Robust, Performance-Based and Reliability-Based Structural Optimization Under Uncertainty
Structural design should be robust with respect to uncertainties inherently present in resistance of structural materials, environmental and man-imposed loads, boundary conditions, physical, mathematical and numerical models, and to other types of intrinsic and epistemic uncertainties. Structural performance and reliability should be only marginally affected by future fluctuations or changes in problem parameters. Proper decision making in presence of uncertainties is fundamental to avoid severe or fatal consequences and/or costly posteriori changes to design. These observations have led to the recent development of different approaches to structural optimization: robust, fuzzy, performance-based, reliability-based and risk-based optimizations.
This mini-symposium aims at bringing together researchers, academics and practicing engineers concerned with the various forms of structural optimization in presence of uncertainties. Contributions addressing both theoretical developments and practical applications, in the following topics, are invited:
- Robust structural optimization;
- Performance-based optimization;
- Reliability-based structural optimization: stationary and dynamic problems;
- Risk management and optimization;
- Modeling of extreme or rare events;
- Decision-making in presence of uncertainties;
- Modeling of uncertainty with probability theory, Bayesian theory, imprecise probabilities including evidence theory, interval models, fuzzy set theory, information gap theory, etc.
- Structural health monitoring, system identification, and damage detection.
- Héctor A. Jensen
- Dept. of Civil Engineering, University Federico Santa Maria.
- André T. Beck
- Department of Structural Engineering, São Carlos School of Engineering, University of São Paulo.
- Kurt Marti
- Institut for Mathematics and Computer Sciences, Federal Armed Forces University Munich.
- Michael Beer
- Centre for Engineering Sustainability, School of Engineering, University of Liverpool.