Dr Boulent Imam

A large number of old metallic bridges have complex riveted details that pose challenges during their fatigue assessment using detail-specific S-N curves. In this paper, the fatigue life prediction capability of a novel method, the Theory of Critical Distances (TCD), which relies on the fatigue properties of the plain material only is investigated through finite element analysis of riveted details obtained from the literature. Fatigue life predictions of both the TCD and the traditional S-N methods were compared with experimental data from literature to assess their predictive capabilities. Details analysed include a number of riveted built-up girders for which experimental results were available. The results of this study showed that the TCD method successfully predicted fatigue life within the scatter bands of constant amplitude experimental data. The critical hotspot locations identified by the TCD method were consistent with the fatigue damage initiation sites observed in the experiments.

Scour is one of the most widespread causes of bridge failure worldwide. The magnitude of the river flow at the bridge location is a key factor which directly affects the scour hole depth. Climate change may cause changes in the flow characteristics in a river due to changes in the precipitation patterns and catchment characteristics. In this paper, statistical analysis of the expected maximum annual flow of rivers is combined with the Monte Carlo simulation to estimate the probability of local scour failure. Climate change is assumed to manifest itself through gradual changes in the statistical characteristics of the expected maximum annual flow distributions. Results are presented from a case study using a bridge in the UK, which revealed that a time-dependent increase in the mean of the expected maximum annual flow has a more pronounced effect on scour performance as compared to an increase of its variability alone. Amongst the cases examined, however, the most adverse effect on local scour performance is observed from the simultaneous increase in both mean and variability of the expected maximum annual flow. The results also highlighted the significance of the foundation depth and local scour model parameter in relation to the changing flow characteristics.

[Display omitted] •Novel traffic reinstatement and capacity restoration models for scour-damaged bridges.•Standardisation of damage per bridge component and functionality of scoured bridges.•High uncertainty in restoration task duration, dependencies and overlaps.•Duration of restoration tasks is twice the duration of functionality reinstatement.•Recovery models validated based on documented cases of scoured bridges. Bridges are the most vulnerable assets of our transport networks. They are disproportionately exposed to and hit by multiple natural hazards, with flooding being the leading cause of bridge failures in the world. Their performance is constantly challenged by the combined effects of natural hazard stressors, e.g. flash floods, exacerbated by climate change, ageing, increasing traffic volumes and loads. Bridges are vulnerable to scour and other flood-related impacts, such as hydraulic forces and debris accumulation. In order to assess and quantify the resilience of flood-critical bridges and subsequently deploy bridge resilience models aiming at building resilience into transport networks, it is essential to use reliable fragility, capacity restoration and traffic reinstatement metrics and models. It is surprising that, despite the importance of bridges and their high vulnerability to hydraulic actions, there are no available recovery models. The latter can help quantify the pace of post-flood capacity and functionality gain for facilitating well-informed decision making for reliable prioritisation and efficient allocation of resources in transport networks. The main barrier is the nature and complexity of recovery actions, which encompass engineering, operational, owner resources and organisational challenges, among others. This paper, for the first time in the international literature, aims at filling this gap by generating a set of reliable recovery models that include both bridge reinstatement (traffic capacity) and restoration (structural capacity) models based on a detailed questionnaire that elicits knowledge from experts. Recovery models are then presented and validated for spread and deep foundations for a typical reinforced concrete bridge, including restoration task prioritisation and scheduling, inter-task dependencies, idle times, durations and cost ratios for different damage levels, as well as the evolution of traffic capacity after floods.

Accumulation of instream large wood (i.e., fallen trees, trunks, branches, and roots) at bridges during floods may exacerbate flooding, scour and cause structural failure. Yet, explaining and predicting the likelihood of a bridge trapping wood remains challenging. Quantitative data regarding wood accumulation at bridges are scarce, and most equations proposed to estimate the accumulation probability were derived from laboratory experiments , and include variables such as flow velocity, Froude number, and approaching wood volume or size which are difficult to obtain. Other evaluations based on technical reports and information regarding wood removal have been proposed but are mostly qualitative. Until now, a data-driven approach combining multiple quantitative accessible variables at the river reach and catchment scales remains lacking. As a result, the controlling parameters explaining whether a bridge is prone to trap wood are still unclear. This work aims to fill this gap by analysing a database of 49 bridges across the United Kingdom (UK) classified as prone and not prone to wood accumulation. The database contained information regarding the geometry of the bridge (i.e., number of piers and pier shape) and we added parameters describing the upstream river channel morphology, the riparian land-cover, and high-flow characteristics. We applied multivariate statistics and a machine learning approach to identify the variables that explained and predicted the predisposition of bridges to wood accumulation. Results showed that the number of bridge piers, the unit stream power, the pier shape, and the riparian forested area explained 87% of the total variability for the training dataset (0.87 training accuracy), and the selected model had a testing accuracy of 0.60 (60%). Although limited by the sample size, this study sheds light on the identification of bridges prone to wood accumulation and can inform bridge design and management to mitigate wood-related hazards.

