Computational reduction for parametrized PDEs: strategies and applications
نویسندگان
چکیده
In this paper we present a compact review on the mostly used techniques for computational reduction in numerical approximation of partial differential equations. We highlight the common features of these techniques and provide a detailed presentation of the reduced basis method, focusing on greedy algorithms for the construction of the reduced spaces. An alternative family of reduction techniques based on surrogate response surface models is briefly recalled too. Then, a simple example dealing with inviscid flows is presented, showing the reliability of the reduced basis method and a comparison between this technique and some surrogate models. Mathematics Subject Classification (2010). Primary 78M34; Secondary 49J20, 65N30, 76D55.
منابع مشابه
Low-Rank Tensor Krylov Subspace Methods for Parametrized Linear Systems
We consider linear systems A(α)x(α) = b(α) depending on possibly many parameters α = (α1, . . . ,αp). Solving these systems simultaneously for a standard discretization of the parameter space would require a computational effort growing exponentially in the number of parameters. We show that this curse of dimensionality can be avoided for sufficiently smooth parameter dependencies. For this pur...
متن کاملReduced Basis Method for Finite Volume Approximation of Evolution Equations on Parametrized Geometries
In this paper we discuss parametrized partial differential equations (PDEs) for parameters that describe the geometry of the underlying problem. One can think of applications in control theory and optimization which depend on time-consuming parameter-studies of such problems. Therefore, we want to reduce the order of complexity of the numerical simulations for such PDEs. Reduced Basis (RB) meth...
متن کاملModel order reduction by reduced basis for optimal control and shape optimization
Optimal control and shape optimization problems governed by partial differential equations (PDEs) arise in many applications involving computational fluid dynamics; they can be seen as many-query problems since they involve repetitive evaluations of outputs expressed as functionals of field variables. Since they usually require big computational efforts, looking for computational efficiency in ...
متن کاملReduction strategies for PDE-constrained optimization problems in haemodynamics
Solving optimal control problems for many different scenarios obtained by varying a set of parameters in the state system is a computationally extensive task. In this paper we present a new reduced framework for the formulation, the analysis and the numerical solution of parametrized PDE-constrained optimization problems. This framework is based on a suitable saddle-point formulation of the opt...
متن کاملCertified Reduced Basis Approximation for Parametrized Partial Differential Equations and Applications
Reduction strategies, such as model order reduction (MOR) or reduced basis (RB) methods, in scientific computing may become crucial in applications of increasing complexity. In this paper we review the reduced basis method (built upon a high-fidelity “truth” finite element approximation) for a rapid and reliable approximation of parametrized partial differential equations, and comment on their ...
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 2012