Horizon 2020 Marie Skłodowska-Curie Innovative Training Network

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Publications in Workshops and Conferences 2018-06-22T08:20:36+00:00

 About the overall TRUSS ITN project 

There is multitude of models available to assess structural safety based on a set of input parameters. As the degree of complexity of the models increases, the uncertainty of their output tends to decrease. However, more complex models typically require more input parameters, which may contain a higher degree of uncertainty. Therefore, it becomes necessary to find the balance that, for a particular scenario, will reduce the overall uncertainty (model + parameters) in structural safety. The latter is the objective of the Marie Skłodowska-Curie Innovative Training Network titled TRUSS (Training in Reducing Uncertainty in Structural Safety) funded by the EU Horizon 2020 research and innovation programme (http://trussitn.eu). This paper describes how TRUSS addresses uncertainty in: (a) structural reliability of materials such as basalt fiber reinforced polymer, (b) testing techniques in the assessment of concrete strength in buildings, (c) numerical methods in computing the non-linear response of submerged nuclear components subjected to an earthquake, (d) estimation of life of wind turbines, (e) the optimal inspection times and management strategies for ships, (f) characterization of the dynamic response of ship unloaders and (g) the relationship between vehicles fuel consumption and pavement condition.-> Link to full text in repository
This paper reports on recent contributions by the Marie Skłodowska-Curie Innovative Training Network titled TRUSS (Training in Reducing Uncertainty of Structural Safety) to the field of structural safety in rail and road bridges (http://trussitn.eu). In TRUSS, uncertainty in bridge safety is addressed via cost efficient structural performance monitoring and fault diagnostics methods including: (1) the use of the rotation response due to the traffic traversing a bridge and weigh-in-motion concepts as damage indicator, (2) the combination of design parameters in probabilistic context for geometrical and material properties, traffic data and assumption on level of deterioration to evaluate bridge safety (via Bayesian updating and a damage indicator based on real time measurement), (3) the application of a fuzzy classification technique via feature selection extracted using empirical mode decomposition to detect failure, and (4) the testing of alternative vibration based damage sensitive features other than modal parameters. Progress has also been made in improving modern technologies based on optical fiber distributed sensing, and sensors mounted on instrumented terrestrial and on aerial vehicles, in order to gather more accurate and efficient info about the structure. More specifically, the following aspects have been covered: (a) the spatial resolution and strain accuracy obtained with optical distributed fiber when applied to concrete elements as well as the ideal adhesive, and the potential for detecting crack or abnormal deflections without failure or debonding, (b) the possibility of using the high-resolution measurement capabilities of the Traffic Speed Deflectometer for bridge monitoring purposes and, (c) the acquisition of bridge details and defects via unmanned aerial vehicles. -> Link to full text in academic repository
The growth of cities, the impacts of climate change and the massive cost of providing new infrastructure provide the impetus for TRUSS (Training in Reducing Uncertainty in Structural Safety), a €3.7 million Marie Skłodowska-Curie Action Innovative Training Network project funded by EU’s Horizon 2020 programme, which aims to maximize the potential of infrastructure that already exists (http://trussitn.eu). For that purpose, TRUSS brings together an international, inter-sectoral and multidisciplinary collaboration between five academic and eleven industry institutions from five European countries. The project covers rail and road infrastructure, buildings and energy and marine infrastructure. This paper reports progress in fields such as advanced sensor-based structural health monitoring solutions – unmanned aerial vehicles, optical backscatter reflectometry, monitoring sensors mounted on vehicles, … – and innovative algorithms for structural designs and short- and long-term assessments of buildings, bridges, pavements, ships, ship unloaders, nuclear components and wind turbine towers that will support infrastructure operators and owners in managing their assets. [DOI] -> Link to full text in repository

About WP4. Buildings, Energy and Marine Infrastructure

In recent years the long term durability of reinforced concrete structures has become a major concern. The effect of harsh loading conditions and aggressive environmental factors can lead to corrosion of reinforcing steel in civil engineering applications. This in turn leads to undesired repairs, additional costs and shorter service lives. Advanced composite materials, such as Basalt Fibre Reinforced Polymer (BFRP), have the capacity to significantly address this problem. These materials have enhanced physical properties such as higher mechanical and corrosion resistance, and have the potential to replace traditional steel rebars as tension reinforcement in concrete. There are however limitations that prevent their use on a larger scale, and lack of ductility is the most significant. Braiding techniques could provide the required performance benefits related to the additional ductility and flexibility needed, as well as enhancing the bond between FRP and concrete. If this is achieved, it has the potential to prevent a brittle failure and successfully meet strength, reliability and cost demands. This study focuses on the basics of materials characterization and reliability analysis of internal BFRP reinforcement for concrete structures towards design optimization for structural reliability over their service life. [DOI] -> Link to full text in repository
In recent years, degradation of reinforced concrete (RC) structures due to corrosion of reinforcing steel has become a major concern worldwide. This affects long-term durability, total service life and structural safety of RC elements. Advanced composite materials, such as Basalt Fibre Reinforced Polymer (BFRP), are currently being developed and are showing promising results as a viable alternative to steel in infrastructure applications. More specifically, these materials can offer significant advantages related to both their non-corrodible nature and their enhanced physical and mechanical properties. However, their brittle nature is considered as the main limitation preventing their use on a larger scale. A detailed investigation of manufacturing technologies and design methodologies for the optimum development of BFRP composites, indicates that braiding methods could provide the required performance benefits through increased ductility and flexibility; it can also enhance the bond between FRP and concrete.

This study focuses on exploring the potential of braided Basalt Fibre Reinforced Polymer reinforcement through design optimisation and evaluation of their structural performance. Braided BFRP preforms with different configurations were produced changing key braiding parameters in order to achieve the desired structural geometry and meet the performance characteristics of existing rebar reinforcement. Following from that, successful epoxy resin impregnation trials in regular and spiral configurations confirmed the possibility of manufacturing braided BFRP composites in complex shapes. Moreover, a theoretical numerical approach based on Classical Laminate Theory (CLT) has been developed to determine the stiffness properties of manufactured braided composites, calculating the effective longitudinal in-plane modulus of each braided sample. The relation between geometrical factors and processing conditions on the physical and mechanical properties of the braided rebars was clearly observed. Future plans include assessment of the manufacturing process for improved rebar design, advanced material analysis and characterization tests combined with experimental validation of the developed numerical approach. In addition, finite element analysis (FEA) models will be developed for braided BFRP composites in order to assess the relation between braiding parameters and rebar performance.

