A novel meshfree superconvergent Gradient Smoothing Stabilized Collocation Method (GSSCM) for large deformation problems: A concise discretized form

IF 7.3 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Zhiyuan Xue , Lihua Wang , Yan Li , Magd Abdel Wahab
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引用次数: 0

Abstract

The strong form Direct Collocation Method (DCM) with Reproducing Kernel (RK) shape function is hindered in its development due to its computational complexity and low efficiency in derivative calculations. Furthermore, the nonlinear large deformation governing equations in strong form, which involve intricate derivative terms, introduce additional challenges for discretization and iterative solutions. This paper proposes a novel efficient and superconvergent Gradient Smoothing Stabilized Collocation Method (GSSCM) using RK shape function. Based upon the divergence theorem, the proposed method converts traditional subdomain integration in the Stabilized Collocation Method (SCM) into subdomain boundary integration by gradient smoothing, which reduces the order of derivatives and simplifies the discretized terms of governing equations. This allows RK shape function with low-order basis functions like the linear basis functions, and enhances computational efficiency. GSSCM ensures exact integration using low-order Gaussian quadrature and improves solution stability. Both conforming and non-conforming smoothing domain are constructed for the gradient smooth. The incremental Newton-Raphson iteration approach is employed to solve the nonlinear discrete equations. Numerical results demonstrate that the proposed approach achieves superconvergent rates when odd RK basis functions are used. The GSSCM can also outperform traditional DCM, SCM and Superconvergent Gradient Smoothing Meshfree Collocation (SGSMC) method with gradient smoothing of shape function in terms of computational efficiency under the same accuracy. Moreover, GSSCM-II with conforming integration subdomains generally outmatches GSSCM-I and SCM with non-conforming subdomains in accuracy, efficiency and stability. The advantages of GSSCMs hold significant promise for nonlinear solid mechanics and engineering applications.
一种新的大变形问题的无网格超收敛梯度平滑稳定配置方法:一种简洁的离散形式
具有再现核(RK)形状函数的强形式直接配置法(DCM)由于其计算量大、导数计算效率低而阻碍了其发展。此外,强形式的非线性大变形控制方程涉及复杂的导数项,给离散化和迭代解带来了额外的挑战。提出了一种基于RK形状函数的高效、超收敛的梯度平滑稳定配置方法。该方法基于散度定理,通过梯度平滑将稳定配置法中的传统子域积分转化为子域边界积分,降低了导数阶数,简化了控制方程的离散项。这使得RK形状函数可以像线性基函数一样具有低阶基函数,提高了计算效率。GSSCM使用低阶高斯正交确保精确积分,并提高解的稳定性。构造了符合光滑域和不符合光滑域进行梯度光滑。采用增量牛顿-拉夫森迭代法求解非线性离散方程。数值结果表明,当使用奇数RK基函数时,该方法达到了超收敛速度。在相同精度下,GSSCM的计算效率也优于传统的DCM、SCM和形状函数梯度平滑的超收敛梯度平滑无网格配置(SGSMC)方法。此外,具有一致性积分子域的GSSCM-II在精度、效率和稳定性方面普遍优于具有非一致性积分子域的GSSCM-I和SCM。gsscm的优点对非线性固体力学和工程应用具有重要的前景。
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来源期刊
CiteScore
12.70
自引率
15.30%
发文量
719
审稿时长
44 days
期刊介绍: Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.
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