Avaliação da vulnerabilidade sísmica de pontes rodoviárias existentes de betão armado no Irão

Doutoramento em Engenharia CivilSismos recentes mostram que as pontes são uma das infraestruturas mais vulneráveis dos sistemas de transporte rodoviário, e comprovam a necessidade de avaliação da vulnerabilidade deste tipo de estruturas, especialmente as projetadas segundo a filosofia patente nos códigos antigos. A avaliação da vulnerabilidade sísmica das pontes rodoviárias localizadas em áreas de elevada perigosidade sísmica e a estimativa do seu desempenho sísmico representam tarefas importantes para a segurança dos sistemas de transporte. Neste contexto, esta investigação tem como objetivo estudar a vulnerabilidade sísmica das pontes de betão armado existentes no Irão. O trabalho foca-se principalmente nas seguintes tarefas: desenvolvimento de análises estatísticas, classificação das pontes mais comuns no Irão, seleção da ação sísmica representativa, definição de estados de dano, estudo dos efeitos das práticas de construção e, finalmente, análise de curvas de fragilidade para avaliar a vulnerabilidade sísmica de pontes tipo representativas das obras existentes no Irão. O primeiro capítulo resume trabalhos no domínio da caracterização da sismicidade na área geográfica em estudo, em função das diferentes placas tectónicas e da distribuição das zonas de rotura prováveis, com base em informação recolhida em sismos passados e uma revisão geral dos estudos anteriores e a pesquisa bibliográfica, nomeadamente em termos de curvas de fragilidade para as pontes com base em diferentes abordagens. O Capítulo 2 descreve os tipos de ponte mais comuns existentes no Irão e classifica-as de acordo com as suas características estruturais primárias. Capítulo 3 explicar os modelos analíticos não lineares 3-D das estruturas de pontes amostra usando modelos analíticos detalhados para os seus componentes. O Capítulo 4 é dedicado à seleção de um conjunto de registos sísmicos reais que sejam representativos das diferentes fontes sísmicas. O Capítulo 5 é dedicado à definição de estados limite de dano. Neste capítulo, foi realizada uma revisão das propostas para a avaliação dos estados limite de dano disponíveis na literatura. Para isso, diferentes tipos de incertezas associadas a parâmetros que influenciam o comportamento das pontes foram consideradas, nomeadamente em termos de seção e altura dos pilares, presença da emenda da armadura longitudinal e vão. Além disso, a influência das propriedades dos materiais com base na resistência à compressão do betão e da resistência do aço são analisadas e os resultados são tratados em termos de curvas de fragilidade para cada classe de pontes considerada. O Capítulo 6 apresenta os principais resultados da análise sísmica tridimensional realizada sobre vários casos de estudo. Capítulos 7 indicam o estudo da resposta estocástica de pontes de betão considerando a incerteza na rigidez de rolamento e de encosto. Finalmente, no capítulo 8, as principais conclusões são tiradas a partir do trabalho desenvolvido no âmbito do presente estudo.Past earthquakes occurred in seismically active areas around the world show that bridges are one of the most vulnerable components of the highway transportation systems, and evidence the need to study the vulnerability of bridges, especially the ones designed with the old codes. Thus, the seismic vulnerability assessment of the highway bridges located in high seismic hazard areas and the assessment of the bridges’ performance under seismic demands play an important role for the safety of transportation systems. In this context, this research aimed to study the seismic vulnerability of existing old concrete bridges in Iran. The research work was mainly focused on the following tasks: identification of the most common bridges in Iran, ground motion selection, damage state definition, real construction practices and finally the analysis of fragility curves to assess the seismic vulnerability of common bridges in Iran. The first chapter presents the study of seismicity in a geographical area of interest for this study, covered by different tectonic plates and distribution of probable rupture zones of past earthquakes and the general overview of previous studies and a literature survey developed to generate the bridge fragility curves based on different approaches. Chapter 2 describes the most common existing ordinary highway bridges and classifies them according to their primary structural characteristics. Chapter 3 explains the 3-D nonlinear analytical models of the sample bridge structures using detailed analytical models for its components. Chapter 4 is devoted to the procedure followed in the selection of earthquake ground motion records that are representative of the different seismic sources, based on ground motion intensity. Chapter 5 addresses aspects related with the definition of damage limit states. In this chapter, a review of the damage states definitions and strategies available in the literature is also made. For this, different types of bridges uncertainties, in terms of column height, superstructure type, lap splice and span length are investigated for the selected case studies. Also, the influence of material properties, namely the compressive strength of concrete and the yield strength of steel is described. In Chapter 6 the results are generated in terms of fragility curves for each bridges class. Chapter 7 indicates the study of the stochastic response of concrete bridges considering the uncertainty in the bearing and abutment stiffness. Finally in chapter 8, the main conclusions are drawn from the work developed within the present study