In recent years, the development and use of Fibre Reinforced Polymer composite materials in infrastructure have gained increasing attention worldwide. More specifically, natural mineral fibres such as basalt are currently being developed and are showing promising properties. Within an appropriate polymer matrix, their use as reinforcement in concrete structures offers performance benefits related to their environmentally friendly and non-corrodible nature. In particular, BFRPs have the potential to replace conventional internal steel rebar and thus, to be the next generation material in concrete reinforcement applications. A detailed literature review indicates that a careful selection of the appropriate manufacture technique and design methodology are required in order to prevent brittle failure on a concrete structure reinforced with FRP composite material. This paper reports on how to use the additional helical reinforcement and the braid configuration in order to increase strength, structural ductility and long term durability. Moreover, this study outlines the development of an analytical numerical model to predict the longitudinal elastic modulus of braided composites, as well as its validation by comparison of the results with available data from the literature. -> Link to full text in repository
In recent years, significant research has been conducted, by both industry and academia, into the optimum development and use of Fiber Reinforced Polymer composite materials in infrastructure. In particular, it is widely recognised that FRPs have the potential to replace conventional internal steel rebars in concrete reinforcement and offer performance benefits related to their advanced properties, such as corrosion resistance, high tensile strength etc. A review of the available literature indicates that brittle behaviour of FRP can significantly decrease the expected ultimate load capacity and, thus have a negative effect on structure’s long term durability. However, selecting braiding as manufacture technique and enhancing flexural capacity and shear strength through additional helical reinforcement, could provide structure with the additional ductility needed to prevent a brittle failure. Furthermore, the impact of deterioration mechanisms, focusing on the interaction between FRP and concrete in a structure, is an aspect for further investigation via laboratory testing and advanced analysis. This study summarises the results of research on structural design and manufacture methods of FRP composite materials by presenting new configuration and types of FRP reinforcement in order to encourage the use of these promising materials in construction industry. -> Link to full text in repository

For capacity evaluation, the structural assessment of existing structures is necessary. Concrete strength is an important parameter for such assessment. Non-destructive tests (NDTs) are used along with the traditional approach of core testing for strength assessment of concrete in existing structures. The low reliability of NDT results leads to uncertainty in assessing concrete strength. A new method of non-destructive testing is presented in this paper with the aim of achieving better reliability and reducing uncertainty in the assessment of mortar strength. This approach is based on a modified pullout of post-installed screw anchors. The technique involves a pushing mechanism for a steel screw inside the mortar where a void underneath the screw is left to allow for the uninterrupted movement of the screw inside the concrete. The failure pattern involves local crushing of concrete between the threads of the screw. This paper investigates the load bearing behavior of threaded screws installed in cement mortar under compressive loading. The results supports the application of the technique in the assessment of the compressive strength of mortar. The main parameters affecting the pushing behavior are presented and their effects are discussed. It is planned to extend the test program to concrete in the future. -> Link to full text in repository

With more emphasis on reusing and extending the life of structures, it often becomes necessary to assess the capacity of existing concrete structures. One major component of this assessment relates to the concrete strength. Ideally such assessment is carried out without damaging the concrete of the structure. The currently available methods for assessing in-situ concrete strength as a part of capacity evaluation of the existing structures can be broadly divided into two groups. One group of tests is completely non-destructive. The other group is partially destructive where limited damage to the surface is caused by the tests. For the strength evaluation of existing concrete, methods such as surface hardness test, ultrasonic pulse velocity test, penetration resistance test and maturity test fall under the non-destructive category. Partially destructive tests include pull out test, CAPO test, pull off test and break off test. This paper critically evaluates and analyses the applicability and limitations of the methods used for evaluating concrete strength in existing structures. Most methods for strength evaluation are found to measure a certain property such as elasticity, density, tensile strength or hardness of concrete and then relate the measured value to compressive strength. Studies on these methods show a wide variation in the correlations between estimated and predicted compressive strength. Partially destructive methods are noted to provide correlations with good consistency between estimated and predicted compressive strength. -> Link to full text in repository
The computation of the rack seismic response requires an implicit transient analysis with numerical integration of the differential equation of motion. It involves the solution of thousands of time steps throughout the whole earthquake duration. A series of Newton-Raphson trial iterations seek to establish equilibrium within a certain tolerance at each calculation step. The parameters related to such analysis are decisive in the computation of robust and accurate results. This paper carries out a ‘one-factor-at-a-time’ parametric analysis of six key analysis parameters for a simple two-rack system: maximal step size, maximal number of equilibrium iterations, convergence tolerance and Rayleigh and algorithmic damping. This technique examines the impact on the main transient outputs when an analysis parameter is systematically varied while the others remain at their nominal value. Numerical results provide a source of insight into the uncertain seismic response of the rack system and an effective tool to propose an efficient trade-off regarding the computational cost. 

Spent fuel racks are steel structures designed to store the spent fuel assemblies removed from the nuclear power reactor. They rest in free-standing conditions submerged in the depths of the spent fuel pool. During a strong-motion earthquake, racks undergo large displacements subjected to inertial forces. An accurate estimation of their response is essential to achieve a safe pool layout and a reliable structural design. A transient analysis with direct integration of the equation of motion throughout the whole earthquake duration becomes therefore unavoidable. The computational cost associated to this analysis leads to the use of simplified finite element models giving rise to a certain dose of uncertainty. This paper carries out a parametric analysis of the key modelling properties for a two-rack system. This technique examines the behavior of the main transient outputs as a modelling parameter is systematically varied. Numerical results provide a source of insight into the general behavior of the rack system and an effective tool to propose an efficient and reliable modeling and meshing. The trade-off between outputs and computational cost and is also discussed. [DOI] -> Link to full text in repository

High Density Spent Fuel Storage (HDSFS) racks are structures designed to hold nuclear spent fuel assemblies removed from the nuclear power reactor after having been irradiated. They are used in the first step of the waste management process, during the wet storage. The underwater seismic response of HDSFS racks is a troubling safety issue. Since they are 12 m submerged free standing multi-body structures loaded with radioactive fuel, their design remains as complex as crucial. The design deals with a Fluid-Structure Interaction problem, a transient dynamic response and a very highly nonlinear behaviour. Several cost-effective industrial approaches have been used in these calculations to date, but some dispersion of results still exists. Therefore, the regulatory authorities are requiring an evaluation of the uncertainties in the methodology. Equipos Nucleares, S.A. (ENSA) is a worldwide expert in racks design and construction and has recently launched a research project to improve the understanding of the phenomena. The latter is funded by the European Commission and aimed to identify, evaluate and reduce the uncertainties involved in the calculations. In this paper, the state of the art and the current sources of uncertainty are discussed. -> Link to full text in repository
High Density Spent Fuel Storage racks are steel structures designed to hold nuclear spent fuel assemblies removed from the nuclear power reactor. Weighing around 60 tons, they are 5m high free standing structures resting on the floor of a 12 m depth pool and separated by only a few centimetres. Their underwater seismic response is a troubling safety issue, especially after Fukushima nuclear disaster. However, only limited basic guidelines have been provided as regulatory design criteria to date. The racks’ design deals with a very highly nonlinear behaviour, a transient dynamic response and a fluid-structure interaction problem. Industry is currently using available computer-aided finite element analysis software to solve the design problem in a cost-effective manner but some dispersion of results still exists. Hence, the nuclear regulatory authorities are requiring an evaluation of the current uncertainty associated to the assessment of rack displacements, rocking and maximum forces on supports. This paper discusses the main difficulties faced during the seismic analysis and presents an ad-hoc analysis methodology based on the hydrodynamic mass concept which takes advantage of a simplifying thermal analogy. The methodology, implemented in ANSYS FE Mechanical is hereby described for a reduced scale 2-rack model where the coupling effect of water in the dynamic motion of immersed racks is quantified and displacements and forces are provided. Finally, methodology assumptions are discussed and lessons learnt about the behaviour trends are summarized. -> Link to full text in repository

