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Robustness has been recognized as interesting research topic due to several collapses that have been occurring over last years. Indeed, this subject is related with global failure or collapse. However, its definition is not consensual since several definitions have been proposed in the literature. This shortpaper aims to present a framework for assessing bridge's robustness as a probabilistic performance indicator. In this study, a non-linear model of a clamped beam with two point loads using DIANA software was developed to validate the framework presented. By means of a probabilistic approach, the load carrying capacity and structural safety were evaluated. In this regard, special focus is placed on an adaptive Monte Carlo simulation procedure to achieve a proper meta-model. ; ISISE – Institute for Sustainability and Innovation in Structural Engineering (PEstC/ECI/UI4029/2011 FCOM-01-0124-FEDER-022681) ; FCT– Portuguese Scientific Foundation for the research grant PD/BD/113677/2015 ; European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement No. ...

This work provides an overview of human-made hazards impact on the malfunctioning of terrestrial transportation systems. The impacts evaluation is gathered in four major groups, specifically: human, economic, environmental and political/social impacts. For further characterization or forecast of human-made hazards impact in real case scenarios, a traditional risk assessment framework is proposed by assuming four main steps: i) hazard identification; ii) probability of occurrence; iii) asset vulnerability; iv) impacts. The present work was carried within the SAFEWAY project, which aims at improving the resilience of transport infrastructures, developing a holistic toolset with transversal application to anticipate and mitigate the effects of extreme events at all modes of disaster cycle. ; H2020 -Horizon 2020 Framework Programme(UIDB / ...

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. ...

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 programme under 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.

Infrastructure healthy enhancement for saving resources in operation procedures is one of the most important objectives for owners on their decision support system based on cost management. In this manner, finding the intervention action priority, as well as the inspection method and maintenance system for each component, with regard to a limited resources amount is investigated in this paper. Defects on infrastructure components create data and these data are undoubtedly useful to increase the knowledge in decision making in practice. In that sense, risk analysis and value of information can be applied using decision trees together with Bayesian networks. For data filtering and noise reduction, a principal component analysis may also be applied to manage a database and prepare useful input variables for the decision tree system. This paper presented an approach for the maintenance managers to prepare their infrastructure available with a sustainable index with minimum cost. This index would be a tool for decision-makers with regard to the cost management and sustainability aspects. ; 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. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement ...

Natural disasters are unavoidable and can cause serious damage to bridges, which may lead to catastrophic losses, both human and economic. Therefore, the assessment of bridges exposed to these events is of paramount importance to identify possible mitigation needs. The objective of the present work is to present consistent tools that may allow us to obtain the failure probability of a masonry arch bridge under a flood event, leading to local scour. Surrogate models were implemented to ease the computational cost of the probabilistic analysis. Moreover, a stochastic parametric analysis based on the geotechnical properties of the soil components of masonry arch bridges located in Portugal was performed. The results show the failure mechanism of the masonry arch bridges when subjected to scour-induced settlements and the influence of soil density on the failure probability obtained for different flow discharge values and angles of attack. The presented methodology and derived fragility curves can be used to assess bridge performance under a flood event, thus providing useful information for bridge management and monitoring. ; This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Engineering Structures (ISISE), under reference UIDB/04029/2020. The second author would like to thank FCT—Portuguese Scientific Foundation—for research grant SFRH/BD/144749/2019. This project has received funding from the European Union's Horizon 2020 research and innovation programmed under 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 ...

In the context of bridge management, three main types of maintenance actions can be considered. Maintenance actions can be taken preventively before the predefined limit condition is reached, or as a corrective measure in case those limits have been reached. The third possibility corresponds to the so-called "doing nothing" scenario, in which no action is taken on the bridge. To be able to implement preventive maintenance, it is necessary to know the current condition of the bridge, as well as to be able to predict its performance. On the other hand, it is also important to be able to identify potentially threatening events that might occur in the analysis life period. This paper describes an integrated methodology to help bridge managers in defining an efficient maintenance program, considering the specific case of a railway bridge. The novelty of the methodology is focused on updating an existing methodology proposed by COST TU1406, by extending it to railway bridges and also by including the resilience analysis in case of a sudden event occurrence. The analysis considers a multi-hazard future scenario, in which a flood event occurs while corrosion phenomena were already in place. The results show the feasibility of the proposed methodology as a support for the establishment of an efficient maintenance schedule to prevent bridge severe degradation, as well as to establish recovery plans in case of a sudden event. ; 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), reference no. UIDB/04029/2020; HYPER FCT–Por tuguese Scientific Foundation, research grant no. PD/BD/ 128015/2016, under the Ph.D. program "Innovation in Railway System and Technologies-iRail" of the author João N.D. Fernandes; and European Union's Horizon 2020 re search and innovation programme, grant agreement no. 769255. ,e authors would like to thank the Portuguese company "Infraestruturas de Portugal (IP)" for providing ...

