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Optimization of framed structures under uncertainties and progressive collapse

Grant number: 19/23531-8
Support Opportunities:Scholarships in Brazil - Doctorate
Start date: July 01, 2020
End date: July 31, 2024
Field of knowledge:Engineering - Civil Engineering - Structural Engineering
Principal Investigator:André Teófilo Beck
Grantee:Lucas da Rosa Ribeiro
Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated scholarship(s):21/12884-7 - Performance-based risk optimization approach for progressive collapse of reincorced cocrete buildings, BE.EP.DR

Abstract

Currently, the usual project design is made member by member and in a semi probabilistic way, using partial safety factors calibrated to lead to the target reliability. Redundancy, typical of hyperstatic structural systems, is not objectively accounted in the design. However, recent occurrences of partial and global progressive collapse have instigated the designers to consider the systemic behavior more objectively; for example, prescribing the discretionary removal of elements in order to verify redundancy and robustness. The distinct scenarios of loading, as well as the intensity of extraordinary actions that might lead to the loss of a key element, like a pillar, have high level of uncertainty, justifying a probabilistic approach to the problem. From the mathematical formulations point of view, it is noticeable some advance in structural optimization under uncertainties, but little has been done regarding the systemic behavior. Therefore, there is a lack of tools and methods between deterministic studies of the systemic behavior subjected to loss of a critical element, and formulations of structural optimization considering uncertainties and the systemic behavior. This project aims to fill this gap, proposing a probabilistic approach for the structural optimal design considering the progressive collapse and the systemic behavior. The approach is imminently conceptual, besides the use of nonlinear numerical models. The study object are reinforced concrete frames, but this study also has relevance for other materials and civil infrastructure in general. (AU)

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