The fatigue design of Offshore Wind Turbines (OWT) is one of the most resource demanding tasks in the OWT design process. Techniques have been developed recently to simplify the amount of effort needed to design to structural fatigue. This is the example of the usage of Kriging surrogate models. These may be used in OWTs design not only, to reduce the computational effort needed to analyse an OWT, but also to allow their design to be robust. Due to the stress variability and its non-linear character, the short-term fatigue damage variability is high, and converging the stochastic field approached by the surrogate model in relation to the real observations is challenging. A thorough analysis of the different components that load an OWT and are more critical for the tower component fatigue life is required, and therefore, presented and discussed in the current paper. The tower, jointly with the foundation, are particular components of the OWT regarding the fatigue analysis process. Statistical assessments of the extrapolation of fatigue loads for the tower and the influence of the environmental parameters in the short-term damage are presented in this paper. This sets a support analysis for the creation of the Kriging response surfaces for fatigue analysis. NREL’s 5MW monopile turbine is used due to its state of the art character. Five environmental variables are considered in the analysis. A sensitivity analysis is conducted to identify which variables are most prominent in the quantification of the short-term damage uncertainty in the tower. The decoupling of the different external contributions for the fatigue life is a major contribution of the work presented. Preliminary guidelines are drawn for the creation of surrogate models to analyse fatigue of OWT towers and the most relevant conclusions are presented in an industry-oriented design outline regarding the most critical random variables that influence OWT short-term fatigue calculation. -> Link to full text in repository

The probabilistic analysis of Offshore Wind Turbines (OWT) is not a new practice. The standards for designing OWT (IEC 61400 class) emphasizes that assessing uncertainty is of major importance inside the design chain. Still, major challenges related to the uncertainty and the probabilistic assessment pose to the sector and its development. The analysis of operational loads is one them. The problem of analyzing extreme responses or cumulated damage in operation during the design phase is significantly related to its high computational cost. As we progressively add complexity to the system to account for its uncertainties, the computational effort increases and a perceptive design becomes a heavy task. If an optimization process is then sought, the designing effort grows even further. In the particular case of fatigue analysis, it is frequent to not be able to cover a full lifetime of simulations due to computational cost restrictions. The mentioned difficulties fomented the utilization of surrogate models in the reliability analysis of OWT. From these surrogate approximations the ones based on Kriging models gained a special emphasis recently for structural reliability. It was shown that, for several applications, these models can be efficient and accurate to approximate the response of the system or the limit state surfaces. The presented paper tackles some of the issues related to their applicability to OWT, in a case specific scenario of the tower component subjected to operational fatigue loads. A methodology to assess the reliability of the tower component to fatigue damage is presented. This methodology combines a Kriging model with the theory of extreme values. A one-dimensional Kriging case using the state of art NREL’s monopile turbine is presented. The reliability of the OWT tower is calculated for 20 years. The results show that the usage of a Kriging model to calculate the long term damage variation shows a high potential to assess the reliability of OWT towers to fatigue failure. -> Link to full text in repository

Offshore wind energy experienced an exponential growth in installed power since the beginning of the current century. While this growing trend is expected to continue, further growth of the sector imposes more demanding engineering methods. It is then envisaged that enhanced technical competitiveness can be achieved through a progressively less deterministic design process. Under the described context, a comparative study on the applicability of different probabilistic methods to estimate the probability of failure (Pf) of offshore wind turbine (OWT) towers under extreme events is presented here. Depending on the complexity introduced in the analysis of the OWT towers the applicability of different probabilistic approaches may be limited. FORM, SORM, Monte Carlo Simulation are examples of well-established methodologies to estimate Pf. Nevertheless, alternative methodologies such as the directional simulation can be an even more efficient solution for the problem. This preliminary assessment of the probabilistic approaches enables further developments in reliability methodologies for the specific case of OWT towers. -> Link to full text in repository

Fatigue cracking is a common problem that needs to be managed in the life cycles of steel structures. Operational inspections and repairs are important means of fatigue crack management. Driven by high relevance in safety control and budget saving, inspection and maintenance planning has been widely studied. However, the value of inspection and repairs has typically not been fully appreciated and quantified rationally before they are implemented. The basic idea of this paper is to address the planning problem with focus on repair other than on inspection. A maintenance strategy without inspection is studied and serves as comparison of a maintenance strategy with inspection. Then the value of repair and the value of inspection relative to repair can be evaluated respectively. An illustrative example is performed on a typical fatigue-prone detail in steel structures. ->

Fatigue cracks threaten integrity of marine and offshore assets and need to be managed properly during the life cycles. However, the decision making process for fatigue design and maintenance are often disconnected and probably not be optimal with respect to life cycle total costs. This paper proposes a holistic decision support tool for jointly optimizing fatigue design, inspection and maintenance decision based on risk quantification and life cycle cost analysis, taking into account the uncertainties associated with fatigue deterioration, inspection performance and repair effect. The tool can be used to support risk-informed fatigue design; inspection and maintenance decision making, so that fracture risk associated with design and operation of marine assets are controlled with the minimum life cycle total costs. ->Link to full text in repository

Efficient inspection and maintenance are important means to enhance fatigue reliability of engineering structures, but they can only be achieved efficiently with the aid of accurate pre-diction of fatigue crack initiation and growth until fracture. The influence of crack initiation on fatigue life has received a significant amount of attention in the literature, although its im-pact on the inspection plan is not generally addressed. Current practice in the prediction of fatigue life is the use of S-N models at the design stage and Fracture Mechanics (FM) models in service. On the one hand, S-N models are relatively easy to apply given that they directly relate fatigue stress amplitude to number of cycles of failure, however, they are difficult to extrapolate outside the test conditions employed to define the S-N curves. On the other hand, FM models like the Paris propagation law give measurable fatigue damage accumulation in terms of crack growth and have some ability to extrapolate results outside the test conditions, but they can only be a total fatigue life model if the initial crack size was known given that they do not address the crack initiation period. Furthermore, FM models generally introduce large uncertainties in parameters that are often difficult to measure such as initial crack size, crack growth rate, threshold value for stress intensity factor range, etc. This paper proposes a modified FM model that predicts the time to failure allowing for crack initiation period. The main novelty of the modified FM model is the calibration using S-N data (i.e., inclusive of crack initiation period) for an established criterion in fatigue life and reliability level. Sources of uncertainty associated to the model are quantified in probabilistic terms. The modified FM model can then be applied to reliability-based inspection planning. An illustrative example is performed on a typical detail of ship structure, where the optimum inspection plan derived from the proposed model is compared to recommendations by existing FM models. Results demonstrate to what extent is the optimum inspection plan influenced by the crack initiation period. The modified model is shown to be a reliable tool for both fatigue design and fatigue management of inspection and maintenance intervals. -> Link to full text in repository