Development of fragility curves for RC bridges subjected to reverse and strike-slip seismic sources

. This paper presents a probabilistic fragility analysis for two groups of bridges: simply supportedand integral bridges. Comparisons are based on the seismic fragility of the bridges subjected toaccelerograms of two seismic sources. Three-dimensional finite-element models of the bridges were createdfor each set of bridge samples, considering the nonlinear behaviour of critical bridge components. When theseismic hazard in the site is controlled by a few seismic sources, it is important to quantify separately thecontribution of each fault to the structure vulnerability. In this study, seismic records come from earthquakesthat originated in strike-slip and reverse faulting mechanisms. The influence of the earthquake mechanismon the seismic vulnerability of the bridges was analysed by considering the displacement ductility of thepiers. An in-depth parametric study was conducted to evaluate the sensitivity of the bridges' seismicresponses to variations of structural parameters. The analysis showed that uncertainties related to thepresence of lap splices in columns and superstructure type in terms of integral or simply supported spansshould be considered in the fragility analysis of the bridge system. Finally, the fragility curves determine theconditional probabilities that a specific structural demand will reach or exceed the structural capacity byconsidering peak ground acceleration (PGA) and acceleration spectrum intensity (ASI). The results alsoshow that the simply supported bridges perform consistently better from a seismic perspective than integralbridges and focal mechanism of the earthquakes plays an important role in the seismic fragility analysis ofhighway bridges

Advanced Railway Infrastructures Engineering

The European Commission is developing a Single European Transport Area and has promoted a modal shift from road to rail to achieve a more competitive and resource-efficient transport system [...

Railway Vehicle Wheel Flat Detection with Multiple Records Using Spectral Kurtosis Analysis

The gradual deterioration of train wheels can increase the risk of failure and lead to a higher rate of track deterioration, resulting in less reliable railway systems with higher maintenance costs. Early detection of potential wheel damages allows railway infrastructure managers to control railway operators, leading to lower infrastructure maintenance costs. This study focuses on identifying the type of sensors that can be adopted in a wayside monitoring system for wheel flat detection, as well as their optimal position. The study relies on a 3D numerical simulation of the train-track dynamic response to the presence of wheel flats. The shear and acceleration measurement points were defined in order to examine the sensitivity of the layout schemes not only to the type of sensors (strain gauge and accelerometer) but also to the position where they are installed. By considering the shear and accelerations evaluated in 19 positions of the track as inputs, the wheel flat was identified by the envelope spectrum approach using spectral kurtosis analysis. The influence of the type of sensors and their location on the accuracy of the wheel flat detection system is analyzed. Two types of trains were considered, namely the Alfa Pendular passenger vehicle and a freight wagon

