This paper gives an overview of recent advances in the field of non-probabilistic uncertainty
quantification. Both techniques for the forward propagation and inverse quantification of …

The structural response field is crucial for understanding mechanical behavior, especially
under uncertain conditions. However, current uncertainty quantification predominantly …

This paper introduces an improved version of a novel inverse approach for the quantification
of multivariate interval uncertainty for high dimensional models under scarce data …

This paper proposes a new non-probabilistic time-dependent reliability model for evaluating
the kinematic reliability of mechanisms when the input uncertainties are characterized by …

Finite element analysis of linear-elastic structures with spatially varying uncertain properties
is addressed within the framework of the interval model of uncertainty. Resorting to a …

Non-probabilistic convex models are powerful tools for structural model updating with
uncertain‑but-bounded parameters. However, existing non-probabilistic model updating …

An interval parameter sensitivity analysis is developed to quantify the impact of simulation
model parameters on the model outputs. This sensitivity analysis contains two main steps …

This study proposes a novel sensitivity index to provide essential insights into numerical
models whose inputs are characterized by intervals. Based on the interval model and its …

One of the key challenges of uncertainty analysis in model updating is the lack of
experimental data. The definition of an appropriate uncertainty quantification metric, which is …

This paper presents a novel methodology for the identification and quantification of spatial
uncertainty, modelled as an interval field. In order to make a realistic assessment of the …