A problem with fracture mechanics (FM) based fatigue analysis is that reliable information on initial crack/flaw size is often hard to obtain. Also, FM method can’t be applied directly to welded joints with relatively small initial flaws and long crack initiation life. This paper proposes a novel probabilistic FM method based on the equivalent initial flaw size (EIFS) concept. The initial crack size is substituted with EIFS to take both the crack initiation and propagation life into account. Three methods are tested to obtain mean value of EIFS: calibrating to S-N curves, Kitagawa-Takahashi (KT) diagram and fitting to test data. The obtained EIFSs are evaluated by comparing the predicted fatigue lives and crack evolutions with S-N curves and test crack evolution data. The suggested procedure is to derive the mean value of EIFS from S-N curves and the coefficient of variation from KT diagram. -> Link to full text in repository

Fatigue cracks pose threats to the integrity of welded structures and thus need to be addressed in the whole service lives of structures. In-service inspections are important means to decease the probability of failure due to uncertainties that cannot be accounted for in the design stage. To help schedule inspection actions, the decline curve of reliability index with time needs to be known. A predictive tool is normally developed based on crack propagation models neglecting the crack initiation stage, which leads to conservative predictions for fatigue life. Inspection plans built on those predictions are far from optimal, especially for welds with relatively long crack initiation life. This paper proposes to use a fracture mechanics based reliability analysis method that takes the crack initiation stage into account via the concept of Time-To-Crack-Initiation (TTCI). The optimum inspection plan for a fatigue prone ship structural component is derived by the new approach and compared to the commonly-used method that only considers crack propagation life. Two inspection planning approaches are tested to investigate the influence of incorporating crack initiation period: (i) target reliability approach and, (ii) equidistant inspection times approach. With each planning approach, two inspection methods are adopted: close visual and magnetic particle inspection. The paper concludes with recommendations on the inspection method and planning approach to adopt while considering and without considering the crack initiation stage. [DOI] -> Link to full text in repository

Crack initiation and propagation threatens structural integrity of welded joints and normally inspections are assigned based on crack propagation models. However, the approach based on crack propagation models may not be applicable for some high-quality welded joints, because the initial flaws in them may be so small that it may take long time for the flaws to develop into a detectable size. This raises a concern regarding the inspection planning of high-quality welded joins, as there is no generally acceptable approach for modeling the whole fatigue process that includes the crack initiation period. In order to address the issue, this paper reviews treatment methods for crack initiation period and initial crack size in crack propagation models applied to inspection planning. Generally, there are four approaches, by: 1) Neglecting the crack initiation period and fitting a probabilistic distribution for initial crack size based on statistical data; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modeled by crack propagation models; 3) Assuming a fixed detectable initial crack size and fitting a probabilistic distribution for crack initiation time based on specimen tests; and, 4) Modeling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. The conclusion is that in view of trade-off between accuracy and computation efforts, calibration of a small fictitious initial crack size to S-N curves is the most efficient approach. -> Link to full text in repository
Container cranes represent an important link in the maritime transport system. Assessment of residual life for such cranes is important both in terms of safety and cost of repair and maintenance. These cranes usually have a hoisting trolley system which can move along the boom for lifting, carrying and lowering the payload, loading/unloading vessels in the harbour. This paper investigates the dynamic response of the lifting boom using a non-linear finite element analysis. A number of such moving trolley systems, with different degrees of complexity, are modelled to assess the impact of their influence on the boom dynamic response parameters. Results from the finite element analysis are compared to a pseudo-static analysis and are presented in terms of a Dynamic Response Factor (DRF).-> Link to full text in repository
This paper highlights the impact of dynamic amplification factors in remaining fatigue life assessment of ship unloaders. In practice, the widely accepted procedure for these structures is to carry out a fatigue life assessment envisages: (1) carrying out static analysis, (2) taking into account dynamics via the application of dynamic amplification factors, and (3) applying Miner’s rule. This factor, provided by the standard, is applied to the structure as a whole without considering the vibration of each structural member individually. This paper characterizes the dynamic behavior of each element using location-based dynamic amplification factors estimated from measurements. This caters for a more accurate assessment of the structure, whilst maintaining the simplicity of the standard procedure. [DOI] -> Link to full text in repository
This paper reviews methodologies for fatigue analysis with emphasis on ship unloaders. Maintaining the performance of ship unloaders at a satisfactory level is essential for any port’s operation in order to comply with the global demand of shipping and trading. Ship unloaders are subject to alternating operational loadings and to adverse environmental conditions, and as a result, they show a rapid rate of deterioration that makes them susceptible to failure by cumulative damage processes such as corrosion and fatigue. The purpose of this paper is to review key features of the most common methodologies for fatigue analysis and to underline the limitations and uncertainties involved. Finally, developments in reliability-based approaches are suggested for a more accurate fatigue assessment of ship unloaders. -> Link to full text in repository
This paper reviews the most common causes of failure in ship unloaders. The structural forms employed in the design of ship unloaders and the characteristics of the loads acting on these structures are introduced first. Then, typical failures including overloading, joint failure, cable breaking, corrosion and fatigue failure amongst others, are described. Fatigue failure is discussed in further detail. When assessing a ship unloader for fatigue, it is necessary to define the fatigue demand and the fatigue strength capacity of those structural details under investigation. The latter experiences stress cycles that accumulate over time until reaching a limit that leads to cracking. Loads and stresses need to be monitored to describe those cycles, and critical locations must be checked to prevent a catastrophic failure. -> Link to full text in repository

About WP5. Rail and Road Infrastructure

Monitoring displacement of in operation bridges is practically challenging but potentially very useful for condition assessment and decision support. The primary difficulties are in finding fixed physical reference points and, for the majority short span bridges under normal operation, the mm-level magnitudes of displacement under normal operating conditions (e.g. standard truck loading). With rare possibility for physical connection between a reference and a bridge, non-contacting technologies such as GPS need to be used. Other options include total station and more exotic technologies of laser interferometer and radar have also been tried. There are drawbacks for each technology related to limited sample rate (for total station) and signal to noise ratio (for GPS) while radar and laser are expensive and require specialist users. With advances in computing power, optics-based systems are becoming popular, relying on a standard lens but with capability to track multiple positions with potential to recover deformation with high spatial resolution. This paper reports the experiences of the authors exploring the suitability of a commercially available optics-based system in terms of spatial and temporal resolution and sampling and in challenging field conditions required for long term monitoring. For example issues such as stability of camera mounting (e.g. in wind) and varying lighting conditions while not problematic in a laboratory govern performance in the field. The paper tracks a sequence of experiments moving from lab to field, ultimately moving up to a field test on a road bridge in Devon. In each case the capabilities and limitations of the system have been critically examined. The study has defined both limitations and capabilities, while defining best approaches for use and at the same time providing some useful performance data on the subject bridges. 
This paper showcases the importance of field testing in efforts to deal with the deteriorating infrastructure. It demonstrates a load test performed on a healthy but aging composite reinforced concrete bridges in Exeter, UK. The bridge girders were instrumented with strain transducers and static strains were recorded while a four-axle, 32 tonne lorry remained stationary in a single lane. The results obtained from the field test were used to calculate transverse load distribution factors (DFs) of the deck structure for each loading case. Additionally, a 3-D finite element model of the bridge was developed and calibrated based on field test data. Similar loading cases were simulated on the analytical model and behaviour of the structure under static loading was studied. It was concluded that the bridge support conditions had changed throughout its service life, which affected the superstructure load distribution characteristics. Finally, DFs obtained from analysis were compared with factors provided in Design Manual for Roads and Bridges Standard Specification for similar type of bridges. -> Link to full text in repository

