In a posteriori error analysis of reduced basis approximations to affinely parametrized partial differential equations, the construction of lower bounds for the coercivity and inf-sup stability constants is essential. In [Huynh et al., C. R. Acad. Sci. Paris Ser. I Math. 345 (2007) 473–478], the authors presented an efficient method, compatible with an off-line/on-line strategy, where the on-line computation is reduced to minimizing a linear functional under a few linear constraints. These constraints depend on nested sets of parameters obtained iteratively using a greedy algorithm. We improve here this method so that it becomes more efficient and robust due to two related properties: (i) the lower bound is obtained by a monotonic process ...
Summarization: We present a technique for the rapid and reliable prediction of linear-functional out...
The Reduced Basis Method (RBM) generates low-order models of parametrized partial differential equat...
We present a technique for the rapid and reliable prediction of linear–functional out-puts of ellipt...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial dif...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial dif...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial dif...
International audienceIn a posteriori error analysis of reduced basis approximations to affinely par...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial diff...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
Note presented by Olivier Pironneau. We present an approach to the construction of lower bounds for ...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
Pour citer cet article: Y. Chen et al., C. R. Acad. Sci. Paris, Ser. I 346 (2008)International audie...
For accurate a posteriori error analysis of the reduced basis method for coercive and non-coercive p...
Summarization: We present a technique for the rapid and reliable prediction of linear-functional out...
The Reduced Basis Method (RBM) generates low-order models of parametrized partial differential equat...
We present a technique for the rapid and reliable prediction of linear–functional out-puts of ellipt...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial dif...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial dif...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial dif...
International audienceIn a posteriori error analysis of reduced basis approximations to affinely par...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial diff...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
Note presented by Olivier Pironneau. We present an approach to the construction of lower bounds for ...
We present a new approach for the construction of lower bounds for the inf-sup stability constants r...
Pour citer cet article: Y. Chen et al., C. R. Acad. Sci. Paris, Ser. I 346 (2008)International audie...
For accurate a posteriori error analysis of the reduced basis method for coercive and non-coercive p...
Summarization: We present a technique for the rapid and reliable prediction of linear-functional out...
The Reduced Basis Method (RBM) generates low-order models of parametrized partial differential equat...
We present a technique for the rapid and reliable prediction of linear–functional out-puts of ellipt...