Access to detailed data sets which can enable detailed hydraulic modelling of the river around a bridge structure is not always possible and may require extensive surveys. It is important for infrastructure managers to decide whether additional data availability that may increase the accuracy of scour risk assessments may be worthwhile. In this regard, this paper aims to examine the scour risk assessment of bridges under different model resolutions by using two commonly used scour risk assessment procedures for railway bridges in the UK and investigate the sensitivity of a number of hydraulic parameters used in the scour prediction equations. These procedures are applied to four case study railway bridges coupled with four data availability scenarios capturing different levels of topographical and hydrological data available for the bridge/river site. The results show that the estimations of hydraulic parameters based on the simple empirical equations recommended by EX2502 for data scarcity conditions have a tendency to cause a significant disparity compared to the estimates from 1D and 2D HEC-RAS models. Particularly 2D models with bathymetric representation of river can provide more reliable results and improve the accuracy of scour risk assessments, especially for bridges that are close to the thresholds distinguishing different scour risk categories, i.e. medium to high risk. Sensitivity analysis of hydraulic parameters suggests that the most influential parameter that causes significant variations in total scour depth and scour risk is average velocity, followed by mean flow depth, mean floodplain depth, and mean floodplain width.

Vibration modal testing was carried out on a 130-year-old metallic riveted bridge, which was taken out of service, to estimate its modal properties under two different boundary conditions. A crane was used to lift the bridge, allowing it to move freely under the excitation load. An impulse hammer was used to excite the structure and a total of nine accelerometers were used to record the acceleration time histories. The response of the bridge, which is comprised of two main girders and seven cross girders, was estimated with a roving hammer technique, where one impulse hammer was used to excite the bridge at multiple locations, thus leading to the estimation of modal properties for the whole bridge, as well as individual girders. The set of modal properties obtained from free-free testing was compared with that estimated from identical testing of the bridge while resting on end supports. This comparison allows the quantification of the effect of the support conditions both on the estimates of the modal properties and on the associated noise levels. Ultimately, the results of this study are aimed at the refinement of bridge numerical (typically Finite Element based) models.

The volume explains how risk and decision-making analytics can be applied to the wicked problem of protecting infrastructure and society from extreme events. There is increasing research that takes into account the risks associated with the timing and severity of extreme events in engineering to reduce the vulnerability or increase the resiliency of infrastructure. "Engineering for extremes" is defined as measures taken to reduce the vulnerability or increase the resiliency of built infrastructure to climate change, hurricanes, storms, floods, earthquakes, heat waves, fires, and malevolent and abnormal events that include terrorism, gas explosions, vehicle impact and vehicle overload. The book introduces the key concepts needed to assess the economic and social well-being risks, costs and benefits of infrastructure to extreme events. This includes hazard modelling (likelihood and severity), infrastructure vulnerability, resilience or exposure (likelihood and extent of damage), social and economic loss models, risk reduction from protective measures, and decision theory (cost-benefit and utility analyses). Case studies authored by experts from around the world describe the practical aspects of risk assessment when deciding on the most cost-efficient measures to reduce infrastructure vulnerability to extreme events for housing, buildings, bridges, roads, tunnels, pipelines, and electricity infrastructure in the developed and developing worlds.

This article investigates the effectiveness of two distinct formative assessment methods for promoting deep learning and hence improving the performance amongst engineering students. The first method, applied for undergraduate students, employs a lecturer-led approach whereas the second method uses a student-led approach and e-learning for postgraduate teaching. Both studies demonstrate that the formative assessment and feedback has a positive effect on the performance of engineering students, especially those lying on the middle and lower grade tail. The mean exam marks increased by 15 to 20% as a result of introducing formative assessment to the case study modules. The main catalysts for performance improvement were found to be the feedback provided by the lecturer to the students, and by the students to their peer partners. Comparison of the two practices leads to the conclusion that whilst both methods are equally effective, peer assessment requires less time commitment from the lecturer.