Probabilistic assessment of ageing bridges has become an important research area as it interests not only researchers but investors, municipalities and even governments. In this paper a simple bridge model is presented in a probabilistic context. A comparative study is carried out involving damage indicators and Bayesian updating. Bayesian updating is a powerful tool, which has been used in various research areas. However, using it for approximating the safety level of a bridge is challenging due to the various sources of uncertainties that may affect the performance of a measurement based damage indicator. The effects of different factors involved in the updating are examined in this paper and compared. [DOI] -> Link to full text in repository

Probabilistic assessment of bridges has been the subject of various studies in recent decades. It has been widely agreed that evaluating an existing bridge according to the standards and codes used for new structures can lead to demolition of a safe bridge or unnecessary repairs, and thus to high economic cost and an increase in the associated environmental impact. This paper investigates several concerns, the sensitivities of and correlation between the different stochastic parameters influencing the load on a bridge and its resistance to that load. The usefulness of updating the bridge safety model using damage indicators from a Structural Health Monitoring system is also examined.

The proposed approach combines a number of aspects. Firstly, a probabilistic bridge load model is established based on Weigh-In-Motion (WIM) data to mimic a realistic traffic flow and hence, the loads and their effects on the bridge. Traffic loading is highly correlated as the same vehicles influence many parts of the bridge. This has a significant influence on the probability of failure.

To model the resistance of the bridge a probabilistic approach is used and full correlation between segments is assumed. Combining the load and resistance models, the probability of failure can be inferred. In the future work the bridge safety model, more precisely the resistance model, will be updated. Bayesian updating will be used in the current framework based on the information obtained from specific damage indicators.

This study aims at obtaining valuable information regarding the importance of the different aspects of bridge safety models and the sensitivity of the probability of failure (i.e. the level of safety) to them. It is also expected to confirm the applicability of a Bayesian approach to this problem. -> Link to full text in repository

The UK railway network is subjected to an electrification process that aims to electrify most of the network by 2020. This upgrade will improve the capacity, reliability and efficiency of the transportation system by providing cleaner, quicker and more comfortable trains. During this process, railway infrastructures, such as tunnels, require to be adapted in order to provide the necessary clearance for the overhead line equipment, and consequently, a rigorous real-time health monitoring programme is needed to assure safety of workforce. Large amounts of data are generated by the real-time monitoring system, and automated data mining tools are then required to process this data accurately and quickly. Particularly, if an unexpected behaviour of the tunnel is identified, decision makers need to know: i) activities at the worksite at the time of movement occurring; ii) the predicted behaviour of the tunnel in the next few hours.

In this paper, we propose a data mining method which is able to automatically analyse the database of the real-time recorded displacements of the tunnel by detecting the unexpected tunnel behaviour. The proposed tool, first of all, relies on a step of data pre-processing, which is used to remove the measurement noise, followed by a feature definition and selection process, which aims to identify the unexpected critical behaviours of the tunnel. The most critical behaviours are then analysed by developing a change-point detection method, which detects precisely when the tunnel started to deviate from the predicted safe behaviour. Finally, an Artificial Neural Network (ANN) method is used to predict the future displacements of the tunnel by providing fast information to decision makers that can optimize the working schedule accordingly. -> Link to full text in repository

More than 35% of the European railway bridges are over 100 years old and the increasing traffic loads are pushing the railway infrastructure to its limits. Bridge condition-monitoring strategies can help the railway industry to improve safety, availability and reliability of the network. In this paper, a Bayesian Belief Network method for condition monitoring and fault detection of a truss steel railway bridge is proposed by relying on a fuzzy analytical hierarchy process of expert knowledge. The BBN method is proposed for obtaining the bridge health state and identifying the most degraded bridge elements. A Finite Element model is developed for simulating the bridge behaviour and studying a degradation mechanism. The proposed approach originally captures the interactions existing between the health state of different bridge elements and, furthermore, when the evidence about the displacement is introduced in the BBN, the health state of the bridge is updated. -> Link to full text in repository

More than 350,000 railway bridges are present on the European railway network, making them a key infrastructure of the whole railway network. Railway bridges are continuously exposed to changing environmental threats, such as wind, floods and traffic load, which can affect safety and reliability of the bridge. Furthermore, a problem on a bridge can affect the whole railway network by increasing the vulnerability of the geographic area, served by the railway network. In this paper a Bayesian Belief Network (BBN) method is presented in order to move from visual inspection towards a real time Structural Health Monitoring (SHM) of the bridge. It is proposed that the health state of a steel truss bridge is continuously monitored by taking account of the health state of each bridge element. In this way, levels of bridge deterioration can be identified before they become critical, the risk of direct and indirect economic losses can be reduced by defining optimal bridge maintenance works, and the reliability of the bridge can be improved by identifying possible hidden vulnerabilities among different bridge elements. -> Link to full text in repository

Bridges are one of the most critical structures of the railway system. External loads may affect the bridge health state, and consequently their safety, availability and reliability can be improved by monitoring their condition and planning maintenance accordingly. In this paper, a Bayesian Belief Network (BBN) fault detection methodology for a truss steel railway bridge is proposed. The BBN is developed to assess the health state of the whole bridge using evidence about the behaviour of the bridge. In this initial study, the evidence is provided in terms of the values of displacement computed by a Finite Element model. -> Link to full text in repository

Over the years, there have been numerous efforts by researchers in quantifying structural degradation and damage from vibration measurements. Traditionally, damage detection techniques in bridges have focused on the use of modal-based damage indicators, such as frequencies, mode shapes and mode shape derivatives. However, these parameters have been shown to be sensitive to environmental and operational variations and can be difficult to accurately extract under low-level ambient excitation. Recent research has found a correlation between certain vibration parameters, such as vibration intensity, and a group of damage bridges, suggesting that vibration parameters may detect damage if extracted correctly. The present study furthers these findings by examining a number of vibration parameters as damage indicators to discern their sensitivity to various condition states of a progressively damaged bridge under ambient excitation.[DOI] -> Link to full text in repository

The assessment of bridge condition from vibration measurements has generally been determined via the monitoring of modal parameters determined though adaptations of the standard Fast Fourier Transform (FFT) or other stationary time-series based transformations. However, the non-stationary nature of measured vibration signals from damaged structures can limit the quality of frequency content information estimated by such methods. The Hilbert–Huang Transform’s (HHT) ability to decompose non-stationary measured vibration data into a time-frequency-energy representation allows signal variations to be identified sooner than other stationary-based transformations, thus potentially allowing early detection of damage. The present study uses data obtained from a progressive damage test conducted on a real bridge subjected to excitation from a double axle passing vehicle as a test subject. Decomposed vibration signals from the HHT and associated marginal spectrums are assessed to determine structural condition for various damage states and different locations along the bridge. [DOI] -> Link to full text in repository

