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
Dealing with extreme events implies working with events that have low probability of occurrence. To characterize these, the peak-over-threshold method alongside the generalized Pareto distribution is commonly applied. However, when it comes to significant wave heights, this approach is not recommended. Here, the generalized Pareto distribution is discussed based on data collected around the coast of Ireland. A careful choice of threshold takes place, and a new methodology to establish the threshold level is introduced. Five indicators to evaluate the fitting are considered to compare the different statistical models. No evidence was identified to justify the rejection of the generalized Pareto distribution to model exceedances. Results show that it may be statistically less, equally or more adequate, depending on the peak-over-threshold implementation. Nevertheless, the generalized Pareto bounded character is of elementary interest for wave statistics. In some circumstances not considering it might lead to unrealistic significant wave return levels. [DOI]
This paper showcases the importance of field testing in efforts to deal with the deteriorating infrastructure. It shows that when tested, bridges do not necessarily behave as expected under load, particularly with respect to boundary conditions. This is demonstrated via a load test performed on a healthy but ageing composite reinforced concrete bridge 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. Subsequently, a 3-D finite element model of the bridge was developed and calibrated based on the field test data. The bridge deck was originally designed as simply supported, however, it is shown (from the field test and calibrated model) that the support conditions were no longer behaving as pin-roller which affects the load distribution characteristics of the superstructure. Transverse load distribution factors (DFs) of the bridge deck structure were studied for different boundary conditions. The DFs obtained from analysis were compared with DFs provided in Design Manual for Roads and Bridges (DMRB) Standard Specification. Having observed in the load test that the ends of the deck appeared to be experiencing some rotational restraint, a parametric study was carried out to calculate mid-span bending moment (under DMRB assessment loading) for varying levels of restraint at the end of the deck. [DOI]
Historically the UK has been a pioneer and early adopter of experimental investigation techniques on new and operation structures, a technology that would now be described as Structural Health Monitoring (SHM), yet few of these investigations have been enduring or carried out on the long span or tall structures that feature in flagship SHM applications in the Far East. [DOI] -> Link to full text in repository
This paper introduces the various aspects of bridge safety models. It combines the different models of load and resistance involving both deterministic and stochastic variables. The actual safety, i.e. the probability of failure, is calculated using Monte Carlo simulation and accounting for localized damage of the bridge. A possible damage indicator is also presented in the paper and the usefulness of updating the developed bridge safety model, with regards to the damage indicator, is examined. [DOI] -> Link to publisher’s version -> Link to full text in repository
Railway importance in the transportation industry is increasing continuously, due to the growing demand of both passenger travel and transportation of goods. However, more than 35% of the 300,000 railway bridges across Europe are over 100-years old, and their reliability directly impacts the reliability of the railway network. This increased demand may lead to higher risk associated with their unexpected failures, resulting safety hazards to passengers and increased whole life cycle cost of the asset. Consequently, one of the most important aspects of evaluation of the reliability of the overall railway transport system is bridge structural health monitoring, which can monitor the health state of the bridge by allowing an early detection of failures. Therefore, a fast, safe and cost-effective recovery of the optimal health state of the bridge, where the levels of element degradation or failure are maintained efficiently, can be achieved. In this article, after an introduction to the desired features of structural health monitoring, a review of the most commonly adopted bridge fault detection methods is presented. Mainly, the analysis focuses on model-based finite element updating strategies, non-model-based (data-driven) fault detection methods, such as artificial neural network, and Bayesian belief network–based structural health monitoring methods. A comparative study, which aims to discuss and compare the performance of the reviewed types of structural health monitoring methods, is then presented by analysing a short-span steel structure of a railway bridge. Opportunities and future challenges of the fault detection methods of railway bridges are highlighted. [DOI] -> Link to full text in repository