This study focuses on deterioration modelling and performance assessment of metallic bridges affected by atmospheric corrosion, considering also the contribution of typical protective systems in the form of multi-layer coatings. The mechanisms leading to coating degradation are reviewed and the main coating types used by infrastructure owners are highlighted. Building on information contained in industry manuals, a simple model for coating degradation is proposed. Atmospheric corrosion models are then presented, with emphasis given to exposure classification, in line with corrosivity classification guidelines and recent research quantifying the influence of corrosion through dose–response functions. Coating degradation and corrosion models are integrated into a modelling framework, aimed at producing performance profiles of elements in metallic railway bridges. Finally, the framework is implemented in a case study in which a range of condition and resistance performance criteria are presented for different elements, such as girders and stiffeners, and their constituent parts, such as webs and flanges. It is shown that the proposed methodology is sufficiently detailed to enable differentiated performance predictions based on key external factors, and has scope for improvement, especially as coating and corrosion models are informed by the collection of field data.

Robustness evaluation of bridges within a risk-based framework requires estimation of the probability of occurrence of different hazards followed by an assessment of the vulnerability of the bridge with respect to those hazards, as well as quantification of the consequences of potential failure. The first part of the paper deals with a statistical analysis of past metallic bridge failures which can help in identifying the principal hazards affecting bridges and their associated vulnerability. The results show that natural hazards, design errors and limited knowledge are amongst the most commonly encountered causes of collapse in metallic bridges, followed by accidents and human error aspects other than in design. When analysed chronologically, the data demonstrates a decreasing trend for collapses attributed to limited knowledge and an increasing trend in failures resulting from accidents and natural hazards. The paper continues by presenting a categorisation procedure through which consequences arising from potential bridge failures can be estimated. Associated models for quantifying their magnitude considering both spatial and temporal domains are highlighted. Finally, the predictive capability of the models is outlined through a case study.

A system-based model for fatigue assessment of riveted railway bridge connections, comprising a number of basic components, is presented in this article. Probabilistic fatigue load spectra are developed through Monte Carlo simulation of train passages over a finite element model of a typical, short-span bridge. Uncertainties arising from loading, resistance and modelling sources are taken into account. The riveted connection is treated through a set of generic sub-systems that capture potential damage in identifiable hot-spots, such as rivets, holes and angle fillets. The fatigue reliability over time is evaluated through system reliability methods by treating these hot-spots as the elements of a structural system. The results show that the probability of failure of the connection depends significantly on the form of the system adopted for the analysis and the rivet clamping force. Damage scenarios accounting for the potential loss of rivet clamping force are investigated, and it is shown that, in some cases, they can affect connection reliability considerably. © 2012 Copyright Taylor and Francis Group, LLC.

A large number of metallic riveted bridges have been constructed using flat plates to form the deck of the structure. When assessed using traditional elastic methods these plates are routinely found to be under capacity for the application of the prescribed load even though they show zero signs of distress. This paper considers the use of alternative methods of assessment, namely yield line and membrane analyses, utilising the beneficial effects of plastic methods of analysis where appropriate to enhance the assessed capacity of these failing plates. The analytical formulation of both methods is presented considering the effects of the plate aspect ratio, support conditions, the presence of stiffeners, plate thicknesses and rivet sizes. By comparing the reassessed capacities of the plates obtained through the refined methods with the original assessed capacities it is shown that the former offer considerable enhancements in assessed capacity ranging between a factor of 1.3 to 7. © 2012 Elsevier Ltd.

Past experience has shown that stringer-to-cross-girder connections in riveted railway bridges are susceptible to fatigue cracking. This fatigue damage is caused by secondary stresses, which develop in the different components of the connection. For this reason, more detailed analysis techniques are needed to capture this type of behaviour. In this paper, a finite element (FE) model of a typical riveted railway bridge is developed by incorporating the detailed local geometry of a stringer-to-cross-girder connection into the global bridge model. Before the development of this model, benchmark FE studies are carried out on a double-lap joint and the results are presented in terms of stress concentration factors and stress gradients. Further verification studies are carried out on a local bridge connection FE model, in terms of its rotational stiffness. After this investigation, a refined FE model of the bridge is analysed under the passage of a freight train. Principal stress histories at different components of the connection are obtained, which are then combined with the plain material S–N curve, in order to identify the most fatigue-critical locations of the connection. These are identified as being the rivet holes and, in some cases, the angle fillet. By considering different rivet clamping stresses and different rivet defect scenarios it is found that the most damaging effects are caused by the presence of clearance between the rivet shank and the hole, and the loss of a rivet. The rivet clamping stress is also found to affect fatigue damage considerably.

