Iterative Methods for Model Reduction by Domain Decomposition

نویسندگان

  • Marcelo Buffoni
  • Angelo Iollo
  • Haysam Telib
چکیده

We propose a method to reduce the computational effort to solve a partial differential equation on a given domain. The main idea is to split the domain of interest in two subdomains, and to use different approximation methods in each of the two subdomains. In particular, in one subdomain we discretize the governing equations by a canonical scheme, whereas in the other one we solve a reduced order model of the original problem. Different approaches to couple the loworder model to the usual discretization are presented. The effectiveness of these approaches is tested on numerical examples pertinent to non-linear model problems including the Laplace equation with non-linear boundary conditions and the compressible Euler equations. Key-words: low-order models, domain decomposition, compressible flows ∗ INRIA Futurs, Equipe-Projet MC2 and Institut de Mathématiques de Bordeaux, UMR 5251 CNRS, Université Bordeaux 1, 33405 Talence cedex, France. † Dipartimento di Ingegneria Aeronautica e Spaziale, Politecnico di Torino. 10129 Torino, Italy Méthodes Itératives pour la Réduction de Modèles par Décomposition de Domaine Résumé : On propose une méthode pour réduire les efforts de calcul pour résoudre une équation aux dérivées partielles sur un domaine donné. L’idée principale est de diviser le domaine considéré en deux sous-domaines, et d’employer différentes méthodes d’approximation dans chacun des deux sous-domaines. En particulier, dans un des sous-domaines l’équation en question est discrétisée par une méthode canonique, tandis que dans l’autre un modèle d’ordre réduit du problème original est utilisé. Des stratégies différentes pour coupler le modèle d’ordre réduit á la discrétisation habituelle sont présentés. L’efficacité de ces approches est testée sur des exemples numériques pertinentes pour des problèmes modèles non linéaires, notamment l’équation de Laplace, avec des conditions limites non linéaires, et les équations d’Euler compressibles. Mots-clés : modèles réduits, décomposition de domaine, écoulements compressibles Iterative Methods for Model Reduction by Domain Decomposition 3

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Iterative Domain Decomposition Procedure for the Reduced Basis Method

Reduced basis methods allow efficient model reduction of parametrized partial differential equations. In the current paper, we consider a reduced basis scheme for homogeneous domain decomposition problems. The method is based on iterative Dirichlet-Neumann coupling. We prove convergence of the iterative reduced scheme, derive rigorous a-posteriori error bounds and provide a full offline/online ...

متن کامل

Updating finite element model using frequency domain decomposition method and bees algorithm

The following study deals with the updating the finite element model of structures using the operational modal analysis. The updating process uses an evolutionary optimization algorithm, namely bees algorithm which applies instinctive behavior of honeybees for finding food sources. To determine the uncertain updated parameters such as geometry and material properties of the structure, local and...

متن کامل

Output Error Bounds for the Dirichlet-Neumann Reduced Basis Method

The Dirichlet-Neumann reduced basis method is a model order reduction method for homogeneous domain decomposition of elliptic PDE’s on a-priori known geometries. It is based on an iterative scheme with full offline-online decomposition and rigorous a-posteriori error estimates. We show that the primal-dual framework for non-compliant output quantities can be transferred to this method. The resu...

متن کامل

Frequency Domain Identiication, Subspace Methods and Periodic Excitation

Recent frequency domain identiication algorithms based on subspace based techniques are discussed. The algorithms construct a state-space model by means of extraction of the signal subspace from a matrix constructed from frequency data. A singular value decomposition plays a key part in the subspace extraction. The subspace methods are non-iterative methods in contrast to classical iterative pa...

متن کامل

OPTIMAL ANALYSIS OF NON-REGULAR GRAPHS USING THE RESULTS OF REGULAR MODELS VIA AN ITERATIVE METHOD

In this paper an efficient method is developed for the analysis of non-regular graphs which contain regular submodels. A model is called regular if it can be expressed as the product of two or three subgraphs. Efficient decomposition methods are available in the literature for the analysis of some classes of regular models. In the present method, for a non-regular model, first the nodes of the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007