Human error effect in the robustness of a reinforced concrete bridge

To the bridges failures that have been arising over the years, experts have pointed out as the main cause of failure, human errors, in the design, construction and operation phases. One of the main goals of this paper is the identification of the foremost causes of failure due to human errors in design and construction procedures. Therefore, a bridge failure database that includes several failure cases and a human errors survey will be used to support this line of work. After the identification of some explicit human errors that is believed to be the source of several reinforced concrete bridges failures, a selective analysis using risk indicators, namely, the probability of occurrence and consequence, is performed to choose those that might represent a higher risk for the structural safety. The outcome of five chosen human errors in a specific case study is quantified using a robustness index that will be computed according to the reliability index reduction of the structure due to the damages caused by the human errors, allowing to demonstrate how these errors can have a huge influence in the structural safety. The modelling and the finite element analysis of the structure will be performed using TNO DIANA software, allowing the calculation of the reliability index of the structure damaged by different human errors. Within the COST action TU-1406, the main goal of this work is to give a contribution to the establishment of a roadways bridge quality control plan with higher efficiency in the reduction of bridge failures and their substantial, fatalities and economic loss.This work was partly financed by FEDER funds through the Competitively Factors Operational Programme (COMPETE 2020) and by national funds through the Foundation for Science and Technology (FCT) within the scope of the projects POCI-01-0145-FEDE-007633, iRail-Innovation in Railway Systems and Technologies. This project has received funding from the European Union’s Horizon 2020 research and innovation programmeunder grant agreement No 769255. This document reflects only the views of the author(s). Neither the Innovation and Networks Executive Agency (INEA) nor the European Commission is in any way responsible for any use that may be made of the information it contains