7,005 research outputs found

    An isogeometric analysis for elliptic homogenization problems

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    A novel and efficient approach which is based on the framework of isogeometric analysis for elliptic homogenization problems is proposed. These problems possess highly oscillating coefficients leading to extremely high computational expenses while using traditional finite element methods. The isogeometric analysis heterogeneous multiscale method (IGA-HMM) investigated in this paper is regarded as an alternative approach to the standard Finite Element Heterogeneous Multiscale Method (FE-HMM) which is currently an effective framework to solve these problems. The method utilizes non-uniform rational B-splines (NURBS) in both macro and micro levels instead of standard Lagrange basis. Beside the ability to describe exactly the geometry, it tremendously facilitates high-order macroscopic/microscopic discretizations thanks to the flexibility of refinement and degree elevation with an arbitrary continuity level provided by NURBS basis functions. A priori error estimates of the discretization error coming from macro and micro meshes and optimal micro refinement strategies for macro/micro NURBS basis functions of arbitrary orders are derived. Numerical results show the excellent performance of the proposed method

    Isogeometric analysis applied to frictionless large deformation elastoplastic contact

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    This paper focuses on the application of isogeometric analysis to model frictionless large deformation contact between deformable bodies and rigid surfaces that may be represented by analytical functions. The contact constraints are satisfied exactly with the augmented Lagrangian method, and treated with a mortar-based approach combined with a simplified integration method to avoid segmentation of the contact surfaces. The spatial discretization of the deformable body is performed with NURBS and C0-continuous Lagrange polynomial elements. The numerical examples demonstrate that isogeometric surface discretization delivers more accurate and robust predictions of the response compared to Lagrange discretizations
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