In structural engineering, model updating is often used for non-destructive damage
assessment: by calibrating stiffness parameters of finite element models based on …

Computer-aided engineering (CAE) is now an essential instrument that aids in engineering
decision-making. Statistical model calibration and validation has recently drawn great …

This book results from a course developed by the author and reflects both his own and
collaborative research regarding the development and implementation of uncertainty …

Model validation metrics have been developed to provide a quantitative measure that
characterizes the agreement between predictions and observations. In engineering design …

This paper deals with a short overview on stochastic modeling of uncertainties. We introduce
the types of uncertainties, the variability of real systems, the types of probabilistic …

Stochastic Models of Uncertainties in Computational Mechanics: Front Matter Page 1
Lecture Notes in Mechanics 2 Stochastic Models of Uncertainties in Computational …

This paper introduces a procedure to assess the predictive accuracy of stochastic models
subject to model error and sparse data. Model error is introduced as uncertainty on the …

This paper investigates model validation under a variety of different data scenarios and
clarifies how different validation metrics may be appropriate for different scenarios. In the …

This article is concerned with the identification of probabilistic characterizations of random
variables and fields from experimental data. The data used for the identification consist of …

This paper is the second part in a two-part series that examines the role of geometric
imperfections in load–displacement response and collapse behavior of cold-formed steel …