Non-Probabilistic Modelling and Analysis of Uncertainty
In practical engineering, all structures exhibit physical and geometrical uncertainties in various degrees. These sources of uncertainty are usually modelled by probabilistic or non-probabilistic methods. The most widely used are certainly the probabilistic approaches which treat the uncertain parameters as random variables or random processes (or fields). However, the applicability of these methods is limited by the large amount of information required to determine the probability density function of the uncertain parameters. In most engineering problems, experimental data are often insufficient to justify the assumptions in constructing a probabilistic model which therefore may lead to unreliable results. The increasing popularity of non-probabilistic approaches, such as interval analysis methods and fuzzy set theory, stems from the questionable reliability estimates provided by probabilistic methods when limited information on the uncertain parameters is available.
This mini-symposium aims at providing a forum for researchers, academics and practicing engineers concerned with the analysis of structural systems in presence of non-probabilistic uncertainties.
Contributions addressing the following topics are welcome:
- Interval analysis of structures subjected to deterministic or stochastic excitations;
- Convex models of uncertainties;
- Fuzzy set modelling and analysis of structures;
- Structural reliability in presence of uncertainties;
- Sensitivity analysis;
- Structural Reanalysis.
- Isaac Elishakoff
- Department of Ocean and Mechanical Engineering, Florida Atlantic University, USA.
- Giuseppe Muscolino
- Department of Civil, Information, Building, Environmental Engineering and Applied Mathematics (DICIEAMA), University of Messina,Italy.
- Alba Sofi
- Department of Civil, Energy, Environmental and Materials Engineering (DICEAM), University Mediterranea of Reggio Calabria, Italy.