Research Publications

 

All titles published by the School are listed in the yearly President's reports classified by type of publication and author and can be downloaded for each academic season from the links in the right hand side menu. 

Full text for some of these titles are available in the Open Access Institutional Repository of UCD Research. The top 10 downloads from the School repository are listed in the right hand side menu and can be accessed by clicking each title. The most recent uploads to the repository can be accessed in the list below. Following this list, an archive of news involving publications by the School is provided.

The effect of controlling heavy vehicle gaps on long-span bridge loading

The effect of controlling heavy vehicle gaps on long-span bridge loading Caprani, Colin C.; O'Brien, Eugene J.; Lipari, Alessandro Long-span road bridges are governed by congested traffic rather than free-flowing conditions. During congestions, heavy vehicles can get quite close to each other, thus giving potential critical loading events for the bridge. In this paper, the effects of a system capable of warning truck drivers when the gap falls below a certain threshold are investigated. The effects are studied both in terms of increase in traffic disruption and reduction in loading. The minimum distance between trucks should be ideally adjusted in relation to the site-specific traffic features and to the load the bridge is able to carry in safety. Doing so, it is possible to allow for future increase in truck weight regulations and/or heavy traffic volumes, by adjusting the control gap value. Importantly, the system does not presume any restriction to the truck weight. By contrast, the system is meant to be an alternative way of limiting the load on long-span bridges by keeping the trucks apart, rather than by limiting the truck weight. The introduction of such a gap control system is studied by means of micro-simulation. The car-following model used here has been shown able to replicate many observed congestion patterns. Results show that the introduction of the gap control system does not significantly disrupt the traffic further. On the other hand, having only 10% of equipped trucks beneficially reduces the total traffic loading by about 10%. When most trucks are equipped, nearly 50% reduction in the total load can be attained. Transport Research Board Annual Meeting, January 2013
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Bayesian updating of bridge safety model

Bayesian updating of bridge safety model Heitner, Barbara; O'Brien, Eugene J.; Schoefs, Franck; et al. This paper investigates the sensitivities of and correlation between the different parameters influencing the load on a bridge and its resistance to that load. The actual safety, i.e. the probability of failure, is calculated by combining the load and resistance models. The usefulness of updating the developed bridge safety model using damage indicators from a Structural Health Monitoring system is also examined. Civil Engineering Research in Ireland 2016, Galway, Ireland, 29-30 August 2016
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Application of Image Processing to the Analysis of Congested Traffic

Application of Image Processing to the Analysis of Congested Traffic Micu, E. Alexandra; O'Brien, Eugene J.; Sevillano, Enrique Traffic congestion has become a significant problem in all developed countries. This is mainly due to the increasing number of vehicles but also to the fact that the infrastructures are usually not designed to take over all this traffic. As a result of this increasing number of vehicles on the roads, bridges are becoming serious strangulation points in the transport system. This issue is more important because most of bridges are either approaching or have surpassed their expected design life and traffic data traditionally collected with inductive loops detectors do not provide information about congested traffic situation. Due to this drawback, it needs a better solution for traffic monitoring. The aim of this paper is to explore the capabilities of using images for applications on transport, especially for traffic monitoring, to extract information about traffic such as gaps between cars, cars and trucks, or trucks. In that sense, a high resolution camera will be used in this work in order to capture aerial images of congested traffic. These images will be processed to distinguish all vehicles as different objects on the road, to identify the type of vehicles (regular cars or trucks) and to measure the length for each vehicle. In order to achieve that result, an algorithm able to detect and count the vehicles on the road as separated objects will be firstly applied, enclosing each object within a rectangle. Civil Engineering Research in Ireland 2016, Galway, Ireland, 29-30 August, 2016
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The influence of speed on the dynamic amplification of two loads crossing a simply supported bridge

The influence of speed on the dynamic amplification of two loads crossing a simply supported bridge O'Brien, Eugene J.; Li, Yingyan; González, Arturo; Brady, Sean P. It is possible to use statistical data for the determination of traffic load models for the design of bridges. For existing bridges, traffic simulations based on measured traffic data, can provide a more accurate prediction of the characteristic load effect for assessment purposes. However, this procedure only provides the characteristic static loading or load effect. The total static-plus-dynamic load is often estimated based on conservative factors due to the high degree of uncertainty involved in the dynamic interaction between traffic, road profile and bridge. This paper aims to reduce this uncertainty by using simple dynamic models to obtain an understanding of the speeds and axle spacings that cause the highest dynamic amplifications. Bridge Managment 5, Proceedings of the 5th International Conference on Bridge Management, London, UK, 11-13 April 2005
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Sensitivity of predicted bridge traffic load effects to the tails of truck weight distributions