Overtime, the structural condition of bridges tends to decline due to a number of degradation processes, such as; creep, corrosion and cyclic loading, among others. Considerable research has been conducted over the years to assess and monitor the rate of such degradation with the aim of reducing structural uncertainty. Traditionally, vibration-based damage detection techniques in bridges have focused on monitoring changes to modal parameters and subsequently comparing them to numerical models. These traditional techniques are generally time consuming and can often mistake changing environmental and operational conditions as structural damage. Recent research has seen the emergence of more advanced computational techniques that not only allow the assessment of noisier and more complex data, but also allow research to veer away from monitoring changes in modal parameters alone. This paper presents a review of the current state-of-the-art developments in vibration based damage detection in small to medium span bridges with particular focus on the utilization of advanced computational methods that avoid traditional damage detection pitfalls. A case study of the S101 Bridge is also presented to test the damage sensitivity a chosen methodology. Finally, in the evaluation of the shear crack pattern, not only crack initiation and location are of importance, but also crack width, shear crack angles and shear sliding displacements along the cracks have to be measured to evaluate the shear performance of a structural element. -> External link to full text -> Link to full text in repository
Overtime, the structural condition of bridges tends to decline due to a number of degradation processes, such as; creep, corrosion and cyclic loading, among others. Considerable research has been conducted over the years to assess and monitor the rate of such degradation with the aim of reducing structural uncertainty. Traditionally, damage detection techniques in bridges have focused on monitoring changes to modal parameters and subsequently comparing them to numerical models. These traditional techniques are generally time consuming and can often mistake changing environmental and operational conditions as structural damage. Recent research has seen the emergence of more advanced computational techniques that not only allow the assessment of noisier and more complex data, but also allow research to veer away from monitoring changes in modal parameters alone. This paper presents a review of the current state-of-the-art developments in vibration based damage detection in small to medium span bridges with particular focus on the utilisation of advanced computational methods, such as machine learning, pattern recognition and advanced data normalisation algorithms. -> Link to full text in repository
Over the years, there have been numerous efforts by researchers in quantifying structural performance and damage from vibration measurements. Curves proposed by several authors (Koch 1953, Steffens 1974) attempt to relate acceleration spectrums to damage level, which were determined based on experimental surveys conducted on buildings. The technique is focused on the use of vibration intensity, which is a function of acceleration amplitude and frequency, as a parameter to discern damage. Recently, some Codes have adopted vibration intensity criteria for evaluating damage, such as the Brazilian Code for non-destructive testing ABNT-NBR-15307 (2005), which reproduces Koch’s criteria for any kind of structure, including bridges. It states that vibration intensity is an empiric parameter used to estimate damage levels in structures, and can be ex-pressed in units known as vibrars. According to the Brazilian Code, there exists an empirical relationship between the values of vibrars and the level of structural damage: 10-30 (None), 30-40 (Small), 40-50 (Severe) and 50-60 (Failure) (ABNT,2005).

The present work investigates the use of vibrars and maximum peak-to-peak accelerations as parameters of damage and performance evaluation in existing bridges and also as a way to predict long-term performance during the initial design stage. To achieve this, a database of the most common Brazilian bridge types was analyzed, whose structural design and dynamic parameters are known. Measured traffic data and material properties were integrated into calibrated FEA models and a fatigue assessment was conducted.

A damage index compiled by Kim et al. (2005) was used to assess damage based on dynamic property variation and the general structural condition of the bridges, observed during detailed inspections. Measured vibration was subsequently assessed against the damage index and an additional reliability index to assess the bridges’ fatigue safety. This resulted in a clear correlation between maximum peak-to-peak accelerations and the indices; however, vibration intensity, measured in vibrars as suggested by ABNT-NBR-15307 (2005), did not produce good correlation with the indices. Not only worse correlation was observed in the case of vibrars, but also a tendency of damage decreasing with increasing vibrars, which is not reasonable. As a final result, from the observed correlations, limits of maximum peak-to-peak acceleration are proposed to be considered in existing and newly designed bridges to certify an acceptable long-term condition and safety against fatigue effects. -> Link to full text in repository

Associacao Brasileira de Normas Tecnicas – ABNT 2005. Ensaios não destrutivos – Provas de cargas dinâmicas em grandes estruturas – Procedimento. NBR 15307.
Kim, T.H., Lee, K.M., Chung, Y.S. & Shin, H.M. 2005. Seismic damage assessment of reinforced concrete bridge columns. Engineering Structures. Vol.27, No.11, pp 576-592.
Koch, H.W. 1953. Determining the effects of vibration in buildings, V.D.I.Z., Vol. 25, N. 21, pp. 744-747.
Steffens, R.J. 1974. Structural vibration and damage. – Building Research Establishment. London.

In this paper, an experiment where distributed optical fiber sensors (DOFS) were implemented in two small concrete beams subjected to a three-point load test is outlined. Here, an optical backscatter reflectometry based DOFS is implemented simultaneously embedded in the concrete (glued to the steel rebar) and attached to the outer surface of the concrete after its hardening. For comparison purposes, three electrical strain gauges are also used in the rebar. The main objectives with this experiment, is to analyze the feasibility of installation of DOFS directly on the rebar element of a reinforced concrete beam and compare the measured strain at rebar and surface of the concrete. -> Link to full text in repository

In this work, an experiment on two small concrete beams is described where Rayleigh based distributed optical fiber sensors (DOFS) are implemented together with traditional electrical strain gauges for the monitoring of these elements during a three-point load test. Part of the DOF sensor is embedded without protective coating directly in the rebar inside the concrete, being the remaining fiber glued to the surface of the element after the concrete hardening. This allows the direct comparison between the developed strains on the surface of concrete and the rebar with the use of a single sensor. Moreover, two types of adhesives are studied and then compared. From all the possible distributed sensing techniques, the Rayleigh based Optical Frequency Domain Reflectometer (OFDR) is the one which enables the better spatial resolution without the need of post-processing algorithms. In this way, in this experiment, this is going to be the used sensing technique. [DOI]
In the past decade, several works and studies have been performed with the goal of improving the knowledge and developing new techniques associated with the application of Distributed Optical Fiber Sensors (DOFS) in order to widen the range of applications of these sensors and also to obtain more correct and reliable data. In this document, after a very brief introduction to the fundamentals of this technology, the most representative work being developed at UPC—BarcelonaTech with the use of these sensors is going to be described. These applications range from laboratory experiments to real world structures monitoring scenarios where different challenges and particular issues had to be overthrown in each one of them. Furthermore, the most recent laboratory experiment performed by this group where DOFS were deployed is going to be described in greater detail. [DOI] -> Link to full text in repository
In the present paper, a novel technique is used to monitor and evaluate shear crack patterns in Partially Prestressed Concrete (PPC) beams. The proposed technique is based on experimental data obtained in two PPC beams tested in laboratory and instrument-ed by Distributed Optical Fiber Sensors (DOFS). The DOFS conform optical fiber grids bonded in the surfaces of the beams. The DOFS experimental data were obtained using an OBR (Optical Backscattered Reflectometer) system that provides continuous strain data with high spatial resolution and cracks can be characterized. The continuous (in space) monitoring of the strain along the DOFS, including the crossing of a crack provides additional information without requiring prior knowledge of the cracked zone.

