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.

Examining Smarter Travel Options to Reduce Emissions

Examining Smarter Travel Options to Reduce Emissions Carroll, Páraic; Caulfield, B. (Brian); Ahern, Aoife This deliverable explores a strategy to encourage a realistic modal shift from the private car to sustainable travel modes such as walking, cycling, bus, rail and smarter modes like carpooling and car-sharing in the Greater Dublin Area (GDA). This research is a large component of the work that has been conducted as part of the Greening Transport project. It examines the responsiveness of a sample to a range of policy measures aiming to incentivise sustainable commuting practices to work and education in the GDA. By means of a stated preference (SP) experiment, a selection of policies was tested in various hypothetical scenarios in order to gauge their response in terms of travel behaviour change, ultimately quantified by analysing the potential modal shift. This technical report will assess relevant literature on this subject and delineate the experimental design, survey creation process and most importantly delve into the discrete-choice modelling results and analysis of this study. Motivation for this work was taken from comparable experiments from leading researchers in the field of SP and discrete-choice modelling. However, an approach such as this has to date not been conducted in the context of Ireland. This presents an opportunity to gain a greater understanding of the behavioural outcomes of implementing various sustainable transport policy incentives from which a modal shift can be achieved in Ireland. The aims of this research are in line with those set-out by the Greening Transport project that is leading this work - exploring ways of promoting smarter travel options as a means of attaining emissions savings and mitigating the associated causes of climate change such as air pollution, burning of fossil fuels and noise pollution in urban areas. However, one of the principal goals of this study is to incentivise "car shedding" behaviour, i.e. promoting a reduction in car usage by making alternative and sustainable travel modes more practical and competitive in terms of time and cost amongst other attributes, in addition to being equally or more convenient modes than driving a car alone. A SP survey instrument was implemented to gather responses to a range of hypothetical scenarios, in addition to other revealed preference (current travel activity), attitudinal and socio-demographic questions to generate various types of data for analysis. The main SP component of the survey was utilised to determine the variables of statistical significance that increase or decrease the utility of the modes and predict or forecast behavioural responses and implications, in the form of direct and cross elasticities and "what if" simulations, to various policy instruments ("carrots") included in the stated choice scenario.
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Validation of Scenario Modelling for Bridge Loading

Validation of Scenario Modelling for Bridge Loading O'Brien, Eugene J.; Leahy, Cathal; Enright, Bernard; Caprani, Colin C. Accurate estimates of characteristic bridge load effects are required for efficient design and assessment of bridges, and long-run traffic simulations are an effective method for estimating the effects. For multi-lane same-direction traffic, truck weights and locations on the bridge are correlated and this affects the calculated load effects. Scenario Modelling is a recently developed method which uses weigh-in-motion (WIM) data to simulate multi-lane same-direction traffic while maintaining location and weight correlations. It has been unclear however whether the method may produce unrealistic driver behaviour when extrapolating beyond the weigh-in-motion measuring period. As weigh-in-motion databases with more than about a year of data are not available, a microsimulation traffic model, which can simulate driver behaviour, is used here to assess the accuracy of extrapolating traffic effects using Scenario Modelling. The microsimulation is used to generate an extended reference dataset against which the results of Scenario Modelling are compared. It is found that the characteristic load effects obtained using Scenario Modelling compare well with the reference dataset. As a result, for the first time researchers and practitioners can model two-lane same-direction traffic loading on bridges while being confident that the approach is generating accurate estimates of characteristic load effects as well as effectively reproducing the complex traffic correlations involved.
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Drive-by detection of railway track stiffness variation using in-service vehicles

Drive-by detection of railway track stiffness variation using in-service vehicles Quirke, Paraic; Cantero, Daniel; O'Brien, Eugene J.; Bowe, Cathal Railway track stiffness is an important track property which can help with the identification of maintenance related problems. Railway track stiffness can currently be measured using stationary equipment or specialised low-speed vehicles. The concept of using trains in regular service to measure track stiffness, has the potential to provide inexpensive daily 'drive-by' track monitoring to complement data collected by less-frequent monitoring techniques. A method is proposed in this paper for the detection of track stiffness variation through an analysis of vehicle accelerations resulting from the vehicle-track dynamic interaction (VTI). The Cross Entropy optimisation technique is applied to determine the track stiffness profile that generates a vehicle response that best fits the measured vertical accelerations of a railway carriage bogie. Numerical validation of the concept is achieved by using a 2-dimensional half-bogie dynamic model, representing a railway vehicle, to infer a global track stiffness profile along a track. The Track Stiffness Measurement Algorithm (TSMA) is implemented in Matlab. This paper reports the results of the numerical simulations. The proposed method gives good estimates of the track stiffness. To the authors' knowledge this is the first time an optimisation technique has been applied to the determination of railway track stiffness.
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Determination of longitudinal profile of railway track using vehicle-based inertial readings

