Structural Health Monitoring (SHM) is a promising tool for condition assessment of bridge structures. SHM of bridges can be performed for different purposes in long or short-term. A few aspects of short- and long-term monitoring of highway bridges are addressed in this research. Without quantifying environmental effects, applying vibration-based damage detection techniques may result in false damage identification. As part of a long-term monitoring project, the effect of temperature on vibrational characteristics of two continuously monitored bridges are studied. Natural frequencies of the structures are identified from ambient vibration data using the Natural Excitation Technique (NExT) along with the Eigen System Realization (ERA) algorithm. Variability of identified natural frequencies is investigated based on statistical properties of identified frequencies. Different statistical models are tested and the most accurate model is selected to remove the effect of temperature from the identified frequencies. After removing temperature effects, different damage cases are simulated on calibrated finite-element models. Comparing the effect of simulated damages on natural frequencies showed what levels of damage could be detected with this method. Evaluating traffic loads can be helpful to different areas including bridge design and assessment, pavement design and maintenance, fatigue analysis, economic studies and enforcement of legal weight limits. In this study, feasibility of using a single-span bridge as a weigh-in-motion tool to quantify the gross vehicle weights (GVW) of trucks is studied. As part of a short-term monitoring project, this bridge was subjected to four sets of high speed, live-load tests. Measured strain data are used to implement bridge weigh-in-motion (B-WIM) algorithms and calculate the corresponding velocities and GVWs. A comparison is made between calculated and static weights, and furthermore, between supposed speeds and estimated speeds of the trucks. Vibration-based techniques that use finite-element (FE) model updating for SHM of bridges are common for infrastructure applications. This study presents the application of both static and dynamic-based FE model updating of a full scale bridge. Both dynamic and live-load testing were conducted on this bridge and vibration, strain, and deflections were measured at different locations. A FE model is calibrated using different error functions. This model could capture both global and local response of the structure and the performance of the updated model is validated with part of the collected measurements that were not included in the calibration process.

