ABSTRACT: Uncertainty quantification is the state-of-the-art framework dealing with uncertainties aris-ing in all kind of real-life problems. One of the framework’s functions is to propagate uncertainties from the stochastic input factors to the output quantities of interest, hence the name uncertainty propagation. To this end, polynomial chaos expansions (PCE) have been effectively used in a wide variety of practical problems. However, great challenges are hindering the use of PCE for time-dependent problems. More precisely, the accuracy of PCE tends to decrease in time. In this paper, we develop an approach based on a stochastic time-transform, which allows one to apply low-order PCE to complex time-dependent problems. 1
Generalized polynomial chaos is known to fail for long-term integration, loosing its optimal converg...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
Uncertainty exists widely in engineering design. As one of the key components of engineering design,...
Uncertainty quantification is the state-of-the-art framework dealing with uncertainties arising in a...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
Here, we examine the suitability of truncated Polynomial Chaos Expansions (PCE) and truncated Gram-C...
This paper presents an algorithm for efficient uncertainty quantification (UQ) in the presence of ma...
We consider Uncertainty Quanti¿cation (UQ) by expanding the solution in so-called generalized Polyno...
Inherent physical uncertainties can have a significant influence on computational predictions. It is...
Polynomial chaos expansions (PCE) have proven efficiency in a number of fields for propagating param...
In many fields, active research is currently focused on quantification and simulation of model uncer...
This paper proposes a surrogate model which is able to deal with mixed uncertain dynamical systems: ...
Uncertainty quantification techniques based on the spectral approach have been studied extensively i...
Abstract. In this paper we review some applications of generalized polynomial chaos expansion for un...
Generalized polynomial chaos is known to fail for long-term integration, loosing its optimal converg...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
Uncertainty exists widely in engineering design. As one of the key components of engineering design,...
Uncertainty quantification is the state-of-the-art framework dealing with uncertainties arising in a...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
Here, we examine the suitability of truncated Polynomial Chaos Expansions (PCE) and truncated Gram-C...
This paper presents an algorithm for efficient uncertainty quantification (UQ) in the presence of ma...
We consider Uncertainty Quanti¿cation (UQ) by expanding the solution in so-called generalized Polyno...
Inherent physical uncertainties can have a significant influence on computational predictions. It is...
Polynomial chaos expansions (PCE) have proven efficiency in a number of fields for propagating param...
In many fields, active research is currently focused on quantification and simulation of model uncer...
This paper proposes a surrogate model which is able to deal with mixed uncertain dynamical systems: ...
Uncertainty quantification techniques based on the spectral approach have been studied extensively i...
Abstract. In this paper we review some applications of generalized polynomial chaos expansion for un...
Generalized polynomial chaos is known to fail for long-term integration, loosing its optimal converg...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
Uncertainty exists widely in engineering design. As one of the key components of engineering design,...