的影响,提出基于PC-Kriging模型(Polynomial-Chaos-based Kriging,PC-Kriging)和蒙特卡洛模拟(Monte Carlo Simulation,MCS)方法,结合IEGO学习函数建立的单桩式海上风机基础...为研究基础结构的材料属性和尺寸对单桩式海上风机基础可靠性的影响,提出基于PC-Kriging模型(Polynomial-Chaos-based Kriging,PC-Kriging)和蒙特卡洛模拟(Monte Carlo Simulation,MCS)方法,结合IEGO学习函数建立的单桩式海上风机基础可靠性分析模型,并通过算例验证了该方法的精确性。以50年重现期的海况为极端环境,考虑材料密度、弹性模量和桩腿壁厚的不确定性,进行单桩式海上风机基础在塔筒顶部位移和应力控制两个失效因素下的可靠性分析,并进行全局灵敏度分析。分析结果表明,单桩式海上风机基础失效概率为8.4×10-3,材料密度对可靠性影响可以忽略不计,而材料弹性模量和桩腿壁厚对可靠性影响较大。展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.12272211,12072181,12121002)。
文摘Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.
文摘为研究基础结构的材料属性和尺寸对单桩式海上风机基础可靠性的影响,提出基于PC-Kriging模型(Polynomial-Chaos-based Kriging,PC-Kriging)和蒙特卡洛模拟(Monte Carlo Simulation,MCS)方法,结合IEGO学习函数建立的单桩式海上风机基础可靠性分析模型,并通过算例验证了该方法的精确性。以50年重现期的海况为极端环境,考虑材料密度、弹性模量和桩腿壁厚的不确定性,进行单桩式海上风机基础在塔筒顶部位移和应力控制两个失效因素下的可靠性分析,并进行全局灵敏度分析。分析结果表明,单桩式海上风机基础失效概率为8.4×10-3,材料密度对可靠性影响可以忽略不计,而材料弹性模量和桩腿壁厚对可靠性影响较大。