Sensitivity of predicted bridge traffic load effects to the tails of truck weight distributions Getachew, Abraham; O'Brien, Eugene J. In the last two decades, simulations have been used to predict the characteristic traffic load effects on bridges using Weigh-In-Motion (WIM) data. The recorded Gross Vehicle Weight (GVW) is usually modelled by multimodal distributions. The parameters for these distributions are generally obtained by using different goodness-of-fit tests where the entire recorded data is considered. These parameters are then used as the basis for the simulations. In this work, the sensitivity of the predicted traffic load effects to these fittings is investigated. Generally, moment at mid-span for different return periods can be determined from simulations based on three different assumptions. The first approach is to use empirical distribution functions, i.e., direct simulations using the recorded GVW data. The second approach is to use parametric distribution functions to represent GVW from the recorded data. In the third approach, developed here, semi-parametric distribution functions are used to model the distributions of GVW. From these, load effects corresponding to different return periods are calculated and compared. The results are shown to be highly sensitive to the assumption adopted. Bridge management 5 : inspection, maintenance, assessment and repair, London, UK, 11-13 April 2005
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Transverse variation of dynamic effects on beam-and-slab medium span bridges

Transverse variation of dynamic effects on beam-and-slab medium span bridges Rattigan, Paraic; González, Arturo; O'Brien, Eugene J.; Brady, Sean P. The common approach used to quantify bridge critical load cases is by definition conservative, as the effect of Dynamics is generalised. As a result a number of the site specific and load specific dynamic characteristics are neglected, and the transverse distribution of dynamic amplification across the bridge section also lacks consideration. In this paper, both issues are discussed using simulations of the passage of heavy traffic over an experimentally validated beam-and-slab bridge model. Stress variations across the bridge have been calculated for a number of scenarios involving different combinations of heavy trucks with varying velocities and directions. Results show a significant difference in transverse distribution of load effects and how certain longitudinal beams are more prone to dynamic excitation. EURODYN '05, Paris, France, September 4-7, 2005
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A Mixture Model for Predicting Patterns of Spatial Repeatability in Heavy Vehicle Fleets

A Mixture Model for Predicting Patterns of Spatial Repeatability in Heavy Vehicle Fleets Harris, Niall K.; O'Brien, Eugene J.; Wilson, Simon P. This paper presents a statistical heavy vehicle fleet model for predicting patterns of statistical spatial repeatability (SSR), i.e., the mean pattern of dynamic tyre force applied to a section of pavement by a large number of similar vehicles. Data from a Multiple Sensor Weigh-in-Motion (MS-WIM) system, collected for a sufficiently large number of vehicles, can be used to identify and measure SSR. A Bayesian analysis technique is used to infer the statistical distributions of fleet properties, given measured axle forces from MS-WIM data. The topic is introduced with the simple example of using the technique to predict distributions of axle weights, based on simulated MS-WIM measurements. The statistical Mixture model presented herein builds on previously presented models to add the necessary complexity and flexibility to represent the bimodal nature of truck fleets (e.g. the presence of both unladen and laden vehicles in the population). The model is numerically validated using simulated MS-WIM data to condition the Bayesian analysis. 3rd European Pavement and Asset Management Conference (EPAM3), Coimbra, Portugal, 7-9 July 2008
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A discussion on the merits and limitations of using drive-by monitoring to detect localised damage in a bridge