Scour is one of the most widespread causes of bridge failure worldwide. The magnitude of the river flow at the bridge location is a key factor which directly affects the scour hole depth. Climate change may cause changes in the flow characteristics in a river due to changes in the precipitation patterns and catchment characteristics. In this paper, statistical analysis of the expected maximum annual flow of rivers is combined with the Monte Carlo simulation to estimate the probability of local scour failure. Climate change is assumed to manifest itself through gradual changes in the statistical characteristics of the expected maximum annual flow distributions. Results are presented from a case study using a bridge in the UK, which revealed that a time-dependent increase in the mean of the expected maximum annual flow has a more pronounced effect on scour performance as compared to an increase of its variability alone. Amongst the cases examined, however, the most adverse effect on local scour performance is observed from the simultaneous increase in both mean and variability of the expected maximum annual flow. The results also highlighted the significance of the foundation depth and local scour model parameter in relation to the changing flow characteristics.

Abstract Over 150 research articles relating three multi-disciplinary topics (air pollution, climate change and civil engineering structures) are reviewed to examine the footprints of air pollution and changing environment on the sustainability of building and transport structures (referred as built infrastructure). The aim of this review is to synthesize the existing knowledge on this topic, highlight recent advances in our understanding and discuss research priorities. The article begins with the background information on sources and emission trends of global warming (CO2, CH4, N2O, CFCs, SF6) and corrosive (SO2, O3, NOX) gases and their role in deterioration of building materials (e.g. steel, stone, concrete, brick and wood) exposed in outdoor environments. Further section covers the impacts of climate- and pollution-derived chemical pathways, generally represented by dose-response functions (DRFs), and changing environmental conditions on built infrastructure. The article concludes with the discussions on the topic areas covered and research challenges. A comprehensive inventory of DRFs is compiled. The case study carried out for analysing the inter-comparability of various DRFs on four different materials (carbon steel, limestone, zinc and copper) produced comparable results. Results of another case study revealed that future projected changes in temperature and/or relatively humidity are expected to have a modest effect on the material deterioration rate whereas changes in precipitation were found to show a more dominant impact. Evidences suggest that both changing and extreme environmental conditions are expected to affect the integrity of built infrastructure both in terms of direct structural damage and indirect losses of transport network functionality. Unlike stone and metals, substantially limited information is available on the deterioration of brick, concrete and wooden structures. Further research is warranted to develop more robust and theoretical DRFs for generalising their application, accurately mapping corrosion losses in an area, and costing risk of corrosion damage.

Weather-related disruption is a pressing issue for transport infrastructure in the UK, which is expected to aggravate due to climate change. Infrastructure managers, such as Network Rail, need to adapt to these changes, tackling the challenges brought about by wide-ranging uncertainties from various sources. This paper explores the relationship between climate change and bridge scour, identifying barriers to sustainable adaptation. Scour is the removal of riverbed material at bridge foundations due to hydraulic action and is the foremost cause of bridge failure in the UK and worldwide. A model is developed that simulates the causal chain from climate change to scour risk. This is applied to four case study bridges in Wales and the south-west of England, quantifying the effects of climate change and tracing key uncertainties in the process. Results show that the current scour risk models in Network Rail may be insensitive to increases in risk due to climate change. One way to tackle this may be to introduce models to assess absolute risk; current scour risk models are used only for the prioritisation of vulnerable sites.

This study provides an insight into the dominant negotiation processes that occur between the authors of research articles and academic reviewers at the peer reviewing stage. Data of reviewers comments and authors responses on 32 science and engineering based journal articles covering four decision categories (accept as is, accept with minor revisions, major revisions and reject) were collected. A commonly practised peer-review approach in teaching was applied to analyse the data and to identify the key negotiation attributes, their frequency of occurrence, authors' reaction and approach to negotiate with the reviewers. Six main negotiation attributes were identified. Technical quality was the most frequent (31% of all instances) attracting mixed reactions from the authors. The remaining attributes constituted suggestion (20%), explanation (20%), restatement (15%), grammar (13%) and structure (~1%). With the exception of `explanation' where authors had to counteract to clear misunderstood concepts or contents by the reviewers, the other attributes were of highly collaborative nature and were willingly accepted by the authors. All these negotiations were found to help authors in improving the overall quality, clarity and readability of their manuscripts, besides forcing them to rethink about unclear contents. The negotiation trends emerged here can help the academic researchers to improve the quality of their articles before submission to the peer-reviewed journals. It can also provide a link through which their classroom teaching experience involving supervision of peer review negotiations among students can be utilised in writing their research articles and negotiating with academic reviewers.

This paper presents an overview of recent research efforts by the authors and co-workers on the fatigue assessment of old metallic railway bridges. The investigation focuses on the behaviour of riveted stringer-to-cross-girder connections in a typical, short-span bridge. A generic methodology, which is based on nominal stresses and the S–N method, is presented first, followed by a more detailed analysis using a recently developed fatigue assessment theory, which is based on local stress distributions. The discussion is made within a deterministic as well as a probabilistic context and typical results are presented in terms of fatigue damage and remaining fatigue life.

