关键词: 动态不确定性, 区间过程模型, 区间K-L展开, 刚柔耦合动力学, 序列模拟方法

Abstract: For the dynamic problem of rigid-flexible coupling systems under dynamic uncertain excitations, an interval process model-based sequential simulation method was proposed for uncertainty analysis, which aimed to obtain the upper and lower bounds of the system dynamic responses such as structural vibrations and mechanism kinematics, by sequential sampling of the interval process and the rigid-flexible coupling dynamics simulations. The construction and numerical solution of the dynamic equation of the rigid-flexible coupling systems with central rigid body and flexible beam were introduced. Aiming at the dynamic analysis of rigid-flexible coupling systems under uncertain dynamic excitations, the interval process model and the interval K-L expansion were introduced to quantify and represent the dynamic uncertainty efficiently, and a sequential simulation method was proposed to solve the upper and lower bounds of the dynamic responses of the system mechanism motions and structural vibrations. The method used a sequential simulation strategy to identify the interval process parameter sample sets that contributed to the upper or lower bounds of dynamic responses in the cur rent simulation sequence, and served as the local encrypted sampling center in the next simulation sequence, which might effectively avoid the inefficient convergence problem caused by excessive invalid sampling simulations when calculating the upper and lower bounds of dynamic response in direct Monte Carlo simulation. Finally, three examples were given to verify the effectiveness of the proposed method. The results show that the sequential simulation method has better computational efficiency and accuracy than that of the direct Monte Carlo simulation method for solving the upper and lower bounds of the rigid-flexible coupling systems large overall motions and vibration responses.

Key words:  , dynamic uncertainty, interval process model, interval K-L expansion, rigid-flexible coupling dynamics, sequential simulation method