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首页> 外文期刊>International journal of computer mathematics >Anisotropic mesh adaptation for steady convection-dominated problems based on bubble-type local mesh generation
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Anisotropic mesh adaptation for steady convection-dominated problems based on bubble-type local mesh generation

机译:基于泡沫型本地网格生成的稳定对流主导问题的各向异性网格适应

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ABSTRACT For convection–diffusion equations, it is difficult to obtain accurate solutions due to the presence of layers when convection dominates the diffusion. In this work, a new anisotropic adaptive meshing algorithm for convection-dominated problems is designed to optimize the mesh alignment, size and aspect ratio. Three main techniques are used. First, the streamline upwind Petrov–Galerkin (SUPG) method is used to stabilize the numerical scheme. Second, the a posteriori error estimator is computed and a new metric tensor is deduced. Third, optimal anisotropic meshes are generated by the anisotropic bubble-type local mesh generation (ABLMG) method. Compared with other mesh generation strategies, high-quality mesh can be obtained efficiently. Our algorithm is tested on several examples and the numerical results show that the algorithm is robust.
机译:摘要对于对流扩散方程,难以在对流主导扩散时由于层的存在而获得准确的解决方案。在这项工作中,对对流主导问题的新的各向异性自适应网格化算法旨在优化网格对准,尺寸和宽高比。使用三种主要技术。首先,流线Upwind Petrov-Galerkin(SupG)方法用于稳定数值方案。其次,计算后后误差估计器并推导出新的度量张量。第三,最佳各向异性网状物由各向异性气泡型局部网格产生(ABLMG)方法产生。与其他网格生成策略相比,可以有效地获得高质量的网格。在若干示例中测试了我们的算法,数值结果表明该算法是稳健的。

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