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Sparse matrix implicit numerical integration of the Stiff differential/algebraic equations: Implementation

机译:Stiff微分/代数方程的稀疏矩阵隐式数值积分:实现

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摘要

The finite element absolute nodal coordinate formulation (ANCF) is often used in modeling very flexible bodies in multibody system (MBS) applications. This formulation leads to a constant mass matrix, allowing for an efficient sparse matrix implementation. Nonetheless, the use of the ANCF finite elements to model stiff structures can lead to high frequencies associated with ANCF coupled deformation modes, as discussed in the literature. Implicit numerical integration methods can be effectively used to develop efficient procedures for the solution of MBS differential/algebraic equations. Most existing implicit integration algorithms, however, require numerical differentiation of the equations of motion, and some of these integration methods do not ensure that the kinematic algebraic constraint equations are satisfied at all levels (position, velocity, and acceleration). Because of these limitations, existing implicit integration methods can be less accurate and less efficient when used to solve large scale MBS applications. In order to circumvent this problem, the two-loop implicit sparse matrix numerical integration (TLISMNI) method was proposed for the solution of MBS differential/algebraic equations. The TLISMNI method does not require numerical differentiation of the forces and allows for an efficient sparse matrix implementation. This paper discusses TLISMNI implementation issues including the step size selection, the error control, and the effect of the numerical damping. The relation between the step size selection and the structure stiffness is also discussed. The use of the computer implementation described in this paper is demonstrated by solving very stiff structure problems using the Hilber–Hughes–Taylor (HHT) method, which includes numerical damping. An eigenvalue analysis and Fast Fourier Transform (FFT) are performed in order to identify the fundamental modes of deformation and demonstrate that the contributions of these fundamental modes can be erroneously damped out when some other implicit integration methods are used. The TLISMNI method, on the other hand, captures the contributions of these fundamental modes. The results, obtained using the TLISMNI method, are compared with the results obtained using other methods including the implicit HHT-I3 and the explicit Adams integration methods. The results obtained show that the TLISMNI method can be five times faster than the other two methods when no numerical damping is considered.
机译:有限元绝对节点坐标公式(ANCF)通常用于对多体系统(MBS)应用中的非常灵活的物体进行建模。该公式导致质量矩阵恒定,从而实现有效的稀疏矩阵实现。尽管如此,如文献所讨论的,使用ANCF有限元来对刚性结构建模可以导致与ANCF耦合变形模式相关的高频。隐式数值积分方法可以有效地用于开发MBS微分/代数方程解的有效程序。但是,大多数现有的隐式积分算法都需要对运动方程进行数值微分,并且其中一些积分方法不能确保在所有级别(位置,速度和加速度)都满足运动代数约束方程。由于这些限制,当用于解决大规模MBS应用程序时,现有的隐式集成方法可能会降低准确性和效率。为了解决这个问题,提出了两环隐式稀疏矩阵数值积分(TLISMNI)方法求解MBS微分/代数方程。 TLISMNI方法不需要对力进行数值微分,并且可以实现有效的稀疏矩阵实现。本文讨论了TLISMNI的实现问题,包括步长选择,误差控制以及数值阻尼的影响。还讨论了步长选择与结构刚度之间的关系。通过使用Hilber-Hughes-Taylor(HHT)方法(包括数值阻尼)解决非常刚性的结构问题,证明了本文所述计算机实现的使用。为了识别变形的基本模式,并进行了特征值分析和快速傅立叶变换(FFT),并证明了当使用某些其他隐式积分方法时,这些基本模式的贡献可能会被错误地抵消。另一方面,TLISMNI方法捕获了这些基本模式的贡献。将使用TLISMNI方法获得的结果与使用其他方法(包括隐式HHT-I3和显式Adams积分方法)获得的结果进行比较。所得结果表明,在不考虑数值阻尼的情况下,TLISMNI方法可以比其他两种方法快五倍。

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