Constraint Realization-Based Hamel Field Integrator for Geometrically Exact Planar Euler–Bernoulli Beam Dynamics

IF 2.9 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY International Journal for Numerical Methods in Engineering Pub Date : 2024-10-26 DOI:10.1002/nme.7603
Benliang Wang, Donghua Shi, Zhonggui Yi
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Abstract

In this article, we first introduce a Hamel field integrator designed for a geometrically exact Euler–Bernoulli beam with infinite-dimensional holonomic constraints, constructed using a Lagrange multiplier. This method addresses the complexities introduced by constraints, but the additional multiplier introduces a new degree of freedom and hence results in a system with mixed-type partial differential equations. To address this issue, we further propose a constraint realization method based on perturbation theory for infinite-dimensional mechanical systems within the framework of Hamel's formalism. This method circumvents the use of additional Lagrange multiplier, significantly reducing the computational complexity of modeling problems. Building on this, we construct a perturbed Hamel field integrator optimized for parallel computing and incorporate artificial viscosity to accelerate constraint convergence. While applicable to three dimensions, our method is demonstrated in a simplified context using planar Euler–Bernoulli beam examples to illustrate the effectiveness of the unified mathematical framework.

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基于约束实现的哈梅尔场积分器,用于几何精确的平面欧拉-伯努利梁动力学
在本文中,我们首先介绍了一个Hamel场积分器,该积分器设计用于具有无限维完整约束的几何精确欧拉-伯努利梁,使用拉格朗日乘法器构造。这种方法解决了约束带来的复杂性,但附加的乘数引入了新的自由度,因此得到了一个混合型偏微分方程的系统。为了解决这一问题,我们进一步提出了一种基于微扰理论的无限维机械系统的约束实现方法。该方法避免了使用额外的拉格朗日乘子,大大降低了建模问题的计算复杂度。在此基础上,我们构造了一个适合并行计算的微扰Hamel场积分器,并加入了人工黏度来加速约束收敛。虽然适用于三维,但我们的方法在一个简化的背景下使用平面欧拉-伯努利梁的例子来说明统一数学框架的有效性。
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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