Reducing the Constrained Multibody Dynamics Problem to the Solution of a System of ODEs via Velocity Partitioning and Lie Group Integration

IF 1.9 4区 工程技术 Q3 ENGINEERING, MECHANICAL
Alexandra Kissel, Luning Bakke, D. Negrut
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引用次数: 0

Abstract

In multibody dynamics, formulating the equations of motion in absolute Cartesian coordinates results in a set of index-3 differential algebraic equations (DAEs). In this work, we present an approach that bypasses the DAE problem by partitioning the velocities in the system into dependent and independent coordinates, thereby reducing the task of producing the time evolution of the mechanical system to one of solving a set of ordinary differential equations (ODEs). In this approach, the independent coordinates are integrated directly, while the dependent coordinates are recovered through the kinematic constraint equations at the position and velocity levels. Notably, Lie group integration is employed to directly obtain the orientation matrix A at each time step of the simulation. This eliminates the need to choose generalized coordinates to capture the orientation of a body, as the matrix A is a byproduct of the solution algorithm. The approach is akin to the method presented in [1], which combines coordinate partitioning with an Euler parameter formulation. Herein, we outline the new approach and demonstrate it in conjunction with four mechanisms: a single pendulum, a double pendulum, a four-link mechanism, and a slider crank. We report on the convergence order behavior of the proposed method and a performance comparison with the solution introduced in [1]. The Python code developed to generate the reported results is open-source and available in a public repository for reproducibility studies [2].
通过速度分区和列组积分将受约束多体动力学问题简化为一个 ODE 系统的求解过程
在多体动力学中,以绝对笛卡尔坐标表示运动方程会产生一组索引 3 微分代数方程 (DAE)。在这项工作中,我们提出了一种绕过 DAE 问题的方法,即将系统中的速度划分为从属坐标和独立坐标,从而将产生机械系统时间演化的任务简化为求解一组常微分方程 (ODE)。在这种方法中,独立坐标直接积分,而从属坐标则通过位置和速度层面的运动学约束方程恢复。值得注意的是,在模拟的每个时间步长上,采用李群积分法可直接获得方向矩阵 A。由于矩阵 A 是求解算法的副产品,因此无需选择广义坐标来捕捉体的方向。这种方法类似于文献[1]中介绍的方法,后者将坐标划分与欧拉参数公式相结合。在此,我们概述了新方法,并结合四种机构进行了演示:单摆、双摆、四连杆机构和滑块曲柄。我们报告了所提方法的收敛阶次行为,并与 [1] 中介绍的解决方案进行了性能比较。为生成报告结果而开发的 Python 代码是开源的,可在公共存储库中获取,用于可重复性研究[2]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.00
自引率
10.00%
发文量
72
审稿时长
6-12 weeks
期刊介绍: The purpose of the Journal of Computational and Nonlinear Dynamics is to provide a medium for rapid dissemination of original research results in theoretical as well as applied computational and nonlinear dynamics. The journal serves as a forum for the exchange of new ideas and applications in computational, rigid and flexible multi-body system dynamics and all aspects (analytical, numerical, and experimental) of dynamics associated with nonlinear systems. The broad scope of the journal encompasses all computational and nonlinear problems occurring in aeronautical, biological, electrical, mechanical, physical, and structural systems.
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