Recent studies have found that stringer-to-cross-girder connections in riveted railway bridges are susceptible to fatigue cracking, caused by secondary, deformation induced effects. These effects are difficult to interpret in terms of a single applied stress descriptor, which is customarily used in an S–N assessment. In order to address this problem, the results of a global–local finite element analysis of a riveted railway bridge are used in this paper within the context of the theory of critical distances (TCD). Using the TCD in the way proposed by Taylor [Bellett D, Taylor D, Marco S, Mazzeo E, Guillois J, Pircher T. The fatigue behaviour of three-dimensional stress concentrations. Int J Fatigue 2005; 27(3) 207–21], fatigue damage (a) is shown to converge upon mesh refinement and (b) is found to be relatively sensitive to the selection of the characteristic dimension of the critical volume. Furthermore, comparisons of the TCD-based method with its more traditional, detail-specific S–N counterpart, reveal that the latter can underestimate fatigue damage, in some cases by a factor of 3.5.

Bridge owners worldwide manage large numbers of assets with limited budgets through risk assessments, using asset-specific data. However, when managing a large stock of aging assets, maintaining robust and up-to-date data records can be challenging. This issue comes to the fore when trying to understand asset vulnerability to current and future weather events in the context of a changing climate. By using a sample of data on railway bridges in the UK, this paper explores uncertainty associated with raw data used in bridge scour risk assessments for bridge stocks and its interaction with climate change uncertainty. Results indicate that our ability to foresee climate change impacts is not only limited by the aleatory uncertainty of climate change projections; avoidable uncertainty in basic asset data can outweigh aleatory uncertainty by an order of magnitude. Some parameters, such as floodplain width and the width of abutments, were found to be both subject to high uncertainty and also very influential for the estimation of scour risk, leading to reduction in the confidence in scour risk assessments. This finding contrasts with the unchallenged assumption in the field that dimensions of bridge elements are not associated with uncertainty. The nature of scour implies that a potential increase in the frequency and severity of extreme weather events will increase scour risk. This paper shows that in order to be able to understand and account for this increase, scour management processes must effectively address data uncertainty. Active measures to control data quality would be an effective step towards understanding and managing bridge resilience in the context of current and future climatic conditions.

This paper presents load models for quantifying the effect of historical rail traffic on the remaining fatigue life of riveted bridges in the UK. Three types of load models, based on realistic trains, accounting for differences in rail traffic composition, are developed and subsequently used for investigating their effect on the accumulation of fatigue damage in typical old metallic bridge structures. The overall findings show that the increase within train axle loads from 1900 to 2010 is the main attributor to the significant increase in fatigue damage caused from the modern trains compared to the residual fatigue damage from the historic trains. These findings are particularly relevant to the majority of existing metallic rail bridges on the rail network, which are known to have a span length less than 10 m. These findings show the importance of considering the effects of historical loading for more reliable fatigue assessment purposes, leading towards more efficient planning of bridge maintenance and renewal programmes.

The aim of this paper is to present advanced modelling techniques for dynamic analysis of steel railway bridges. Finite element analyses of a case study skew bridge are carried out and the results are compared with available field measurements. Initially, eigenvalue analyses of different models are carried out in order to obtain the fundamental mode shapes and bridge frequencies and to assess the capability of each model to capture the dynamic behaviour of the bridge. Single-span, three-span and full bridge models are investigated with different elements such as shell, beam and combination of these. Very good agreement between the fundamental dynamic properties of the bridge and empirical results is found. Following the eigenvalue analysis, time history dynamic analyses are carried out using the full bridge model. The analyses are carried out for different train speeds and the strain histories are compared with available field measurements. In terms of fatigue assessment, mean stress range values, obtained from the strain histories at selected locations on the bridge members are also compared to each other. The results show that a full bridge model using a combination of beam and shell elements is a reasonably accurate and computationally efficient way of capturing the dynamic behaviour of a bridge and estimating mean stress range for fatigue damage calculations.