Several experiences have demonstrated the feasibility of using OFDR theory and SWI technique in the structural monitoring of concrete structures (Villalba and Casas 2013, Rodriguez et al 2015). In the specific case of detection, location and control of cracking in concrete structures, OBR system is an attractive monitoring tool. In the evaluation of shear crack pattern, the inclination of the cracking pattern is an additional unknown property. Two PPC beams named I1 and I2, were tested using DOFS grids as measuring alternative to check the proposed structural monitoring method.

According to the preliminary results obtained in this paper, the use of DOFS is a feasible methodology to obtain important information in the study of shear structural behavior in concrete structures. Continuous strain data at different loading levels were obtained with high spatial resolution by OBR system. Using this data, detection and location of flexural and shear cracks were obtained without requiring prior knowledge of the cracked zone.

Finally, in the evaluation of the shear crack pattern, not only crack initiation and location are of importance, but also crack width, shear crack angles and shear sliding displacements along the cracks have to be measured to evaluate the shear performance of a structural element. -> Link to full text in repository

Villalba S. and Casas J. 2013. Application of optical fiber distributed sensing to health monitoring of concrete structures. Mechanical Systems and Signal Processing, 441-451.
Rodríguez G., Casas J., and Villalba S. 2015. Cracking assessment in concrete structures by distributed optical fiber. Smart Materials and Structures, 24, 1-11.

It’s widely recognized that during its lifetime, civil engineering structures are subjected to adverse changes that affect their condition and structural safety. These changes are due to several factors such as damage and deterioration induced by environmental aggressions, design and/or construction errors, overloading, not expected events such as earthquakes or simply due to the normal degradation associated with the normal use of the structure through their working life. In this way, the application of Structural Health Monitoring (SHM) systems to these civil engineering structures has been a developing studied and practiced topic, that has allowed for a better understanding of structures’ conditions and increasingly lead to a more cost-effective management of those infrastructures.

In this field, the use of fiber optic sensors has been studied, discussed and practiced with encouraging results. These sensors present several advantages when compared with the more traditional and used electric sensors, such as their immunity to electromagnetic interferences and corrosion, their ability to withstand high temperatures and their small dimensions and light weight just to name a few. Furthermore, with distributed fiber optic technology it’s possible to measure virtually any point along a single fiber allowing for truly distributed sensing measurements with great spatial resolution. The possibility of understanding and monitor the distributed behaviour of extensive stretches of critical structures it’s an enormous advantage that distributed fiber optic sensing provides to SHM systems. These distributed fiber optic sensors (DOFS) when bonded or embedded in the structural material works as its nervous system and for all these reasons, it is acknowledged as the most promising fiber optic sensing technique.

In the past decade, several R&D works have been performed with the goal of improving the knowledge and developing new techniques associated with the application of DOFS in order to widen the range of applications of these sensors and also to obtain more correct and reliable data. This paper presents, after a brief introduction to DOFS, the latest developments related with the improvement of these products as long as a review of their diverse applications on structural health monitoring with special focus on engineering structures. -> External link to publisher’s version -> Link to full text in repository

Two different existing structures monitored with distributed optical fiber sensors, are described in this paper. The principal Structural Health Monitoring (SHM) results of a valuable hospital rehabilitation (Sant Pau Hospital) and the enlargement of a prestressed concrete bridge (Sarajevo bridge), are presented. The results are obtained using a novel Distributed Optical Fiber Sensor system (DOFSs) based on an Optical Backscattered Reflectometry (OBR) technique. The versatility and easy installation of DOFSs compared with traditional monitoring systems is an important characteristic to consider its application in monitoring real world structures. The DOFS used in this study provide continuous (in space) strain data along the optical fiber with high spatial resolution in order of centimeters. Also and because the structural surfaces generally are roughness, the procedure to attach the optical fiber to two monitored structures are described. This is an important aspect because the influence in strain transfer between the DOFS and the surface is one of the principal parameters that should be considered in the application of the OBR technique.

Numerous works presenting information regarding the study of the potential of these sensors have been published in the last decade (Rodríguez et al. 2015 a,b; Palmieri & Schenato 2013) but very few showcase their application to real world structures. One of the various advantages of this technology is the easy installation to real life structures and the variety of them that can be instrumented with it. In both studied instrumentations the used fiber is based on a type of fiber optic in which the wavelength is established and compatible with a commercial data acquisition system. Each section of optical fiber has a maximum length of 50 meters and the union between the fiber and structural element (concrete/masonry) was performed using a twocomponent type epoxy adhesive. A coating of a polymer (polyimide) was used to protect the fiber against scratches and environmental attack.

Due to their particularities, each one of these structures underwent changes in their structural behavior without, nevertheless, ceasing to serve their purpose, i.e. accommodating patients in the case of the Sant Pau Hospital and the passage of vehicles and pedestrians in the case of Sarajevo bridge thanks to the application of these sensors. With the results obtained in this work, the OBR theory associated with DOFS proved its reliability in SHM of civil engineering applications and continues to showcase the promising future of monitoring systems based on this technology. -> Link to full text in repository

Palmieri, L. & Schenato, L., 2013. Distributed optical fiber sensing based on Rayleigh scattering. The Open Optics Journal, 7(1).
Rodríguez, G., Casas, J.R. & Villaba, S., 2015. Cracking assessment in concrete structures by distributed optical fiber. Smart Materials and Structures, 24(3), p.35005.
Rodríguez, G., Casas, J.R.. & Villalba, S., 2015. SHM by DOFS in civil engineering : a review. Structural Health Monitoring and Maintenance, 2(4), pp.357–382.

 The aim of this paper is to present the latest developments in the use of an instrumented vehicle called the Traffic Speed Deflectometer (TSD). A large axle load is applied to the pavement under the TSD. The deflection caused by this axle load is measured using several Doppler lasers. In the first step, the velocity of the deflection of the pavement is measured which can be shown to be proportional to the slope of the deformed profile. The pavement deflection is calculated in the second step using an integration model. A Winkler model is used to simulate the pavement behaviour under the axle load and the TSD is represented as a half-car model. The TSD is shown to be an effective tool for pavement damage detection. -> Link to full text in repository 

The aim of this paper is to present the latest developments in the use of an instrumented vehicle called the Traffic Speed Deflectometer (TSD). A large axle load is applied to the pavement under the TSD. The deflection caused by this axle load is measured using several Doppler lasers. In the first step, the velocity of the deflection of the pavement is measured which can be shown to be proportional to the slope of the deformed profile. The pavement deflection is calculated in the second step using an integration model. A Winkler model is used to simulate the pavement behaviour under the axle load and the TSD is represented as a half-car model. The TSD is shown to be an effective tool for pavement damage detection. -> Link to full text in repository