Development and Validation of a Weigh-in-Motion Methodology for Railway Tracks

In railways, weigh-in-motion (WIM) systems are composed of a series of sensors designed to capture and record the dynamic vertical forces applied by the passing train over the rail. From these forces, with specific algorithms, it is possible to estimate axle weights, wagon weights, the total train weight, vehicle speed, etc. Infrastructure managers have a particular interest in identifying these parameters for comparing real weights with permissible limits to warn when the train is overloaded. WIM is also particularly important for controlling non-uniform axle loads since it may damage the infrastructure and increase the risk of derailment. Hence, the real-time assessment of the axle loads of railway vehicles is of great interest for the protection of railways, planning track maintenance actions and for safety during the train operation. Although weigh-in-motion systems are used for the purpose of assessing the static loads enforced by the train onto the infrastructure, the present study proposes a new approach to deal with the issue. In this paper, a WIM algorithm developed for ballasted tracks is proposed and validated with synthetic data from trains that run in the Portuguese railway network. The proposed methodology to estimate the wheel static load is successfully accomplished, as the load falls within the confidence interval. This study constitutes a step forward in the development of WIM systems capable of estimating the weight of the train in motion. From the results, the algorithm is validated, demonstrating its potential for real-world application

Probabilistic Seismic Safety Assessment of Railway Embankments

The purpose of this research is to study the seismic performance of railway embankments through a probabilistic approach. Nonlinear response history analyses were conducted utilizing PLAXIS software. Three categories of railway embankments were selected and more than 2400 embankment-earthquake case studies were performed. Sensitivity analyses were implemented to obtain the most important variables in the seismic performance of railway embankments. Finally, analytical fragility curves were generated in terms of the mechanical properties of railway embankments (e.g., soil cohesion and friction angle). Fragility functions were developed, employing an incremental dynamic analysis approach using a set of ground motions, including near- and far-field earthquakes. The maximum vertical displacement of the embankment was chosen as a damage index parameter. Fragility curves were derived for three damage states, including slight, moderate and extensive damage, with respect to threshold values proposed in the literature. The results of this study revealed that the mechanical properties of embankments could be considered one of the crucial uncertainty factors in seismic fragility analysis of railway embankments

An Unsupervised Learning Approach for Wayside Train Wheel Flat Detection

One of the most common types of wheel damage is flats which can cause high maintenance costs and enhance the probability of failure and damage to the track components. This study aims to compare the performance of four feature extraction methods, namely, auto-regressive (AR), auto-regressive exogenous (ARX), principal component analysis (PCA), and continuous wavelet transform (CWT) capable of automatically distinguishing a defective wheel from a healthy one. The rail acceleration for the passage of freight vehicles is used as a reference measurement to perform this study which comprises four steps: (i) feature extraction from acquired responses using the specific feature extraction methods; (ii) feature normalization based on a latent variable method; (iii) data fusion to enhance the sensitivity to recognize defective wheels; and (iv) damage detection by performing an outlier analysis. The results of this research show that AR and ARX extraction methods are more efficient techniques than CWT and PCA for wheel flat damage detection. Furthermore, in almost every feature, a single sensor on the rail is sufficient to identify a defective wheel. Additionally, AR and ARX methods demonstrated the potential to distinguish a defective wheel on the left and right sides. Lastly, the ARX method demonstrated robustness to detect the wheel flat with accelerometers placed only in the sleepers

An Unsupervised Learning Approach for Wayside Train Wheel Flat Detection

One of the most common types of wheel damage is flats which can cause high maintenance costs and enhance the probability of failure and damage to the track components. This study aims to compare the performance of four feature extraction methods, namely, auto-regressive (AR), auto-regressive exogenous (ARX), principal component analysis (PCA), and continuous wavelet transform (CWT) capable of automatically distinguishing a defective wheel from a healthy one. The rail acceleration for the passage of freight vehicles is used as a reference measurement to perform this study which comprises four steps: (i) feature extraction from acquired responses using the specific feature extraction methods; (ii) feature normalization based on a latent variable method; (iii) data fusion to enhance the sensitivity to recognize defective wheels; and (iv) damage detection by performing an outlier analysis. The results of this research show that AR and ARX extraction methods are more efficient techniques than CWT and PCA for wheel flat damage detection. Furthermore, in almost every feature, a single sensor on the rail is sufficient to identify a defective wheel. Additionally, AR and ARX methods demonstrated the potential to distinguish a defective wheel on the left and right sides. Lastly, the ARX method demonstrated robustness to detect the wheel flat with accelerometers placed only in the sleepers

Advanced Railway Infrastructures Engineering

Electronic Instrumentatio