Pour les ouvrages neufs, les modèles de trafic dans les normes ou les législations pour la conception des ponts incluent une marge de sécurité suffisante pour que la croissance du trafic soit prise en compte sans dommage par ces ouvrages. Les fondements et les utilisations faites de ces méthodes pour modéliser les effets extrêmes du trafic sur les ouvrages sont donnés dans un premier chapitre. Différentes méthodes sont ainsi étudiées, telles la méthode des moments (MM), la méthode des moments à poids (PWM), le maximum de vraisemblance (ML), le maximum de vraisemblance pénalisé (PML), le minimum de la densité de la divergence (MDPD), la méthode des fractiles empiriques (EPM), la statistique du maximum d'adaptation et la vraisemblance des moments (LM). Pour comparer ces méthodes, des échantillons numériques, des effets de trafic simulés par Monte Carlo et des effets mesurés sur un ouvrage réel sont utilisés. Pour des effets du trafic simulés, ML et PML donne des valeurs de retour plus correctes lorsque le nombre de valeurs au-dessus du seuil est supérieur à 100 ; Des méthodes permettant de prendre en compte ce point et utilisant des distributions mélangées (exponentielles ou valeurs extrêmes généralisées) ont été proposées dans la littérature pour modéliser les effets du trafic. Pour des ponts ayant des portées supérieures à 50m, le scénario déterminant est celui de la congestion, qui n'est pas ce qui est étudié ici. De plus, le trafic n'est pas la composante déterminante pour la conception des ponts de longue portée. Mais des problèmes de fatigue peuvent apparaître dans certains ponts, tels les ponts métalliques à dalle orthotrope, où l'étude du trafic peut devenir nécessaire. Ainsi nous avons fait une étude de l'influence de la position des véhicules sur le phénomène de fatigue. Pour cela, quatre fichiers de trafic réels, mesurés en 2010 et 2011 par quatre stations de pesage différentes, ont été utilisés. Ils ont mis à jour des comportements latéraux différents d'une station à l'autre. Si nous les appliquons au viaduc de Millau, qui est un pont métallique à haubans et à dalle orthotrope, nous voyons que l'histogramme des effets et l'effet de fatigue cumulé est beaucoup affecté par le comportement latéral des véhicules. Ainsi, des études approfondies utilisant les éléments finis pour modéliser les ouvrages et des enregistrements de trafic réel, peuvent être utilisées pour pré-déterminer quels éléments, donc quelles soudures, doivent être examinés dans les ponts afin d'estimer leur santé structurelle / Traffic load model in standard or specification for bridge design should guarantee all newly designed bridges to have sufficient security margin for future traffic. Many different methods have been used to model extreme traffic load effects on bridges for predicting characteristic value for short or long return period. In order to provide some guidance on selecting parameter estimation when applying POT to bridge traffic loading, we focus on the effect that method used to estimate the parameters of the GPD has on the accuracy of the estimated characteristic values. Through this qualitative discussion on the methods, several available methods for traffic loading are selected. Numerical simulation data, Monte Carlo simulation traffic load effects and in-field traffic load effect measurements are analyzed and presented. Literature points out that the traffic load effect is induced by loading event that involves different number of vehicles, and the distribution of the load effects from different loading events are not identically distributed, which violates the assumption of classic extreme value theory that the underlying distribution should be identically independent distributed. Methods using mixture distribution (exponential or generalized extreme value) has been proposed in the literature to model the extreme traffic load effect by loading event. However, the traffic loading may be also importance if the bridge encounter traffic induced fatigue problem, components like orthotropic steel deck is governed by traffic induced fatigue load effects. We intend to explore the influence of traffic load on the fatigue behaviour of orthotropic steel deck, especially the influence of the loading position in terms of transverse location of vehicle. Measurements of transverse location of vehicle collected from by weigh-in-motion (WIM) systems in 2010 and 2011 four French highways showed a completely different distribution model of transverse location of vehicle to that recommended in EC1. Stress spectrum analysis and fatigue damage calculation was performed on the stresses induced traffic on orthotropic steel deck of Millau cable-stayed bridge. By comparing the stresses and damages induced by different traffic patterns (through distributions of transverse location of vehicle), it was found that the histogram of stress spectrum and cumulative fatigue damage were significantly affected by the distribution of transverse location of vehicle. Therefore, numerical analysis that integrates finite element modelling and traffic data with distributions of transverse location of vehicles can help to make an accurate predetermination of which welded connections should be sampled to represent the health of the deck

This research analyzes fuel consumption and emissions of Turnpike double trailer combinations (Turnpikes) on a regional network in the Canadian Prairies. The research: (1) establishes current benchmarks for fuel consumption of Turnpikes and five-axle tractor semitrailers (3-S2s) with van trailers; (2) develops fuel consumption models for these vehicle types; (3) establishes an understanding of current operating characteristics of Turnpikes in the region; and (4) estimates their system-wide effects in terms of fuel consumption and emissions in Manitoba by applying the developed models. Canadian Prairie region-based carriers revealed an increase in Turnpike travel (from 2007-2009) of 44 percent after the twinning of the Trans-Canada Highway between Winnipeg and Regina in 2007 was completed. Turnpikes can save one third of fuel consumed when compared to 3-S2s; have higher fuel consumption in the winter months; and their use in 2009 reduced fuel consumption and CO2 emissions by five percent compared to 3-S2s.

