Probabilistic responses of dynamical systems subjected to gaussian coloured noise excitation: foundations of a non-markovian theory
Abstract
Determining the probabilistic structure of the response to a dynamical system under random excitations is an important question in various problems of stochastic dynamics, advanced statistical physics, material science, medical and environmental sciences, and uncertainty quantification of macroscopic systems. Furthermore, in most real-life applications, random excitations cannot be modelled as white (delta-correlated) noise, see e.g. excitations by sea waves, wind or earthquakes. The topic of this PhD dissertation is the derivation of evolution equations for probability density functions (pdfs) that describe the non-Markovian response to scalar or multidimensional dynamical systems subjected to Gaussian coloured (smoothly-correlated) noise excitation. More specifically, we derive evolution equations for the one-time response pdf, as well as for pdfs of higher order, such as the joint two-time response pdf, and the joint one-time response-excitation pdf. The aforementioned pdf evolution ...
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