Reduced Basis, POD and PGD Model Reduction Techniques A numerically stable a posteriori error estimator for reduced basis approximations of elliptic equa- tions
نویسندگان
چکیده
The Reduced Basis (RB) method is a well established method for the model order reduction of problems formulated as parametrized partial differential equations. One crucial requirement for the application of RB schemes is the availability of an a posteriori error estimator to reliably estimate the error introduced by the reduction process. However, straightforward implementations of standard residual based estimators show poor numerical stability, rendering them unusable if high accuracy is required. In this work we propose a new algorithm based on representing the residual with respect to a dedicated orthonormal basis, which is both easy to implement and requires little additional computational overhead. A numerical example is given to demonstrate the performance of the proposed algorithm.
منابع مشابه
Reduced Basis Method for Finite Volume Approximations of Parametrized Linear Evolution Equations
The model order reduction methodology of reduced basis (RB) techniques offers efficient treatment of parametrized partial differential equations (PDEs) by providing both approximate solution procedures and efficient error estimates. RB-methods have so far mainly been applied to finite element schemes for elliptic and parabolic problems. In the current study we extend the methodology to general ...
متن کاملReduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations
In this paper we consider (hierarchical, Lagrange) reduced basis approximation and a posteriori error estimation for linear functional outputs of affinely parametrized elliptic coercive partial differential equations. The essential ingredients are (primal-dual) Galerkin projection onto a low-dimensional space associated with a smooth “parametric manifold” — dimension reduction; efficient and ef...
متن کاملReduced basis approximation and a posteriori error estimation for parametrized parabolic PDEs; Application to real-time Bayesian parameter estimation
In this chapter we consider reduced basis approximation and a posteriori error estimation for linear functional outputs of affinely parametrized linear and non-linear parabolic partial differential equations. The essential ingredients are Galerkin projection onto a low-dimensional space associated with a smooth “parametric manifold” — dimension reduction; efficient and effective Greedy and POD-...
متن کاملReduced Basis Method for Finite Volume Approximations of Parametrized Evolution Equations
The model order reduction methodology of reduced basis (RB) techniques offers efficient treatment of parametrized partial differential equations (PDEs) by providing both approximate solution procedures and efficient error estimates. RB-methods have so far mainly been applied to finite element schemes for elliptic and parabolic problems. In the current study we extend the methodology to general ...
متن کاملA new certification framework for the port-reduced static condensation reduced basis element method
In this talk we introduce a new certification framework for the port-reduced static condensation reduced basis element (PR-SCRBE) method [1, 3], which has been developed for the simulation of large component based applications such as bridges or acoustic waveguides. In an offline computational stage we construct a library of interoperable parametrized reference components; in the subsequent onl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014