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引用次数: 1
摘要
摘要将高阶混合有限元离散化技术及其相关的预条件迭代求解方法应用于两个空间维度的可变Eddington因子(VEF)方程。将混合有限元VEF离散化与离散坐标输运方程的高阶间断伽辽金(DG)离散化相耦合,形成与高阶(曲线)网格兼容的有效线性输运算法。劳伦斯利弗莫尔国家实验室(LLNL)在流体力学计算中使用了高阶混合有限元方法,从而激发了VEF和输运离散化的结合。由于VEF方程的数学结构,标准的Raviart - Thomas (RT)混合有限元不能近似求解VEF方程中的矢量变量。相反,我们研究了基于对每个矢量组件使用连续有限元的三种替代方案,一种使用类似dg技术的非一致性RT方法,以及一种杂交RT方法。我们给出的数值结果表明,在迭代求解耦合输运-VEF系统和用于反演离散VEF方程的预条件线性求解器中,具有高阶精度、与曲面网格兼容、鲁棒性和高效收敛性。
High-Order Mixed Finite Element Variable Eddington Factor Methods
Abstract We apply high-order mixed finite element discretization techniques and their associated preconditioned iterative solvers to the Variable Eddington Factor (VEF) equations in two spatial dimensions. The mixed finite element VEF discretizations are coupled to a high-order Discontinuous Galerkin (DG) discretization of the discrete ordinates transport equation to form effective linear transport algorithms that are compatible with high-order (curved) meshes. This combination of VEF and transport discretizations is motivated by the use of high-order mixed finite element methods in hydrodynamics calculations at the Lawrence Livermore National Laboratory (LLNL). Due to the mathematical structure of the VEF equations, the standard Raviart Thomas (RT) mixed finite elements cannot be used to approximate the vector variable in the VEF equations. Instead, we investigate three alternatives based on the use of continuous finite elements for each vector component, a non-conforming RT approach where DG-like techniques are used, and a hybridized RT method. We present numerical results that demonstrate high-order accuracy, compatibility with curved meshes, and robust and efficient convergence in iteratively solving the coupled transport-VEF system and in the preconditioned linear solvers used to invert the discretized VEF equations.
期刊介绍:
Emphasizing computational methods and theoretical studies, this unique journal invites articles on neutral-particle transport, kinetic theory, radiative transfer, charged-particle transport, and macroscopic transport phenomena. In addition, the journal encourages articles on uncertainty quantification related to these fields. Offering a range of information and research methodologies unavailable elsewhere, Journal of Computational and Theoretical Transport brings together closely related mathematical concepts and techniques to encourage a productive, interdisciplinary exchange of ideas.