Among all the Structural Health Monitoring (SHM) recent methods found in literature, drive by monitoring has demonstrated to be promising for damage detection purposes, particularly in bridges. As curvatures can be derived from displacement measurements taken by this method, they can also be used for damage detection, which has already been successfully demonstrated. This paper describes the use of Instantaneous Curvature (IC) for that purpose. Once the absolute displacements of the bridge are measured, damage location and quantification can be obtained through IC when having a moving reference over a bridge. In this paper, a bridge is represented by a finite element model of a Euler-Bernoulli beam. A Half-Car model of a vehicle is used to represent a Traffic Speed Deflectometer (TSD), a drive-by monitoring vehicle. Damage is represented as a loss of stiffness in different parts of the bridge and 1 % measurement noise is added. A generic road profile is also considered. Healthy and damaged states of the bridge are compared in order to validate the method. -> Link to full text in repository
The Traffic Speed Deflectometer (TSD) is a vehicle incorporating a set of laser Doppler vibrometers on a straight beam to measure the relative velocity between the beam and the pavement surface. This paper describes a numerical study to see if a TSD could be used to detect damage in a bridge. From this measured velocity it is possible to obtain the curvature of the bridge, from whose analysis, it will be demonstrate that information on damage can be extracted. In this paper a Finite Element model is used to simulate the vehicle crossing a single span bridge, for which deflections and curvatures are calculated. From these numerical simulations, it is possible to predict the change in the curvature signal when the bridge is damaged. The method looks promising and it suggests that this drive-by approach is more sensitive to damage than sensors installed on the bridge itself. -> Link to full text in repository
Considerable effort has been dedicated in recent years to the development of bridge damage detection techniques. Recently, drive-by monitoring has become popular as it allows the bridge to be monitored without installing sensors on it. In this work, the Traffic Speed Deflectometer (TSD), which incorporates a set of laser Doppler sensors on a straight beam to obtain the relative velocity between the vehicle and the pavement surface, is modelled to obtain deflections on the bridge as the vehicle drives. From these deflections it is possible to obtain the curvature of the bridge, from which inferences on damage can be made. However, most of the time, the measurements taken by drive-by sensors are subject to a set of uncertainties or noise that can lead the damage detection procedure to either give false positives or to miss damage. For that reason, an analysis is needed in order to determine if these methods can work properly in uncertain or noisy environments. Moreover, as the road surface roughness affects the dynamic interaction between the vehicle and the bridge, this may also have an effect on the damage predictions. Hence, the goal of this paper is to study the sensitivity of curvature measurements to both the presence of environmental noise and the effect of the road surface roughness. -> Link to full text in repository
Drive-by monitoring has received increasing attention in recent years, as it has great potential useful for Structural Health Monitoring (SHM) applications. Although direct instrumentation of civil infrastructures has been demonstrated to be a way of detecting damage, it is also a very expensive method as it requires data acquisition, storage and transmission facilities on each bridge. Drive-by constitutes an alternative that allows the monitoring of a bridge without the necessity of installing sensors on it. In this numerical study, the vertical displacements of the bridge are used for damage detection purposes. The goal of this paper is to describe a model that can reproduce the vertical displacements of the bridge when a simulated vehicle is driving through and show how these displacements change with damage. Vertical displacements are calculated before and after damage, so that the sensitivity of the data to bridge damage can be determined.

A finite element (FE) model of a simply supported beam interacting with a moving half car is used in this study. Damage is represented as a loss of stiffness in several parts of the bridge. Vertical displacements are generated at a moving reference for healthy and damaged states, corresponding to vehicle location on the bridge. Two options are explored, the first axle and the second one, as the locations to fix the simulated sensor on the vehicle. -> Link to full text in repository

Considering data from 260 articulated trucks, with ∼12900 cc Euro 6 engines driving along a motorway in England (M18), the study first shows how different approaches lead to the conclusion that road pavement surface conditions influence fuel consumption of the considered truck fleet. Then, a multiple linear regression for the prediction of fuel consumption was generated. The model shows that evenness and macrotexture can impact the truck fuel consumption by up to 3% and 5%, respectively. It is a significant impact which confirms that, although the available funding for pavement maintenance is limited, the importance of limiting GHG emissions, together with the economic benefits of reducing fuel consumption are reasons to improve road condition (Zaabar & Chatti, 2010). [DOI] -> Link to full text in repository

In Europe, the road network is the most extensive and valuable infrastructure asset. In England, for example, its value has been estimated at around £344 billion and every year the government spends approximately £4 billion on highway maintenance (House of Commons, 2011).

Fuel efficiency depends on a wide range of factors, including vehicle characteristics, road geometry, driving pattern and pavement condition. The latter has been addressed, in the past, by many studies showing that a smoother pavement improves vehicle fuel efficiency. A recent study estimated that road roughness affects around 5% of fuel consumption (Zaabar & Chatti, 2010). However, previous studies were based on experiments using few instrumented vehicles, tested under controlled conditions (e.g. steady speed, no gradient etc.) on selected test sections. For this reason, the impact of pavement condition on vehicle fleet fuel economy, under real driving conditions, at network level still remains to be verified.

A 2% improvement in fuel efficiency would mean that up to about 720 million liters of fuel (~£1 billion) could be saved every year in the UK. It means that maintaining roads in better condition could lead to cost savings and reduction of greenhouse gas emissions.

Modern trucks use many sensors, installed as standard, to measure data on a wide range of parameters including fuel consumption. This data is mostly used to inform fleet managers about maintenance and driver training requirements. In the present work, a ‘Big Data’ approach is used to estimate the impact of road surface conditions on truck fleet fuel economy for many trucks along a motorway in England. Assessing the impact of pavement conditions on fuel consumption at truck fleet and road network level would be useful for road authorities, helping them prioritize maintenance and design decisions. -> Link to full text in repository

Experimental studies have estimated the impact of road surface conditions on vehicle fuel consumption to be up to 5% (Beuving et al., 2004). Similar results have been published by Zaabar and Chatti (2010). However, this was established testing a limited number of vehicles under carefully controlled conditions including, for example, steady speed or coast down and no gradient, amongst others. This paper describes a new “Big Data” approach to validate these estimates at truck fleet and route level, for a motorway in the UK. Modern trucks are fitted with many sensors, used to inform truck fleet managers about vehicle operation including fuel consumption. The same measurements together with data regarding pavement conditions can be used to assess the impact of road surface conditions on fuel economy. They are field data collected for thousands of trucks every day, year on year, across the entire network in the UK. This paper describes the data analysis developed and the initial results on the impact of road surface condition on fuel consumption for journeys of 157 trucks over 42.6km of motorway, over a time period of one year. Validation of the relationship between road pavement surface condition and vehicle fuel consumption will increase confidence in results of LCA analyses including the use phase. [DOI] -> Link to full text in repository

This paper introduces a three-dimensional reconstruction experiment based on a physical laboratory-based experiment on a brick wall. Using controlled shooting distances and angles, different images sets were captured and processed with a structure from motion based technique, which can reconstruct 3D models based on multi-view, Two-Dimensional (2D) images. Those 2D geometries are shown to generate significant deformations within the resulting point cloud, especially where there were large angles (with respect the camera position and the wall’s normal direction) and at close distances to the wall’s surface. This paper demonstrates that by overlapping different flawed image sets, the deformation problem can be minimised. -> Link to full text in repository