A discussion on the merits and limitations of using drive-by monitoring to detect localised damage in a bridge Hester, David; González, Arturo Given the large number of bridges that currently have no instrumentation, there are obvious advantages in monitoring the condition of a bridge by analysing the response of a vehicle crossing it. As a result, the last two decades have seen a rise in the research attempting to solve the problem of identifying damage in a bridge from vehicle measurements. This paper examines the theoretical feasibility and practical limitations of a drive-by system in identifying damage associated to localized stiffness losses. First, the nature of the damage feature that is sought within the vehicle response needs to be characterized. For this purpose, the total vehicle response is considered to be made of ¿static¿ and ¿dynamic¿ components, and where the bridge has experienced a localized loss in stiffness, an additional ¿damage¿ component. Understanding the nature of this ¿damage¿ component is crucial to have an informed discussion on how damage can be identified and localised. Leveraging this new understanding, the authors propose a wavelet-based drive-by algorithm. By comparing the effect of the ¿damage¿ component to other key effects defining the measurements such as ¿vehicle speed¿, the ¿road profile¿ and ¿noise¿ on a wavelet contour plot, it is possible to establish if there is a frequency range where drive-by can be successful. The algorithm uses then specific frequency bands to improve the sensitivity to damage with respect to limitations imposed by Vehicle-Bridge vibrations. Recommendations on the selection of the mother wavelet and frequency band are provided. Finally, the paper discusses the impact of noise and road profile on the ability of the approach to identify damage and how periodic measurements can be effective at monitoring localised stiffness changes. 
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Weighing-In-Motion of Axles and Vehicles for Europe (WAVE) WP1.2: Bridge WIM Systems

Weighing-In-Motion of Axles and Vehicles for Europe (WAVE) WP1.2: Bridge WIM Systems O'Brien, Eugene J.; Znidaric, Ales; Baumgärtner, Werner; González, Arturo; McNulty, Peter; et al. The objective of the WAVE project was to effect a significant step forward for those responsible  for road networks, through the following actions: Improve the capacity of conventional WIM systems to accurately estimate static loads from measurements of dynamic impact forces applied by axles, through use of arrays of sensors whose combined results can allow for the dynamic interaction between vehicle and pavement. Develop and improve the functioning and accuracy of bridge-based WIM systems through more sophisticated vehicle/bridge interaction modelling and data processing. Develop common data structures, formats and quality assurance procedures to facilitate the exchange and comparison of WIM data throughout Europe, to increase confidence in such  data and to provide reliable management information to decision makers. Perform tests of WIM systems to assess their durability and performance in various climatic conditions, particularly in cold regions where pavements deform and are weaker during the thaw and sensors are susceptible to studded tyres and de-icing salt. Develop standardised calibration methods  and  procedures  by improving  existing methods and extending their applicability to all European climates and types of WIM system. Develop and implement a new WIM technology,  based on an innovative fibre optic sensor  which has considerable potential in terms of quality and the extent of information provided and its insensitivity to harsh climatic conditions.This project constituted a strategic policy initiative to confirm the Europe's leadership in WIM. It led to the development of new technologies such as advanced multiple sensor and bridge WIM systems, a quality assurance procedure to be implemented in a pan-European database, data about the behaviour of WIM systems in harsh environments, an improvement in calibration procedures and  the development of a new European optic-fibre WIM technology. That will help road and transport decision makers.
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Camera-based Bridge Safety Monitoring

Camera-based Bridge Safety Monitoring O'Brien, Eugene J.; Catbas, Necati; Taylor, Su E.; Khuc, Tung This paper describes a research project focused on the safety assessment of bridges using camera-based technologies. It is a collaboration with partners in three countries: Ireland, the United Kingdom and the United States. A major challenge of the project is the development of algorithms and methods that transform the measured sensor signals and video images into a form that is highly damage-sensitive/ change-sensitive for bridge safety assessment. The study will exploit the unique attributes of computer vision systems, where the signal is "continuous in space". This research will significantly advance current sensor-based structural health monitoring with computer-vision techniques, leading to practical applications for damage detection of complex structures with a novel approach. In the long term, monitoring with cameras is expected to be more broadly utilized for structural engineering purposes because of its potential for inexpensive deployment in real life bridges. While advancing the knowledge by integrating multidisciplinary concepts from theory to application, this research will have direct benefits as civil infrastructure (and particularly aged bridges) has become a critical societal concern from safety and cost perspectives. The paper will describe the bridge monitoring system that will be developed. It will include a weigh-in-motion (WIM) system to weigh vehicles, with cameras to monitor both the traffic and the bridge. The WIM system and the 1st camera will track the traffic and will extract its properties. The 2nd camera with some supplementary sensors will monitor the response of the bridge to the traffic. Structural identification algorithms will transform all of this data into damage indicators that indicate when the bridge has deteriorated or changed. The system will be tested using numerical simulation, scale models in the laboratory and trials using full scale bridges in the field. 14th East Asia-Pacific Conference on Structural Engineering & Construction (EASEC-14), Ho Chi Minh City, Vietnam, 6-8 January 2016
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