Yaqi Wang
Idaho National Laboratory
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Featured researches published by Yaqi Wang.
Nuclear Science and Engineering | 2014
Yaqi Wang; Hongbin Zhang; Richard C. Martineau
Abstract A Galerkin weak form for the monoenergetic neutron transport equation with a continuous finite element method and discrete ordinate method is developed based on self-adjoint angular flux formulation. This weak form is modified for treating void regions. A consistent diffusion scheme is developed with P0 projection. Correction terms of the diffusion scheme are derived to reproduce the transport scalar flux. A source iteration that decouples the solution of all directions with both linear and nonlinear diffusion accelerations is developed and demonstrated. One-dimensional Fourier analysis is conducted to demonstrate the stability of the linear and nonlinear diffusion accelerations. Numerical results of these schemes are presented.
Journal of Computational Physics | 2017
Sebastian Schunert; Yaqi Wang; Frederick N. Gleicher; Javier Ortensi; Benjamin Baker; Vincent M. Laboure; Congjian Wang; Mark D. DeHart; Richard C. Martineau
Abstract This work presents a flexible nonlinear diffusion acceleration (NDA) method that discretizes both the S N transport equation and the diffusion equation using the discontinuous finite element method (DFEM). The method is flexible in that the diffusion equation can be discretized on a coarser mesh with the only restriction that it is nested within the transport mesh and the FEM shape function orders of the two equations can be different. The consistency of the transport and diffusion solutions at convergence is defined by using a projection operator mapping the transport into the diffusion FEM space. The diffusion weak form is based on the modified incomplete interior penalty (MIP) diffusion DFEM discretization that is extended by volumetric drift, interior face, and boundary closure terms. In contrast to commonly used coarse mesh finite difference (CMFD) methods, the presented NDA method uses a full FEM discretized diffusion equation for acceleration. Suitable projection and prolongation operators arise naturally from the FEM framework. Via Fourier analysis and numerical experiments for a one-group, fixed source problem the following properties of the NDA method are established for structured quadrilateral meshes: (1) the presented method is unconditionally stable and effective in the presence of mild material heterogeneities if the same mesh and identical shape functions either of the bilinear or biquadratic type are used, (2) the NDA method remains unconditionally stable in the presence of strong heterogeneities, (3) the NDA method with bilinear elements extends the range of effectiveness and stability by a factor of two when compared to CMFD if a coarser diffusion mesh is selected. In addition, the method is tested for solving the C5G7 multigroup, eigenvalue problem using coarse and fine mesh acceleration. While NDA does not offer an advantage over CMFD for fine mesh acceleration, it reduces the iteration count required for convergence by almost a factor of two in the case of coarse mesh acceleration.
Annals of Nuclear Energy | 2015
Sebastian Schunert; Yaqi Wang; Richard C. Martineau; Mark D. DeHart
Archive | 2011
Yaqi Wang; Hongbin Zhang; Ronaldo Szilard; Richard C. Martineau
Archive | 2014
Frederick N. Gleicher; R.L. Williamson; Javier Ortensi; Yaqi Wang; Benjamin Spencer; S.R. Novascone; Jason Hales; Richard C. Martineau
Numerical Linear Algebra With Applications | 2018
Fande Kong; Yaqi Wang; Sebastian Schunert; John W. Peterson; Cody Permann; David Andrs; Richard C. Martineau
Progress in Nuclear Energy | 2017
Yaqi Wang; Sebastian Schunert; Mark D. DeHart; Richard C. Martineau; Weixiong Zheng
Numerical Linear Algebra With Applications | 2018
Fande Kong; Yaqi Wang; Sebastian Schunert; John W. Peterson; Cody Permann; David Andrs; Richard C. Martineau
Archive | 2018
Javier Ortensi; Sebastian Schunert; Yaqi Wang; Vincent M. Laboure; Frederick N. Gleicher; Richard C. Martineau
Annals of Nuclear Energy | 2018
Javier Ortensi; Yaqi Wang; Alexandre Laurier; Sebastian Schunert; Alain Hébert; Mark D. DeHart