Determination of longitudinal profile of railway track using vehicle-based inertial readings O'Brien, Eugene J.; Bowe, Cathal; Quirke, Paraic; Cantero, Daniel The longitudinal profile of a railway track excites a dynamic response in a train which can potentially be used to determine that profile. A method is proposed in this paper for the determination of the longitudinal profile through an analysis of bogie vertical accelerations and angular velocities resulting from the train/track dynamic interaction. The Cross Entropy optimisation technique is applied to determine the railway track profile elevations that generate a vehicle response which best fits the measured dynamic response of a railway carriage bogie. Numerical validation of the concept is achieved by using a 2-dimensional quarter-car dynamic model, representing a railway carriage and bogie, traversing an infinitely stiff profile. The concept is further tested by the introduction of a 2-dimensional car dynamic vehicle model and a 3 layer track model to infer the track profile in the longitudinal direction. Both interaction models are implemented in Matlab. Various grades of track irregularity are generated which excite the vehicle inducing a dynamic response. Ten vertical elevations are found at a time which give a least squares fit of theoretical to measured accelerations and angular velocity. In each time step, half of these elevations are retained and a new optimisation is used to determine the next ten elevations along the length of the track. The optimised elevations are collated to determine the overall longitudinal profile over a finite length of railway track.
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Recent Developments in Bridge Weigh in Motion (B-WIM)

Recent Developments in Bridge Weigh in Motion (B-WIM) Lyndon, Myra; Taylor, Su E.; Robinson, Desmond; Mufti, A.; O'Brien, Eugene J. Bridge Weigh in Motion (B-WIM) uses accurate sensing systems to transform an existing bridge into a mechanism to determine actual traffic loading. This information on traffic loading can enable efficient and economical management of transport networks and is becoming a valuable tool for bridge safety assessment. B-WIM can provide site specific traffic loading on deteriorating bridges, which can be used to determine if the reduced capacity is still sufficient to allow the structure to remain operational and minimise unnecessary replacement or rehabilitation costs and prevent disruption to traffic. There have been numerous reports on the accuracy classifications of existing B-WIM installations and some common issues have emerged. This paper details some of the recent developments in B-WIM which were aimed at overcoming these issues. A new system has been developed at Queens University Belfast using fibre optic sensors to provide accurate axle detection and improved accuracy overall. The results presented in this paper show that the fibre optic system provided much more accurate results than conventional WIM systems, as the FOS provide clearer signals at high scanning rates which require less filtering and less post processing. A major disadvantage of existing B-WIM systems is the inability to deal with more than one vehicle on the bridge at the same time; sensor strips have been proposed to overcome this issue. A bridge can be considered safe if the probability that load exceeds resistance is acceptably low, hence B-WIM information from advanced sensors can provide confidence in our ageing structures.
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Study Of Same-Lane And Inter-Lane GVW Correlation

Study Of Same-Lane And Inter-Lane GVW Correlation Enright, Bernard; O'Brien, Eugene J.; Caprani, Colin C. Extensive work has been done over the last two decades on the simulation of traffic loading on bridges. The methodology used is to generate a number of years of simulated traffic and to use extreme value statistics to predict more accurately the characteristic loading for a given bridge. The parameters and probability distributions used in the Monte Carlo simulation must be based on observed sample traffic data. Many previous studies have assumed that there is no significant correlation between the Gross Vehicle Weights (GVW) of trucks in the same lane, or between trucks in adjacent, same direction lanes. For this paper, an extensive database of Dutch Weigh in Motion data is analysed. Data is collected from two same direction lanes and is time stamped to the nearest 0.01 seconds. The statistical characteristics of this set of data are presented, and various techniques are used to establish the nature and extent of GVW correlation. 3rd International ASRANet Colloquium, Glasgow, Scotland, 10-12 July 2006
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Traffic Load Effect Forecasting for Bridges

