The consideration of imprecise probability in engineering analysis to account for missing,
vague or incomplete data in the description of model uncertainties is a fast-growing field of …

A probabilistic approach to phase-field brittle and ductile fracture with random material and
geometric properties is proposed within this work. In the macroscopic failure mechanics …

Non‐deterministic approaches that enable uncertainty analysis in numerical simulation have
been studied extensively over the past decades. Non‐deterministic models of spatial …

Sophisticated sampling techniques used for solving stochastic partial differential equations
efficiently and robustly are still in a state of development. It is known in the scientific …

The application of isotropic random fields in engineering analysis requires the definition of
their first two central moments, as well as their covariance function. In general, insufficient …

Typically, non-deterministic models of spatial or time dependent uncertainty are modelled
using the well-established random field framework. However, while tailored for exactly these …

Temporally and spatially dependent uncertain parameters are regularly encountered in
engineering applications. Commonly these uncertainties are accounted for using random …

When dealing with modern complex systems, the relationship existing between components
can lead to the appearance of various dependencies between component failures, where …

Imprecise random fields consider both, aleatory and epistemic uncertainties. In this paper,
spatially varying material parameters representing the constitutive parameters of a damage …

Interval fields have been introduced to model spatial uncertainty in Finite Element Models
when the stochastic resolution of available data is too limited to build representative …