The accuracy of forecasting models for the prediction of an infrastructure's deterioration process plays a significant role in the estimation of optimal maintenance, rehabilitation, and replacement strategies. Numerous approaches have been developed to overcome the limitations of existing forecasting models. In this article, a direct comparison is made between different models using the same input data to derive conclusions of their distinct performance. The models selected for the comparison were Markov, semi-Markov, and hidden Markov models together with artificial neural networks (ANNs), which have been reported in literature as reliable deterioration prediction models. A quality of fit was performed to measure how well the observed data corresponded to the predicted values, and therefore objectively compare the performance of each model. The results demonstrated that the most accurate prediction was accomplished by the ANN model. Nevertheless, all models presented differences with respect to typical values of concrete decks life expectancy, which is attributed to the inherent difficulties of the database. Additionally, the problem of the visual inspection subjectivity was also regarded as one of the potential causes for the found deviations. Therefore, this article also discusses the shortcomings of current condition assessment practices and encourages future bridge management systems to replace the classical methods by more sophisticated and objective tools. ; The first, third and fourth authors also acknowledge that, this work was partly 574 financed by FEDER funds through the Competitivity Factors Operational 575 Programme - COMPETE and by national funds through FCT Foundation for 576 Science and Technology within the scope of the project POCI-01-0145-FEDER- 577 007633. This project has received funding from the European Union's Horizon 578 2020 research and innovation programme under grant agreement No 769255. This 579 document reflects only the views of the author(s). Neither the Innovation and 580 ...

As bridges provide crossing at critical points such as waterways, valleys and other type of physical obstacles, they are invaluable assets within a rail network. However, these infrastructures are exposed to several hazards of different natures that compromise their structural safety and ultimately lead to critical events. Accord-ing to literature, there are commonly five levels of assessment of safety with increasing complexity per level. Level 1, consisting on an assessment based on partial coefficients, is the simplest one, whereas level 5 is the most complex involving a combination of non-linear analysis and probabilistic assessment. Within that scope, this paper analyses the structural safety of a pre-stressed reinforced concrete railway bridge located in Portugal, by using a combination of linear elastic and probabilistic analysis procedures. The proposed framework is adaptable and suitable for common safety analysis. The obtained reliability index is compared to threshold values given by different standards which validates that the bridge ensures the safety at ultimate limit state. The reliability levels along time are also determined assuming a reduction in the cross-section area of the steel reinforcement, resulting from corro-sion initiation based on onsite inspection evidences. From the analysis of this scenario over time, it may be concluded that the bridge under study exhibits sufficient load carrying capacity during its planned service life even under the proposed damage. ; The third author would like to thank FCT – Portuguese Scientific Foundation for the research grant PD/BD/128015/2016 under the PhD program "Innovation in Railway System and Technologies- iRail". This work was partly financed by FEDER funds through the Competitivity Factors Operational Programme - COMPETE and by national funds through FCT Foundation for Science and Technology within the scope of the project POCI-01- 0145-FEDER-007633. This project has received funding from the European Union's Horizon 2020 research and innovation ...

Bridges have substantial significance within the transport system, considering that their functionality is essential for countries' social and economic development. Accordingly, a superior level of safety and serviceability must be reached to ensure the operating status of the bridge network. On that account, the recent collapses of road bridges have led the technical–scientific community and society to reflect on the effectiveness of their management. Bridges in a network are likely to share coinciding environmental conditions but may be subjected to distinct structural deterioration processes over time depending on their age, location, structural type, and other aspects. This variation is usually not considered in the bridge management predictions. For instance, the Brazilian standards consider a constant inspection periodicity, regardless of the bridges' singularities. Consequently, it is helpful to pinpoint and split the bridge network into classes sharing equivalent deterioration trends to obtain a more precise prediction and improve the frequency of inspections. This work presents a representative database of the Brazilian bridge network, including the most relevant data obtained from inspections. The database was used to calibrate two independent predictive models (Markov and artificial neural network). The calibrated model was employed to simulate different scenarios, resulting in significant insights to improve the inspection periodicity. As a result, the bridge's location accounting for the differentiation of exposure was a critical point when analyzing the bridge deterioration process. Finally, the degradation models developed following the proposed procedure deliver a more reliable forecast when compared to a single degradation model without parameter analysis. These more reliable models may assist the decision process of the bridge management system (BMS). ; : This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 769255. ...

Risk management plays a crucial role in the stakeholders' decision making because it is directly related to safety, serviceability and economy. There is now a growing concern about how to relocate known risks into an acceptance threshold: this implies the evaluation of several options obtained from hazard scenarios considering the related consequences. In parallel, practitioners usually rely on standard tools for risk assessment, and on structural codes to compute performances. Although this approach is currently widely implemented, this research shows that hazardous situations can arise in properly designed infrastructures, due to errors in management. This paper deals with such issue, also highlighting a gap in current codes that could contribute to losses caused by unforeseen failure modes. In this study, a preliminary FMEA assessment was performed to identify the failure modes that required a deeper quantitative analysis. In a second step, a quantitative analysis was implemented, using a modular methodology that combines reliability theory with a risk-based approach. The results evidenced that a wider analysis focused on the identification of vulnerable areas shall be considered in every stage of the asset management. Furthermore, the dynamic of this process is regulated by the established safety level concerning possible damages to people, production sites and commercial activities. ; This work was partly financed by FEDER funds through the Competitivity Factors Operational Programme - COMPETE and by national funds through FCT Foundation for Science and Technology within the scope of the project POCI01-0145-FEDER-007633. This work was supported by the FCT Foundation for Science and Technology under Grant SFRH/BD/145478/2019. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No ...