Spacetime Wavelet Method for the Solution of Nonlinear Partial Differential Equations

IF 2.9 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Cody D. Cochran, Karel Matouš
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引用次数: 0

Abstract

We propose a high-order spacetime wavelet method for the solution of nonlinear partial differential equations with a user-prescribed accuracy. The technique utilizes wavelet theory with a priori error estimates to discretize the problem in both the spatial and temporal dimensions simultaneously. We also propose a novel wavelet-based recursive algorithm to reduce the system sensitivity stemming from steep initial and/or boundary conditions. The resulting nonlinear equations are solved using the Newton–Raphson method. We parallelize the construction of the tangent operator along with the solution of the system of algebraic equations. We perform rigorous verification studies using the nonlinear Burgers' equation. The application of the method is demonstrated by solving the Sod shock tube problem using the Navier–Stokes equations. The numerical results of the method reveal high-order convergence rates for the function as well as its spatial and temporal derivatives. We solve multiscale problems with steep gradients in both the spatial and temporal directions with a priori error estimates.

非线性偏微分方程的时空小波解法
我们提出了一种高阶时空小波解非线性偏微分方程的方法,具有用户规定的精度。该技术利用小波理论和先验误差估计同时在空间和时间维度上离散问题。我们还提出了一种新的基于小波的递归算法,以降低由陡峭的初始和/或边界条件引起的系统灵敏度。用牛顿-拉夫逊方法求解得到的非线性方程。我们将切线算子的构造与代数方程组的解并行化。我们使用非线性Burgers方程进行严格的验证研究。通过应用Navier-Stokes方程求解Sod激波管问题,说明了该方法的应用。该方法的数值结果表明,该函数具有高阶收敛率,其空间导数和时间导数也具有高阶收敛率。我们用先验误差估计来解决空间和时间方向上具有陡峭梯度的多尺度问题。
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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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