Issue |
Mechanics & Industry
Volume 16, Number 1, 2015
|
|
---|---|---|
Article Number | 104 | |
Number of page(s) | 6 | |
DOI | https://doi.org/10.1051/meca/2014065 | |
Published online | 16 September 2014 |
Quantification of structural robustness: application to the study of a prestressed concrete beam
1 University Paris-Est, IFSTTAR,
Materials and Structures Department, Champs-sur-Marne, France
2 CEREMA/DTecITM, Technical center for
Bridge Engineering, Sourdun, France
3 CEREMA/DTerNP, Bridge
Division, Haubourdin,
France
a Corresponding author:
andre.orcesi@ifsttar.fr
Received:
26
June
2013
Accepted:
5
July
2014
The term of “structural robustness” gives rise to various definitions and applications. In particular, the European structural standards Eurocodes recommend a structural design to be sufficiently safe against accidental or abnormal loads not explicitly considered in the design. This paper presents a probabilistic approach for the quantification of structural robustness, which measures the impact of a localized failure on the global structural failure. In order to identify the probabilistically most dominant failure mechanisms starting from a local failure, failure tree methods are used, such as the branch and bound method, the β-unzipping method, and an original approach combining the concepts of β unzipping with some bounding aspects. These methods are used to identify dominant failure paths within reasonable computational times. In particular, it is possible to determine the failure path associated with the largest probability of failure, also called the reference path. Considering this reference path, some robustness metrics are proposed to quantify the relative magnitude (expressed in probabilities or in risk measures) between local and global failures. The proposed approach is applied to the structural analysis of a prestressed beam. The results obtained with the three methods as well as the computational times required each time are finally compared.
Key words: Structural robustness / risk / failure / robustness metrics
© AFM, EDP Sciences 2014
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