The field of bridge monitoring is one of rapid development. Advances in sensor technologies, in data communication and processing algorithms all affect the possibilities of Structural Monitoring in Bridges. Bridges are a very critical part of a country’s infrastructure, they are expensive to build and maintain, and many uncertainties surround important factors determining their serviceability and deterioration state. As such, bridges are good candidates for monitoring. Monitoring can extend the service life and avoid or postpone replacement, repair or strengthening works. The amount of resources saved, both to the owner and the users, by reducing the amount of non-operational time can easily justify the extra investment in monitoring. This thesis consists of an extended summary and five appended papers. The thesis presents advances in sensor technology, damage identification algorithms, Bridge Weigh-In-Motion systems, and other techniques used in bridge monitoring. Four case studies are presented. In the first paper, a fully operational Bridge Weigh-In-Motion system is developed and deployed in a steel railway bridge. The gathered data was studied to obtain a characterization of the site specific traffic. In the second paper, the seasonal variability of a ballasted railway bridge is studied and characterized in its natural variability. In the third, the non-linear characteristic of a ballasted railway bridge is studied and described stochastically. In the fourth, a novel damage detection algorithm based in Bridge Weigh-In-Motion data and machine learning algorithms is presented and tested on a numerical experiment. In the fifth, a bridge and traffic monitoring system is implemented in a suspension bridge to study the cause of unexpected wear in the bridge bearings. Some of the major scientific contributions of this work are: 1) the development of a B-WIM for railway traffic capable of estimating the load on individual axles; 2) the characterization of in-situ measured railway traffic in Stockholm, with axle weights and train configuration; 3) the quantification of a hitherto unreported environmental behaviour in ballasted bridges and possible mechanisms for its explanation (this behaviour was shown to be of great importance for monitoring of bridges located in colder climate) 4) the statistical quantification of the nonlinearities of a railway bridge and its yearly variations and 5) the integration of B-WIM data into damage detection techniques. / <p>QC 20140910</p>

This research analyzes fuel consumption and emissions of Turnpike double trailer combinations (Turnpikes) on a regional network in the Canadian Prairies. The research: (1) establishes current benchmarks for fuel consumption of Turnpikes and five-axle tractor semitrailers (3-S2s) with van trailers; (2) develops fuel consumption models for these vehicle types; (3) establishes an understanding of current operating characteristics of Turnpikes in the region; and (4) estimates their system-wide effects in terms of fuel consumption and emissions in Manitoba by applying the developed models. Canadian Prairie region-based carriers revealed an increase in Turnpike travel (from 2007-2009) of 44 percent after the twinning of the Trans-Canada Highway between Winnipeg and Regina in 2007 was completed. Turnpikes can save one third of fuel consumed when compared to 3-S2s; have higher fuel consumption in the winter months; and their use in 2009 reduced fuel consumption and CO2 emissions by five percent compared to 3-S2s.

Cette thèse de doctorat porte sur l'étude et la réalisation d'une plateforme de pesage dynamique pour véhicule roulant basée sur un concept d'intégration de la charge. Ce concept est mis en œuvre en vue de pouvoir minimiser la taille et l'encombrement de ce type de dispositif tout en effectuant des pesées présentant des caractéristiques métrologiques acceptables. Nous démontrons tout d'abord au travers de la réalisation d'un prototype et de plusieurs campagnes d'essais, la faisabilité de la méthode utilisée. Nous évaluons dans un deuxième temps les performances présentées par le prototype lors du pesage de véhicules légers roulant jusqu'à des vitesses de 35km/h. Une étude est ensuite menée sur les jauges de déformation piézorésistives et les jauges piézoélectriques réalisées en couches épaisses grâce à des techniques de sérigraphie. Nous caractérisons ces transducteurs avec pour objectif leur utilisation dans des dispositifs de pesage en remplacement des jauges de déformation classiques à filaments métalliques. / This PhD thesis is devoted to the study and implementation of a weigh-in-motion platform for vehicle based on a concept of integration of load. This concept is used to minimize the size of this kind of device while performing weighings with acceptable results. First, we show thanks to a protoype and several test campagns, the feasability of the method used. In a second time, we evaluate the performances of the prototype in terms of precision and repeatability with the dynamic weighing of vehicles at speeds up to 35km/h. A study is finally conducted on thick-film piezoresitive strain gauges and piezoelectric gauges manufacturing by a screen-printing process with cermet and polymer pastes. We characterize these tranducers with the goal of used them as an alternative of conventional foil strain gauges.

