Surface Couplings for Subdomain-Wise Isoviscous Gradient Based Stokes Finite Element Discretizations
    Huber M, Rüde U, Waluga C, Wohlmuth BI  (2018)
    
    
    Publication Type: Journal article
    Publication year: 2018
Journal
    
    Publisher: Springer US
    
    
    
    Book Volume: 74
    
    Pages Range: 895--919
    
    
    
    
    Journal Issue: 2
    
    URI: http://scholar.google.de/scholar_url?url=https://link.springer.com/article/10.1007/s10915-017-0470-3&hl=de&sa=T&ei=tAqjXODQFpCemgHJjq74Cw&scisig=AAGBfm1hHBkob7udfqJbTd6xziko4-mvEw&nossl=1&ws=2560x1195&at=
    DOI: 10.1007/s10915-017-0470-3
    
    Abstract
    The Stokes system with constant viscosity can be cast into different formulations by exploiting the incompressibility constraint. For instance, the rate of strain tensor in the weak formulation can be replaced by the velocity-gradient yielding a decoupling of the velocity components in the different coordinate directions. Consequently, the discretization of this partly decoupled formulation leads to fewer nonzero entries in the stiffness matrix. This is of particular interest in large scale simulations where a reduced memory bandwidth requirement can help to significantly accelerate the computations. In the case of a piecewise constant viscosity, as it typically arises in multi-phase flows, or when the boundary conditions involve traction, the situation is more complex, and one has to treat the cross derivatives in the original Stokes system with care. A naive application of the standard vectorial Laplacian results in a …
    
    
    
        
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    How to cite
    
        APA:
        Huber, M., Rüde, U., Waluga, C., & Wohlmuth, B.I. (2018). Surface Couplings for Subdomain-Wise Isoviscous Gradient Based Stokes Finite Element Discretizations. Journal of Scientific Computing, 74(2), 895--919. https://doi.org/10.1007/s10915-017-0470-3
    
    
        MLA:
        Huber, Markus, et al. "Surface Couplings for Subdomain-Wise Isoviscous Gradient Based Stokes Finite Element Discretizations." Journal of Scientific Computing 74.2 (2018): 895--919.
    
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