Safety Assessment of Brazilian Concrete Bridges Through Reliability Analysis

Abstract

This paper addresses the need for accurate and objective safety assessments of bridges in Brazil taking into account the increase in traffic load and limited funding for infrastructure. In Brazil, the usual method of ensuring bridge safety involves strengthening based on design codes using deterministic analysis and partial safety factors. This method leads to an increase in the maintenance cost of the bridges. Structural reliability assessment, a higher-tier assessment method, is recommended globally for assessing the safety of existing bridges beyond current deterministic methods. This paper presents a study that evaluates the structural safety of existing road bridges in Brazil using the semi-probabilistic method defined in Brazilian standards and the full probabilistic method. The study selected six case studies of existing reinforced and prestressed concrete bridges to evaluate their structural safety concerning current normative loads. The results suggest that the partial safety factors defined in the Brazilian standards are consistent with international standards. The reliability analysis can guarantee the bridges’ safety, even with increased traffic loads, without additional costs for structural strengthening. Therefore, the paper highlights the importance of promoting reliability analysis in Brazil to ensure the safety of existing bridges and promote cost-effective and objective safety assessments.

Keywords:

• Reliability assessment
• structural safety
• bridge infrastructure
• existing bridges
• partial safety factors
• Brazilian standards
• bridge management

Acknowledgement(s)

The authors would like to thank the Departamento de Infraestrutura de Transportes (DNIT), the Agência Nacional de Transportes Terrestres (ANTT), the Agência de Transporte do Estado de São Paulo (ARTESP), the EcoRodovias group, Rota das Bandeiras, and ViaBahia for providing the data that allowed this work to be carried out.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partly financed by FCT / MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB / 04029/2020, and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE under reference LA/P/0112/2020.

The second author was supported by the doctoral Grant PRT/BD/154332/2023 financed by the Portuguese Foundation for Science and Technology (FCT), and with funds from the European Social Fund (ESF), under MIT Portugal Programme.

The third author acknowledges the funding by FCT through the Scientific Employment Stimulus - 4th Edition.