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  • 1.
    Hoffman, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    de Abreu, Rodrigo Vilela
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Degirmenci, Niyazi Cem
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Müller, Kaspar
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Nazarov, Murtazo
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Spühler, Jeannette Hiromi
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Unicorn: Parallel adaptive finite element simulation of turbulent flow and fluid-structure interaction for deforming domains and complex geometry2013In: Computers & Fluids, ISSN 0045-7930, E-ISSN 1879-0747, Vol. 80, no SI, p. 310-319Article in journal (Refereed)
    Abstract [en]

    We present a framework for adaptive finite element computation of turbulent flow and fluid structure interaction, with focus on general algorithms that allow for complex geometry and deforming domains. We give basic models and finite element discretization methods, adaptive algorithms and strategies for efficient parallel implementation. To illustrate the capabilities of the computational framework, we show a number of application examples from aerodynamics, aero-acoustics, biomedicine and geophysics. The computational tools are free to download open source as Unicorn, and as a high performance branch of the finite element problem solving environment DOLFIN, both part of the FEniCS project.

  • 2.
    Hoffman, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Vilela de Abreu, Rodrigo
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Degirmenci, Niyazi Cem
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Müller, Kaspar
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Nazarov, Murtazo
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis, NA.
    Spühler, Jeannette Hiromi
    Unicorn: Parallel adaptive finite element simulation of turbulent flow and fluid-structure interaction for deforming domains and complex geometry2011Report (Other academic)
    Abstract [en]

    We present a framework for adaptive finite element computation of turbulent flow and fluid-structure interaction, with focus on general algorithms that allow for complex geometry and deforming domains. We give basic models and finite element discretization methods, adaptive algorithms and strategies for e cient parallel implementation. To illustrate the capabilities of the computational framework, we show a number of application examples from aerodynamics, aero-acoustics, biomedicine and geophysics. The computational tools are free to download open source as Unicorn, and as a high performance branch of the finite element problem solving environment DOLFIN, both part of the FEniCS project

  • 3.
    Qin, Xinsheng
    et al.
    Univ Washington, Dept Civil & Environm Engn, More Hall Box 352700, Seattle, WA 98195 USA..
    Motley, Michael
    Univ Washington, Dept Civil & Environm Engn, More Hall Box 352700, Seattle, WA 98195 USA..
    LeVeque, Randall
    Univ Washington, Dept Appl Math, Seattle, WA 98195 USA..
    Gonzalez, Frank
    Univ Washington, Dept Earth & Space Sci, Seattle, WA 98195 USA..
    Mueller, Kaspar
    KTH, School of Computer Science and Communication (CSC).
    A comparison of a two-dimensional depth-averaged flow model and a three-dimensional RANS model for predicting tsunami inundation and fluid forces2018In: Natural hazards and earth system sciences, ISSN 1561-8633, E-ISSN 1684-9981, Vol. 18, no 9, p. 2489-2506Article in journal (Refereed)
    Abstract [en]

    The numerical modeling of tsunami inundation that incorporates the built environment of coastal communities is challenging for both 2-D and 3-D depth-integrated models, not only in modeling the flow but also in predicting forces on coastal structures. For depth-integrated 2-D models, inundation and flooding in this region can be very complex with variation in the vertical direction caused by wave breaking on shore and interactions with the built environment, and the model may not be able to produce enough detail. For 3-D models, a very fine mesh is required to properly capture the physics, dramatically increasing the computational cost and rendering impractical the modeling of some problems. In this paper, comparisons are made between Geo-Claw, a depth-integrated 2-D model based on the nonlinear shallow-water equations (NSWEs), and OpenFOAM, a 3-D model based on Reynolds-averaged Navier-Stokes (RANS) equation for tsunami inundation modeling. The two models were first validated against existing experimental data of a bore impinging onto a single square column. Then they were used to simulate tsunami inundation of a physical model of Seaside, Oregon. The resulting flow parameters from the models are compared and discussed, and these results are used to extrapolate tsunami-induced force predictions. It was found that the 2-D model did not accurately capture the important details of the flow near initial impact due to the transiency and large vertical variation of the flow. Tuning the drag coefficient of the 2-D model worked well to predict tsunami forces on structures in simple cases, but this approach was not always reliable in complicated cases. The 3-D model was able to capture transient characteristic of the flow, but at a much higher computational cost; it was found this cost can be alleviated by subdividing the region into reasonably sized subdomains without loss of accuracy in critical regions.

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