Surrogate models are popular tool to approximate the functional relationship of expensive
simulation models in multiple scientific and engineering disciplines. Successful use of …

In this paper, the uncertainty quantification and sensitivity analysis of a mathematical model
of the SARS-CoV-2 virus transmission dynamics with mass vaccination strategy has been …

In the context of uncertainty analysis, Polynomial chaos expansion (PCE) has been proven
to be a powerful tool for developing meta-models in a wide range of applications, especially …

Developing surrogate models for costly mathematical models representing physical systems
is challenging since it is typically not possible to generate large training data sets, ie to …

Recently, design for additive manufacturing has been proposed to maximize product
performance through the rational and integrated design of the product, its materials, and …

In modern engineering, physical processes are modelled and analysed using advanced
computer simulations, such as finite element models. Furthermore, concepts of reliability …

The probability-based robust optimization methods require a large amount of sample data to
build probability distribution models of uncertain parameters. However, it is a common …

A dynamical system is an information processing apparatus that encodes input streams from
the external environment to its state and processes them through state transitions. The …

Surrogate modeling techniques such as polynomial chaos expansion (PCE) are widely used
to simulate the behavior of manufactured and physical systems for uncertainty quantification …

The rapidly growing number of objects encircling our planet is an increasing concern.
Collisions between these objects have already occurred and pose a potential threat in the …