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Dive into the research topics where Siu Wun Cheung is active.

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Featured researches published by Siu Wun Cheung.


Journal of Computational Physics | 2015

Staggered discontinuous Galerkin methods for the incompressible Navier-Stokes equations

Siu Wun Cheung; Eric T. Chung; Hyea Hyun Kim; Yue Qian

In this paper, we present a staggered discontinuous Galerkin method for the approximation of the incompressible Navier-Stokes equations. Our new method combines the advantages of discontinuous Galerkin methods and staggered meshes, and results in many good properties, namely local and global conservations, optimal convergence and superconvergence through the use of a local postprocessing technique. Another key feature is that our method provides a skew-symmetric discretization of the convection term, with the aim of giving a better conservation property compared with existing discretizations. We will present extensive numerical results, including Kovasznay flow, Taylor vortex flow, lid-driven cavity flow, parallel plate flow and channel expansion flow, to show the performance of the method.


Journal of Scientific Computing | 2018

A Mass Conservative Scheme for Fluid–Structure Interaction Problems by the Staggered Discontinuous Galerkin Method

Siu Wun Cheung; Eric T. Chung; Hyea Hyun Kim

In this paper, we develop a new mass conservative numerical scheme for the simulations of a class of fluid–structure interaction problems. We will use the immersed boundary method to model the fluid–structure interaction, while the fluid flow is governed by the incompressible Navier–Stokes equations. The immersed boundary method is proven to be a successful scheme to model fluid–structure interactions. To ensure mass conservation, we will use the staggered discontinuous Galerkin method to discretize the incompressible Navier–Stokes equations. The staggered discontinuous Galerkin method is able to preserve the skew-symmetry of the convection term. In addition, by using a local postprocessing technique, the weakly divergence free velocity can be used to compute a new postprocessed velocity, which is exactly divergence free and has a superconvergence property. This strongly divergence free velocity field is the key to the mass conservation. Furthermore, energy stability is improved by the skew-symmetric discretization of the convection term. We will present several numerical results to show the performance of the method.


arXiv: Numerical Analysis | 2018

Deep Global Model Reduction Learning.

Siu Wun Cheung; Eric T. Chung; Yalchin Efendiev; Eduardo Gildin; Yating Wang


arXiv: Numerical Analysis | 2018

Dynamic Data-driven Bayesian GMsFEM

Siu Wun Cheung; Nilabja Guha


arXiv: Numerical Analysis | 2018

Constraint Energy Minimizing Generalized Multiscale Finite Element Method for dual continuum model

Siu Wun Cheung; Eric T. Chung; Yalchin Efendiev; Wing Tat Leung; Maria Vasilyeva


arXiv: Numerical Analysis | 2018

An embedded SDG method for the convection-diffusion equation.

Siu Wun Cheung; Eric T. Chung


arXiv: Numerical Analysis | 2018

Deep Multiscale Model Learning.

Yating Wang; Siu Wun Cheung; Eric T. Chung; Yalchin Efendiev; Min Wang


arXiv: Numerical Analysis | 2018

Nonlocal multicontinua upscaling for multicontinua flow problems in fractured porous media

Maria Vasilyeva; Eric T. Chung; Siu Wun Cheung; Yating Wang; Georgy Prokopev


arXiv: Numerical Analysis | 2018

Prediction of Discretization of GMsFEM using Deep Learning.

Min Wang; Siu Wun Cheung; Eric T. Chung; Yalchin Efendiev; Wing Tat Leung; Yating Wang


International Journal for Multiscale Computational Engineering | 2017

BAYESIAN MULTISCALE FINITE ELEMENT METHODS. MODELING MISSING SUBGRID INFORMATION PROBABILISTICALLY

Yalchin Efendiev; Wing Tat Leung; Siu Wun Cheung; Nilabja Guha; Viet Ha Hoang; Bani K. Mallick

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Eric T. Chung

The Chinese University of Hong Kong

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Maria Vasilyeva

North-Eastern Federal University

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Yiwei Zhao

The Chinese University of Hong Kong

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Yue Qian

The Chinese University of Hong Kong

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