Traditionally, damage identification techniques in bridges have focused on monitoring changes to modal-based Damage Sensitive Features (DSFs) due to their direct relationship with structural stiffness and their spatial information content. However, their progression to real-world applications has not been without its challenges and shortcomings, mainly stemming from: (1) environmental and operational variations; (2) inefficient utilization of machine learning algorithms for damage detection; and (3) a general over-reliance on modal-based DSFs alone. The present paper provides an in-depth review of the development of modal-based DSFs and a synopsis of the challenges they face. The paper then sets out to addresses the highlighted challenges in terms of published advancements and alternatives from recent literature. [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. [DOI] -> Link to full text in repository
When using distributed optical fiber sensors (DOFS) on reinforced concrete structures, a compromise must be achieved between the protection requirements and robustness of the sensor deployment and the accuracy of the measurements both in the uncracked and cracked stages and under loading, unloading and reloading processes. With this in mind the authors have carried out an experiment where polyimide-coated DOFS were installed on two concrete beams, both embedded in the rebar elements and also bonded to the concrete surface. The specimens were subjected to a three-point load test where after cracking, they are unloaded and reloaded again to assess the capability of the sensor when applied to a real loading scenarios in concrete structures. Rayleigh Optical Frequency Domain Reflectometry (OFDR) was used as the most suitable technique for crack detection in reinforced concrete elements. To verify the reliability and accuracy of the DOFS measurements, additional strain gauges were also installed at three locations along the rebar. The results show the feasibility of using a thin coated polyimide DOFS directly bonded on the reinforcing bar without the need of indention or mechanization. A proposal for a Spectral Shift Quality (SSQ) threshold is also obtained and proposed for future works when using polyimide-coated DOFS bonded to rebars with cyanoacrylate adhesive. [DOI] -> Link to full text in repository
The versatility and ease of installation of Distributed Optical Fibre Sensors (DOFS) compared with traditional monitoring systems are important characteristics to consider when facing the Structural Health Monitoring (SHM) of real world structures. The DOFS used in this study provide continuous (in space) strain data along the optical fibre with high spatial resolution. The main issues and results of two different existing structures monitored with DOFS, are described in this paper. The main SHM results of the rehabilitation of an historical building used as hospital and the enlargement of a pre-stressed concrete bridge are presented. The results are obtained using a novel DOFS based on an Optical Backscattered Reflectometry (OBR) technique. The application of the optical fibre monitoring system to two different materials (masonry and concrete) provides also important insights on the great possibilities of this technique when monitoring existing structures. In fact, the influence of strain transfer between the DOFS and the bonding surface is one of the principal effects that should be considered in the application of the OBR technique to real structures. Moreover, and because structural surfaces generally present considerable roughness, the procedure to attach the optical fibre to the two monitored structures is described. [DOI]-> 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] -> Link to full text in repository
The application of structural health monitoring (SHM) systems to 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. The possibility of understanding and monitor the distributed behavior of extensive stretches of critical structures it’s an enormous advantage that distributed fiber optic sensing provides to SHM systems. In the past decade, several R & D 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. This paper presents, after a brief introduction to the theoretical background of DOFS, the latest developments related with the improvement of these products by presenting a wide range of laboratory experiments as well as an extended review of their diverse applications in civil engineering structures. [DOI] -> Link to full text in repository
This paper describes a new procedure for bridge damage identification through drive-by monitoring. Instantaneous curvature (IC) is presented as a means to determine a local loss of stiffness in a bridge through measurements collected from a passing instrumented vehicle. Moving reference curvature (MRC) is compared with IC as a damage detection tool. It is assumed that absolute displacements on the bridge can be measured by the vehicle. The bridge is represented by a finite element (FE) model. A Half-car model is used to represent the passing vehicle. Damage is represented as a local loss of stiffness in different parts of the bridge. 1% random noise and no noise environments are considered to evaluate the effectiveness of the method. A generic road surface profile is also assumed. Numerical simulations show that the local damage can be detected using IC if the deflection responses can be measured with sufficient accuracy. Damage quantification can be obtained from MRC. [DOI] -> Link to full text in repository