Each step of the analytical procedure influences the final results in a significant way. In the majority of cases the analytical procedure encompasses sampling because the analysis of the entire object (material) is usually not possible. Thus it is necessary to include the uncertainty related to sampling procedure in the uncertainty budget calculations. This paper describes two basic ways of estimating the sampling uncertainty,...

There is a high demand for accurate and fast numerical models for dense granular flows found in many industrial applications. Nevertheless, before numerical model can be used its need to be always validated against experimental data. During the validation, it is important to consider how the measurement data sets, as well as the numerical models, are affected by errors and uncertainties. In this study, the uncertainty quantification...

Physical properties and chemical composition of atmospheric aerosols are of extreme importance, in many fields of interest, namely the Environment even with legal implications. Atmospheric sampling poses inherent problems with consequent demands on sampling optimisation, with sampling strategies requiring validation. In this work a study was conducted aiming at validating the collection of atmospheric aerosols in equivalent fractions....

In this work, particulate matter was collected using an active sampling system consisting of a PM10 (<10 μm) inlet coupled to a multifold device containing six channels, connected to a vacuum pump. Each channel was equipped with a filter holder fitted with adequately chosen filters. The system was fixed on a metallic structure, which was placed on the roof of the laboratory building, at the Faculty of Sciences, in Lisbon. Sampling...

Uncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...