Add to ORKGThis work focuses on providing accurate low-cost approximations of stochastic finite elements simulations in the framework of linear elasticity. In [E. Florentin, P. Diez, Adaptive reduced basis strategy based on goal oriented error assessment for stochastic problems, Comput. Methods Appl. Mech. Engrg. 225-228 (2012) 116-127], an adaptive strategy has been introduced as an improved Monte-Carlo method for multi-dimensional large stochastic problems. We provide here a complete analysis of the method including a new enhanced goal-oriented error estimator and estimates of CPU cost gain. Technical insight of these two topics are presented in details and numerical examples show the interest of these new developments
In this work, we consider an elliptic partial differential equation with a random coefficient solved...
The focus of this work is the introduction of some computable a posteriori error control to the popu...
We present an r-adaptivity approach for boundary value problems with randomly fluctuating mater...
This work focuses on providing accurate low-cost approximations of stochastic ¿nite elements simulat...
In the framework of stochastic non-intrusive finite element modeling, a common practice is using Mon...
International audienceThis contribution addresses the modelling and the stochastic analysis of trans...
The presented adaptive modelling approach aims to jointly control the level of renement for each of ...
The optimisation of discretisation and stochastic errors under a single criterion is not a simple t...
This paper presents mutli-element Stochastic Reduced Basis Methods (ME-SRBMs) for solving linear sto...
This paper develops two-step methods for solving contact problems with uncertainties. In the first s...
Equilibration error estimators have been shown to commonly lead to very accurate guaranteed error bo...
While multilevel Monte Carlo (MLMC) methods for the numerical approximation of partial differential ...
In this work, a Reduced Basis (RB) approach is used to solve a large number of boundary value proble...
International audienceThe reduced basis method is a powerful model reduction technique designed to s...
We use the ideas of goal-oriented error estimation and adaptivity to design and implement an efficie...
In this work, we consider an elliptic partial differential equation with a random coefficient solved...
The focus of this work is the introduction of some computable a posteriori error control to the popu...
We present an r-adaptivity approach for boundary value problems with randomly fluctuating mater...
This work focuses on providing accurate low-cost approximations of stochastic ¿nite elements simulat...
In the framework of stochastic non-intrusive finite element modeling, a common practice is using Mon...
International audienceThis contribution addresses the modelling and the stochastic analysis of trans...
The presented adaptive modelling approach aims to jointly control the level of renement for each of ...
The optimisation of discretisation and stochastic errors under a single criterion is not a simple t...
This paper presents mutli-element Stochastic Reduced Basis Methods (ME-SRBMs) for solving linear sto...
This paper develops two-step methods for solving contact problems with uncertainties. In the first s...
Equilibration error estimators have been shown to commonly lead to very accurate guaranteed error bo...
While multilevel Monte Carlo (MLMC) methods for the numerical approximation of partial differential ...
In this work, a Reduced Basis (RB) approach is used to solve a large number of boundary value proble...
International audienceThe reduced basis method is a powerful model reduction technique designed to s...
We use the ideas of goal-oriented error estimation and adaptivity to design and implement an efficie...
In this work, we consider an elliptic partial differential equation with a random coefficient solved...
The focus of this work is the introduction of some computable a posteriori error control to the popu...
We present an r-adaptivity approach for boundary value problems with randomly fluctuating mater...