Traffic Load Effect Forecasting for Bridges Leahy, Cathal; O'Brien, Eugene J.; O'Connor, Alan Traffic flows, as well as truck weights, increase with time. This must be taken into account in order to accurately assess traffic loading on bridges. The Eurocode Load Model 1 is used for the design of new bridges but a scaled down version of the model can be used for the assessment of existing bridges. This scaling is usually done by applying α–factors to the load model. The effect of traffic growth on these α–factors is assessed in this paper. Weigh-in-motion data from the Netherlands is used as the basis for traffic models which simulate year-on-year growth of both traffic flow and truck weights. A time-varying generalised extreme value distribution is then used to calculate the characteristic load effects and determine the α–factors. The effect of different traffic growth rates on these α–factors is then examined. It is found that an increase in truck weights has the most influence on the α–factors but that increased flow also has a significant effect. IABSE Conference on Structural Engineering: Providing Solutions to Global Challenges, Geneva, Switzerland, 23-25 September 2015
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Identifying and Modelling Permit Trucks for Bridge Loading

Identifying and Modelling Permit Trucks for Bridge Loading Enright, Bernard; O'Brien, Eugene J.; Leahy, Cathal Accurate estimates of characteristic traffic load effects are essential in order to optimize bridge safety assessment. Permit trucks dominate the extreme upper tail of the truck loading distribution and as a result need careful examination. This paper proposes rules for filtering these trucks from Weigh-In-Motion data for both the US and Europe.  The importance of these trucks in critical bridge loading events is then examined for both regions. A Monte Carlo traffic simulation model is developed which focuses on the accurate simulation of permit trucks.
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Cross entropy weight minimization of a compressive strut

Cross entropy weight minimization of a compressive strut O'Brien, Eugene J.; Malekjafarian, Abdollah; Micu, Alexandra In this study, a population-based optimization algorithm is used to minimize the weight of a compressive strut. A geometrically nonlinear analysis is carried out to get an accurate measure of the structure's true capacity, allowing for individual member and overall structure (and sub-structure) buckling. To overcome the computational challenge of nonlinear analysis, the study uses a simple definition of the onset of instability and hence the number of iterations is cut to a minimum. 2nd International Conference on Progress in Additive Manufacturing (Pro-AM 2016), Singapore, May, 2016
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Prediction of Deterioration of Asphalt Pavements by Mechanistic-Empirical Methods

Prediction of Deterioration of Asphalt Pavements by Mechanistic-Empirical Methods Belay, Abraham; O'Brien, Eugene J.; Collop, Andrew Cracking of an asphalt layer arises from repeated tensile strains, the maximum value of which typically occurs at the bottom of the layer (particularly for thinner asphalt layers). The crack, once initiated, propagates upwards causing gradual weakening of the structure. The development of a rut arises from the accumulation of permanent strains throughout the structure. A model of pavement damage accumulation, leading to a prediction of pavement life, is described. In addition to pavement damage, the model allows for the spatial repeatability of traffic loading and differences in the progression of damage at different points along the road. The procedure is divided into four main areas: dynamic vehicle simulation; pavement primary response calculation; pavement damage calculation and damage feedback mechanism. The modes of damage that are included in the model are structural rutting and fatigue damage to the asphalt layers. These primary response influence functions are combined with the dynamic tyre forces, to give primary pavement response time histories at a large number of equally spaced discrete points along the pavement.  The primary responses are combined with the appropriate pavement damage models and the number of load applications, to predict damage (rutting and fatigue damage) as a function of distance along the pavement for each time increment. An updated surface profile is then generated by subtracting the calculated rutting in the wheel path from the initial profile used for that time increment. This mechanism accounts for the effects of changing surface roughness on the pattern of statistical spatial repeatability and hence the pattern of mean dynamic tyre force. The calculated fatigue damage is used to reduce the stiffness of the asphaltic material for each sub-section. This mechanism reflects the effects of cumulative fatigue damage on the primary responses and hence subsequent pavement damage. The above process is then repeated for many time increments until the pavement has reached the end of its serviceable life. The model gives many insights into the nature of the deterioration process and the changing pattern of spatial repeatability as the profile deforms. 6th Symposium on Pavement Surface Characteristics, Portoroz, Slovenia, 20-23 October 2008
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