We consider “Lagrangian” reduced-basis methods for single-parameter symmetric coercive elliptic partial differential equations. We show that, for a logarithmic-(quasi-)uniform distribution of sample points, the reduced–basis approximation converges exponentially to the exact solution uniformly in parameter space. Furthermore, the convergence rate depends only weakly on the continuity-coercivity ratio of the operator: thus very low-dimensional approximations yield accurate solutions even for very wide parametric ranges. Numerical tests (reported elsewhere) corroborate the theoretical predictions
Parametric partial differential equations are commonly used to model physical systems. They also ari...
It has recently been demonstrated that locality of spatial supports in the parametrization of coeffi...
In this paper, we extend the reduced-basis methods and associated a posteriori error estimators dev...
International audienceWe consider "Lagrangian" reduced-basis methods for single-parameter symmetric ...
International audienceWe consider "Lagrangian" reduced-basis methods for single-parameter symmetric ...
Summarization: We present a technique for the rapid and reliable prediction of linear-functional out...
The set of solutions of a parameter-dependent linear partial differential equation with smooth coeff...
Abstract. We present a technique for the rapid and reliable prediction of linear-functional outputs ...
The set of solutions of a parameter-dependent linear partial differential equation with smooth coeff...
In this paper we consider (hierarchical, Lagrange) reduced basis approximation and a posteriori erro...
We present a technique for the rapid and reliable prediction of linear–functional out-puts of ellipt...
Abstract. We present a new “hp ” parameter multi-domain certified reduced basis method for rapid and...
We consider a parametric elliptic PDE with a scalar piecewise constant diffusion coefficient taking ...
Parametric partial differential equations are commonly used to model physical systems. They also ari...
We present an application in multi-parametrized subdomains based on a technique for the rapid and re...
Parametric partial differential equations are commonly used to model physical systems. They also ari...
It has recently been demonstrated that locality of spatial supports in the parametrization of coeffi...
In this paper, we extend the reduced-basis methods and associated a posteriori error estimators dev...
International audienceWe consider "Lagrangian" reduced-basis methods for single-parameter symmetric ...
International audienceWe consider "Lagrangian" reduced-basis methods for single-parameter symmetric ...
Summarization: We present a technique for the rapid and reliable prediction of linear-functional out...
The set of solutions of a parameter-dependent linear partial differential equation with smooth coeff...
Abstract. We present a technique for the rapid and reliable prediction of linear-functional outputs ...
The set of solutions of a parameter-dependent linear partial differential equation with smooth coeff...
In this paper we consider (hierarchical, Lagrange) reduced basis approximation and a posteriori erro...
We present a technique for the rapid and reliable prediction of linear–functional out-puts of ellipt...
Abstract. We present a new “hp ” parameter multi-domain certified reduced basis method for rapid and...
We consider a parametric elliptic PDE with a scalar piecewise constant diffusion coefficient taking ...
Parametric partial differential equations are commonly used to model physical systems. They also ari...
We present an application in multi-parametrized subdomains based on a technique for the rapid and re...
Parametric partial differential equations are commonly used to model physical systems. They also ari...
It has recently been demonstrated that locality of spatial supports in the parametrization of coeffi...
In this paper, we extend the reduced-basis methods and associated a posteriori error estimators dev...