As some of the older riveted railway bridges are close to or have even exceeded their theoretical fatigue lives, it is desirable to develop a comprehensive fatigue assessment methodology for fatigue-critical details. The aim of this study was to present damage and fatigue life estimates for the riveted connections of a typical riveted UK railway bridge through finite-element analyses. In particular, the effect of connection fixity and assumed fatigue detail classification, the effect of the simultaneous passage of two trains over the bridge, the effect of a reduced Young's modulus for the bridge material and the effect of dynamic amplification are studied under different loading scenarios. A historical load model was developed in order to represent bridge rail traffic between 1900 and 1970. The BS 5400 medium traffic trains were used to represent the bridge traffic from 1970 onwards. It was found that the connection damage is axle-dominated and is affected by the parameters mentioned above. The fully-fixed stringer-to-cross-girder connections were found to be the most fatigue-critical details. The damage accumulation rate was found to be small in the pre-1970 period under the historical load model but showed a considerable increase with the introduction of the BS 5400 trains (post-1970).

A large percentage of the railway bridges in the UK rail network and around Europe are of riveted construction exceeding in many cases 100 years of age. The remaining fa-tigue life of these bridges is difficult to estimate due to the uncertainties regarding the fatigue behaviour of wrought-iron and older steel material, which was used for their construction, as well as the actual loading and the number of cycles that these bridges have experienced in the past and will be experiencing in the future. This paper presents probabilistic fatigue life esti-mates for a stringer-to-cross-girder connection of a typical riveted rail bridge. On the loading side, the problem is randomised through the frequency of train traffic, dynamic amplification and the ratio between actual and calculated stresses. On the response side, S-N curves pertaining to the various assumed classes for the connection details and the Miner sum are also treated as random.

The aim of this paper is to propose a methodological framework for consequence analysis of transportation networks. The probabilistic framework is based on the definition of performance indicators that describe the time-dependent functionality of the asset/system, starting from a pre-existing normal performance state, capturing the time and evolution of disruption during and after the disruption and during the recovery/restoration stage. A proposed case study that will be used for the demonstration of the applicability of the framework is described.

The fractures observed following the Northridge earthquake in welded beam-to-column connections have been linked to a number of different material and manufacturing parameters such as fracture toughness, crack size and yield strength all of which are in general random. In a previous study of a simple sway frame, where randomness of the above variables was considered, fracture of the connections was found to result in the reduction of the frame’s lateral stiffness with an accompanying reduction of the natural frequency of the frame. In this paper, the linear elastic behaviour of a multi degree-of-freedom frame under earthquake loading is examined probabilistically as an extension of the previous investigation. The results demonstrate that most of the connections fail early on in the seismic event and that fracture probabilities are heavily dependant on the storey on which they are located. Removal of the backing bar is found to reduce the failure probability of the connection without, however, being able to prevent fracture when used as a sole measure.

A large percentage of the railway bridges in the UK rail network and around Europe are of riveted construction exceeding in many cases 100 years of age. The remaining fatigue life of these bridges is difficult to estimate due to the uncertainties regarding the fatigue behaviour of wrought-iron and older steel material which were used for their construction. The problem is further compounded by the uncertainties associated with the loading both past and future. Previous global finite element analyses of a typical wrought-iron riveted railway bridge have shown that the fatigue critical details are the inner stringer-to-cross-girder connections (Imam et al. 2005). The analyses were carried out under a historical load model (Imam et al. 2005), developed to represent rail traffic in the period 1900-1970, and present day traffic (BS5400 1980) for the period 1970 onwards. Deterministic remaining fatigue life estimates of the connections were found to be sensitive to the level of dynamic amplification as well as the fatigue classification of the details. Following this work, this paper presents probabilistic fatigue life estimates for the most highly damaged stringer-to-cross-girder connection, as identified by the global analysis of the riveted bridge. On the loading side, the problem is randomised through the frequency of train traffic, dynamic amplification and uncertainties regarding the difference between actual and calculated stresses. On the response side, different assumed S-N curves used for detail classification and the Miner sum are also treated as random. The probabilistic analysis, which is carried out using Monte Carlo simulation, shows that the most heavily fatigue-loaded stringer-to-cross-girder connection has considerable fatigue life reserve. Through a sensitivity study, it is found that for a 2.3% probability of failure, the remaining fatigue life of the investigated connection is equal to 68 years for a pessimistic scenario. Under a more realistic combination of variables (base model), the 2.3% characteristic remaining fatigue life is found to be 480 years. Figure 1 shows the effect of different variables on the time to attainment of a 2.3% probability of failure assuming a base model. It can be seen that fatigue life estimates exhibit the highest sensitivity to detail classification, in other words the constant amplitude fatigue behaviour of the detail, and the factor α, which takes into account the difference between measured and calculated stresses. In particular, by changing the detail classification from Class WI (base model), which is used to represent wrought-iron riveted details, to Class D (BS5400 1980), which is used to represent bolted or riveted steel connections with a high clamping force, there is a 180% increase in the time required to attain a 2.3% probability of fatigue failure. On the other hand, a change to a modified Class B detail, which may be thought of being representative of a riveted connection with no or low clamping force in the rivets, is found to result in a 40% decrease in the same time. The use of a mean value of 0.70 for the factor α is found to result in an increase in the fatigue life at the 2.3% failure probability by about 110%. However, a mean value of α of 0.90 is found to result in a decrease in this fatigue life by about 50%. The mean values of the cumulative damage model (Δ) and the dynamic amplification factor (DAF) may be seen in Figure 1 to be of less importance. (Graph Presented). © 2006 Taylor & Francis Group.

