Add to ORKGIn the present paper the authors study second-order elliptic parametric partial differential equations, where the Parameters are scalars or distributed functions. By utilizing a modified greedy algorithm a reduced-basis approximation is derived. This new strategy combines the classical greedy algorithm with techniques from PDE constrained optimization. Numerical examples for the Graetz problem illustrate the efficiency of the strategy to handle not only scalar, but also distributed parameter functions
In this paper we present a compact review on the mostly used techniques for computational reduction ...
We propose a suitable model reduction paradigm---the certified reduced basis method (RB)---for the r...
In this paper we present a compact review on the mostly used techniques for computational reduction ...
In the present paper the authors study second-order elliptic parametric partial differential equatio...
Abstract: The reduced basis (RB) method is an efficient technique to solve parametric partial differ...
Abstract. We present a new “hp ” parameter multi-domain certified reduced basis method for rapid and...
In the present paper non-convex multi-objective parameter optimization problems are considered which...
Abstract. Numerical approximation of the solution of partial differential equations plays an importa...
In the present paper non-convex multi-objective parameter optimization problems are considered which...
We present a new reduced basis approach for the efficient and reliable solution of parametrized PDE-...
Reduction strategies, such as model order reduction (MOR) or reduced basis (RB) methods, in scientif...
<p>This thesis investigates in optimization problems constrained by parametrized partial differentia...
This book provides a basic introduction to reduced basis (RB) methods for problems involving the rep...
The reduced basis method [1,2] is an increasingly popular reduced order modeling technique for param...
The convergence and efficiency of the reduced basis method used for the approximation of the solutio...
In this paper we present a compact review on the mostly used techniques for computational reduction ...
We propose a suitable model reduction paradigm---the certified reduced basis method (RB)---for the r...
In this paper we present a compact review on the mostly used techniques for computational reduction ...
In the present paper the authors study second-order elliptic parametric partial differential equatio...
Abstract: The reduced basis (RB) method is an efficient technique to solve parametric partial differ...
Abstract. We present a new “hp ” parameter multi-domain certified reduced basis method for rapid and...
In the present paper non-convex multi-objective parameter optimization problems are considered which...
Abstract. Numerical approximation of the solution of partial differential equations plays an importa...
In the present paper non-convex multi-objective parameter optimization problems are considered which...
We present a new reduced basis approach for the efficient and reliable solution of parametrized PDE-...
Reduction strategies, such as model order reduction (MOR) or reduced basis (RB) methods, in scientif...
<p>This thesis investigates in optimization problems constrained by parametrized partial differentia...
This book provides a basic introduction to reduced basis (RB) methods for problems involving the rep...
The reduced basis method [1,2] is an increasingly popular reduced order modeling technique for param...
The convergence and efficiency of the reduced basis method used for the approximation of the solutio...
In this paper we present a compact review on the mostly used techniques for computational reduction ...
We propose a suitable model reduction paradigm---the certified reduced basis method (RB)---for the r...
In this paper we present a compact review on the mostly used techniques for computational reduction ...