The field of monitoring is one of rapid development. Advances in sensor technologies, in data communication paradigms and data processing algorithms all influence the possibilities of Structural Health Monitoring, damage detection, traffic monitoring and other implementations of monitoring systems. Bridges are a very critical part of a country’s infrastructure, they are expensive to build and maintain, and many uncertainties surround important factors determining the serviceability and deterioration of bridges. As such, bridges are good candidates for monitoring. Monitoring can extend the service life and avoid or postpone replacement, repair or strengthening work. Many bridges constitute a bottleneck in the transport network they serve with few or no alternative routes. The amount of resources saved, both to the owner and the users, by reducing the amount of non-operational time can easily justify the extra investment in monitoring. This thesis consists of an extended summary and three appended papers. The thesis presents advances in sensor technology, damage identification algorithms and Bridge Weigh-In-Motion techniques. Two case studies are carried out. In the first a bridge and traffic monitoring system is implemented in a highway suspension bridge to study the cause of unexpected wear in the bridge bearings. In the second a fully operational Bridge Weigh-In-Motion system is developed and deployed in a steel railway bridge. The gathered data was studied to obtain a characterization of the site specific traffic. / QC 20111122

Submitted by Edisangela Bastos (edisangela@ufpa.br) on 2015-01-27T18:33:19Z No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) / Rejected by Edisangela Bastos (edisangela@ufpa.br), reason: on 2015-01-29T18:13:44Z (GMT) / Submitted by Edisangela Bastos (edisangela@ufpa.br) on 2015-01-30T17:50:00Z No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) / Approved for entry into archive by Albirene Aires (albireneufpa@gmail.com) on 2015-02-02T12:06:43Z (GMT) No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) / Made available in DSpace on 2015-02-02T12:06:43Z (GMT). No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) Previous issue date: 2014 / Nesta dissertação é apresentado o desenvolvimento de algoritmos para aplicação do método Bridge-Weigh In Motion (B-WIM) para a pesagem em movimento de trens e para a caracterização do tráfego ferroviário, permitindo-se obter informações sobre a velocidade de passagem dos trens, número e espaçamento entre eixos. Os sistemas B-WIM a partir de uma simples instrumentação permitem determinar as cargas por eixo de veículos em movimento, eliminando o efeito dinâmico. Foram implementados os algoritmos para a determinação dos valores referentes a geometria do trem e das cargas, que foi validado a partir de um exemplo teórico, onde se simulou a passagem de um trem de características conhecidas sobre a ponte e as cargas por eixos foram determinadas com 100% de exatidão. Além disso, foi feito um exemplo numérico em elementos finitos, de um viaduto em concreto armado para aplicação do método, onde foi feita a determinação das cargas por eixo para diferentes velocidades de passagem do trem. A fim de reduzir o tempo de processamento nas análises do exemplo numérico, foi desenvolvido um algoritmo para a geração de cargas nodais no modelo numérico que reduziram o tempo de processamento em até 96% quando comparado com a análise de múltiplos passos (“Multi-Step”), que simula automaticamente a passagem do trem sobre a estrutura. Finalmente, o método foi testado em um caso real a partir de monitorações realizadas em um viaduto de concreto armado da Estrada de Ferro Carajás. Apesar de não ter sido possível a determinação das cargas por eixo da locomotiva, foi possível medir precisamente o peso bruto total da locomotiva quando se utilizou o modelo constitutivo de Collins & Mitchell (1991) para o concreto. / This Master’s Thesis presents the development of algorithms for application of Bridge- Weigh In Motion (B-WIM) for weighing moving trains and method for the characterization of rail traffic, allowing up to obtain information about the speed of passage of trains , number and axle spacing. The B-WIM systems from a simple instrumentation for determining the axle loads of moving vehicles, eliminating the dynamic effect. The algorithms for determining the values related the geometry of the train and axle loads were implemented, which was validated from a theoretical example, where we simulated the passage of a train of known characteristics over the bridge and axle loads were determined 100% accuracy. In addition, a numerical example was done in finite element method, of a reinforced concrete viaduct for application of the method, where was determine axle loads for different speeds of train passage. In order to reduce the processing time of the analysis in the numerical example, an algorithm for generating the numerical model nodal loads was implemented that have reduced processing time by 96% compared to the analysis of multi-step, which automatically simulates the passage of the train over the structure. Finally, the method was tested on a real case from monitoring tests realized on a reinforced concrete viaduct in the Carajás Railroad. Although it was not possible to determine the axle load locomotive, it was possible to measure accurately the gross weight of the locomotive when using the constitutive model of Collins and Mitchell (1991) for concrete.

The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.

The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.