Corrosion is a commonly observed deterioration mechanism in metallic bridges, resulting in loss of material with time, which may lead to impaired performance and premature in-service failures. A number of factors are known to influence the initiation and subsequent rate of corrosion in metallic bridges, including climatic parameters such as relative humidity and temperature, atmospheric pollutants (e.g. SO2) and high airborne salinity. These factors and their interactions may have a detrimental influence on the rate of corrosion. Alterations of the exposure conditions, for instance due to climate change or/and adoption of government policies related to the levels of atmospheric pollutants, are likely to influence the long-term corrosion rates in metallic bridges. This paper presents a methodology, based on reliability analysis, for the time-dependent risk assessment of corroding metallic railway bridges, considering the impact of long-term changes in climatic and atmospheric pollutant variables. The evolution of variables related to the deterioration process (e.g. climatic parameters, atmospheric pollutants, etc) and bridge resistance variables are treated as random using suitable distributions. The time evolution of the probability of failure of the bridge is quantified through Monte Carlo simulation and this is then extended into risk by considering the consequences of bridge failure. The procedure is demonstrated through a case study using a steel railway bridge. Results are presented for the moment-capacity limit state of the bridge, considering a number of emission scenarios based on UKCP09 climate projections and assumed changes in the concentrations of atmospheric pollutants.

Structural failure consequences can take many different forms: from material/structural damage and human injuries/fatalities, to functional downtime and environmental impact, as well as loss of reputation and collateral damage that may be orders of magnitude higher than the reconstruction cost. Within a risk-based robustness framework, consequence modelling is an important step in estimating risk, and needs to be undertaken with clarity and transparency. This paper highlights the principles to be adopted in estimating consequences arising from potential building and bridge failures. The two structural forms are chosen so as to elucidate factors relevant to cases where failure is confined to a single facility, or where it is likely to affect a spatial network. Past experience, as well as methods that are increasingly used in emergency response planning, are reviewed. A categorisation of failure consequences is presented, together with associated models for quantifying their magnitude.

This paper presents a probabilistic load model for fatigue assessment of old metallic railway bridges. The traffic basis of the model consists of trains obtained from past records and present-day trains obtained from codes. The traffic is divided into four distinct time periods each associated with particular characteristics in rail traffic. Traffic evolution scenarios for the future, in terms of increase in train axle loads or train frequencies, are also considered. With the help of a finite element model of a short-span, riveted railway bridge, train loading is converted into probabilistic fatigue load spectra via Monte Carlo train simulations. The spectra are found to be described well by Weibull distributions. As an example, the application of the proposed load model for the estimation of the remaining fatigue life of a riveted bridge connection is presented. Uncertainties in terms of loading, resistance and modelling are taken into account. The results show that introduction of higher train axle weights in the future is expected to reduce the remaining life of the connection considerably faster than the accommodation of increased freight through higher train frequencies.

The riveted type of construction is characteristic of older railway bridges. As some of these bridges approach, or have even exceeded their theoretical fatigue life under in-creasing train loads, it is desirable to improve the procedures available for the assessment of fa-tigue-critical details. The aim of this paper is to present results through the use of the FE method, which address the manner in which assumed conditions of fixity of bridge riveted joints affect the resulting internal stresses. Different degrees of connection fixity, ranging from fully fixed to partially fixed, are assigned to the connections. A nominal train is traversed over a UK-typical bridge configuration and the resulting stress histories are converted into stress ranges us-ing the rainflow algorithm. By comparing the resulting S-N damage, the extent to which con-nection fixity can affect fatigue life predictions is quantified and ranking of fatigue-critical de-tails is undertaken.

This paper presents a review of bridge failure statistics, based on literature survey and webbased search, focusing on metallic bridges. Failure cases are distinguished between those resulting in bridge collapse and those that have not reached collapse but resulted in loss of serviceability. Classification of the most common failure causes and modes of failure is undertaken. Statistics regarding the time frame of collapses in the bridge lifetime, bridge structural configuration and the number of resulting casualties are presented. The results show that collapses due to natural hazards, design errors and limited knowledge are the most commonly encountered in metallic bridges, followed by accidents and human error. When analysed chronologically, the data demonstrates a decreasing trend for collapses attributed to limited knowledge and an increasing trend in failures resulting from accidents and natural hazards. In terms of non-collapse cases, fatigue failures are found to be predominant. The paper concludes with a discussion of bridge failure consequences and their significance in risk assessment of bridge structures.

