Abstract
Analysis of a structure is a crucial procedure to ensure its reliable design and performance. These analytical procedures are generally performed deterministically. However, the input parameters defining the material and geometric properties possess uncertainties. These uncertainties can arise from various sources including modeling, manufacturing, and construction. The quantification of uncertainties can be based on either probability theories (using random variables) or possibility theories (using interval and fuzzy variables). In this work, several finite-element-based probabilistic and possibilistic methods are discussed and compared. Case studies of structures analyzed using static and dynamic uncertainty using the aforementioned approaches are presented. Moreover, the analysis methods are compared for both sharpness and computational efficiency. The results of those analyses suggest that the incorporation of uncertainty in the analysis procedure provides a higher level of confidence in the analysis results. It is also observed that the choice of the analytical procedure must be based on both the problem complexity as well as the level of available information.
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Data Availability Statement
All data and models generated or used during the study appear in the published article. The analysis code that supports the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors wish to acknowledge to Mr. Hamza Sekkak and Prof. Jamshid Mohammadi for their valuable input for this work.
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Published In
Practice Periodical on Structural Design and Construction
Volume 26 • Issue 2 • May 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Jun 6, 2020
Accepted: Oct 2, 2020
Published online: Dec 21, 2020
Published in print: May 1, 2021
Discussion open until: May 21, 2021
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