Flexibility and decoupling in the simple temporal problem (abstract)

Reconfiguration of large-scale surveillance systems (abstract)

In [2] we introduced a theoretical framework for modelling scalable information-aggregation systems. The framework is exposed on the background of a description of METIS, a system prototype aiming at supporting maritime safety and security by facilitating continuous monitoring of vessels in national coastal waters. Among the main problems of...

Efficient uncertainty quantification using a two-step approach with chaos collocation

In this paper a Two Step approach with Chaos Collocation for efficient uncertainty quantification in computational fluid-structure interactions is followed. In Step I, a Sensitivity Analysis is used to efficiently narrow the problem down from multiple uncertain parameters to one parameter which has the largest influence on the solution. In Step...

A Monomial Chaos Approach for Efficient Uncertainty Quantification in Computational Fluid Dynamics

A monomial chaos approach is proposed for efficient uncertainty quantification in nonlinear computational problems. Propagating uncertainty through nonlinear equations can still be computationally intensive for existing uncertainty quantification methods. It usually results in a set of nonlinear equations which can be coupled. The proposed...

Reliable Computational Predictions by Modeling Uncertainties Using Arbitrary Polynomial Chaos

Inherent physical uncertainties can have a significant influence on computational predictions. It is therefore important to take physical uncertainties into account to obtain more reliable computational predictions. The Galerkin polynomial chaos method is a commonly applied uncertainty quantification method. However, the polynomial chaos...