A large number of metallic railway bridges currently in use in the UK are of riveted construction and are close to 100 years old. A fatigue assessment methodology is needed for such bridges since these may be close to the end of their fatigue lives. Part of such a methodology is the global analysis of the bridge in order to identify the most fatigue critical details. The aim of this paper is to present results, in terms of Miner’s damage at the riveted connections of a typical riveted UK railway bridge, obtained from a global finite element analysis under various train loadings.

The purpose of this paper is to present fatigue-related results obtained from finite element analyses of a typical riveted railway bridge. The first part of the paper deals with past case studies related to the fatigue assessment of various riveted railway bridges. The second part of the paper presents the results obtained from the finite element analyses of the wrought-iron bridge under typical present-day and assumed historical train loadings. These results are in the form of fatigue damage and associated remaining life estimates of the riveted connections. By fatigue-ranking the connections on an S-N basis and under different detail classifications, the most fatigue-critical connections are identified as being the inner stringer-to-cross-girder connections assuming full rotational connection fixity. Dynamic amplification is shown to affect remaining fatigue life estimates considerably.

This paper presents a generic methodology for the use of PFM within the context of bridge loading for the fatigue design and assessment of steel railway bridges and provides detailed guidance on how to use the proposed methodology in order to carry out a PFM-based fatigue assessment. The problem is set in a probabilistic context to take into account material, loading as well as modeling uncertainties. Guidance is given on how to calibrate a constant amplitude PFM analysis against an S-N curve. Finally, as a case study, a cracked welded bridge detail is considered and its time-dependent fatigue reliability is established © 2012 Taylor & Francis Group.

The objective of the investigation presented in this paper was to identify and rank in terms of damage, fatigue-critical locations on a typical riveted stringer-to-cross-girder connection used in railway bridges using the finite element method. The results were derived in the form of Miner’s damage under the passage of a typical freight train. Through this ranking and by considering different damage scenarios, including rivet defects, loss of clamping force in a rivet and loss of a rivet, it was found that the most damaging effect was caused by the presence of clearance between the rivet shank and the hole or by the loss of a rivet. The damage at the angle-fillet and the rivets connecting the angle to the stringer web was found not to be affected considerably by rivet defects. In contrast, the rivet clamping force appeared to affect fatigue damage around the angle holes and on the rivets to a considerable extent. The effect of the manner of hole preparation was not considered in this investigation.

This paper presents a system-based model for the fatigue assessment of old, deteriorating riveted railway bridge connections, which are built up of a number of basic components. A finite element model of a typical, short-span railway bridge is used to convert train loading into probabilistic fatigue load spectra via Monte Carlo train simulations. Uncertainties in terms of loading, resistance and modelling are taken into account. Fatigue damage calculations are based on the Theory of Critical Distances, which is a recently developed theory that considers the entire stress distribution ahead of any given stress concentration. The paper focuses on a typical riveted stringer-to-cross-girder connection which is treated through generic sub-systems that capture potential damage in identifiable hot-spots, such as rivets, holes and angle fillets. By treating these hot- spots as the elements of a structural system susceptible to fatigue failure, its reliability over time is evaluated using system reliability methods. The results show that the probability of failure of the connection depends significantly on the form of the system adopted for the analysis. Low remaining lives on specific hotspots on different connection components show that fatigue cracking may be imminent or may have already initiated in a number of similar existing bridge connections.

Human activities on earth it is observed is having negative impact on the continuous existence of life on the planet. This is as a result of build-up of gases that tend to affect life and well-being of plants and animals including structures put in place to support them. Structural failure as a result of pollutant exposure does not occur unless where there is wrong design of the structure or the owner has not carried out routine maintenance. The effect of such loss on structure in place need to be further studied to engender better understanding of structural failure possibilities or its reliability. This work looked at the effect of gases such as SO2 and humidity known as climate change gases in the air and their effect on steel structures, specifically bridges, in rural, urban and industrial locations. It was shown also that for these three types of locations, the moment resistance and shear resistance of structures overtime will decrease by 3% and 4.6% respectively. However, the deflection of the same structure will increase by 1% over the same time range. The implication will be an increase in the cost of design and construction as a result of increased thickness of steel structures and additional paint coating to reduce this negative effect