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One major issue when considering the effects of climate change is to understand, qualify and quantify how the changing climate will likely impact infrastructure assets and services as it strongly depends on current and future climate variability, location, asset design life, function and condition. Expected changes to local climatic conditions may potentially lead to changes in the degradation processes of building materials, affecting the durability and service life of structures. A key question is how climate change may produce changes of vulnerability owing to physical and chemical actions affecting structural durability or changes to exposure in terms of the intensity/frequency of extreme weather events. In this context, this article focuses on the impact on structural resistance and associated challenges, considering some recent activities of members of IABSE TG6.1. Several case studies of infrastructure assets worldwide are presented and discussed in this article.

In recent years, several studies have been performed to assess the damages caused by marine biofouling. Marine biofouling (or marine growth) generally refers to the settlement and growth of unwanted aquatic organisms on human-made structures situated in marine and estuarine environments. Regarding the continued demonstration of energy resource potential and a promising area of research by offshore wind turbines (OWTs), this paper provides a review of biofouling phenomena in the context of underwater cylindrical components of offshore/marine structures. Most floating wind turbine installations are located in moderate water depths between 50 m to 100 m. At these depths, biofouling can be seen on a large section of cylindrical structures, including mooring lines or power cables, with considerable roughness. The proposed review will specifically highlight various marine fouling parameters and laboratory approaches employed by researchers in modelling biofouling, and its effects on hydrodynamic loading due to wave and current excitation. Most previous experimental research assumed that biofouling effects are a function of surface roughness that is either uniform or nearly uniform and that the stationary roughened cylinder is fully covered. Some other studies, however, have proven that the surface roughness alone cannot precisely characterize marine growth; other marine fouling parameters such as roughness geometry, surface coverage ratio, facility testing set-up, biofouling species, and colonization pattern can all have a significant impact on the hydrodynamic force coefficients. To highlight knowledge gaps and research trends on collective influential aspects of biofouling to date. This report went on to explore the challenges in modelling biofouling due to its intrinsic randomness and uncertainty, as well as suggestions for many studies on marine fouling that are currently absent.

In structural reliability, the Markovian cumulative damage approaches such as Gamma process seem promising to model a nonreversible deterioration that involves gradually over time with sma...

The unit influence line of a structure reflects its behaviour and changes in response to damage that may occur. An iterative algorithm is presented in this paper to obtain the shape of the instantaneous influence line of a bridge together with the relative axle loads of trucks passing overhead. One great advantage of this approach is that the need for sensor calibration with pre-weighed trucks can be avoided. The only initial information needed are the measurement data and a preliminary estimate of influence line based on engineering judgement. The concept of a so-called population unit influence line is also presented. This is an influence line that is found from a population of trucks instead of a single vehicle. An illustrative example is presented, where strain data have been collected on a reinforced concrete culvert. As well as the robustness of the proposed algorithms, the influence of temperature on the results is demonstrated. The sensitivity of the population influence line to temperature shows that it is likely to be equally sensitive to loss of stiffness in the structure.

In marine environments structures are subjected to a variety of environmental conditions which govern the degradation processes. For reinforced concrete structures these degradation process...

In this paper a methodology is presented to update estimated level of corrosion damage using routine short-term health monitoring measurement data. The case study bridge is a reinforced concrete (RC) slab. It is subject to traffic loading from a weigh-in-motion database and time-dependent deterioration is modelled through corrosion. Different damage indicators based on different virtual sensor measurements (strain, deflection and rotation) are investigated. A method of comparing the performance of the damage indicators is presented and their data is used to achieve a Bayesian update of prior estimates of bridge reinforcement corrosion. It is shown how, with few and uncertain data, the estimation of deterioration level can be significantly improved, particularly with damage indicators based on rotation.

International audience; Characterising spatial variability, which is of utter importance in inspection and maintenance strategies, requires comprehensive spatially distributed databases. However, in real practice, spatially distributed inspection is costly and could damage the structure if a large number of destructive tests are carried out. Therefore, the first objective of this work is to propose a methodology to extract as much informations as possible from available spatially distributed databases, in order to characterise the spatial correlation. Moreover, a preventive maintenance strategy should be supported by deterioration models able to propagate uncertainty and spatial variability. Then, the second objective of the paper is to evaluate the ability of these models to propagate uncertainties and spatial variability. The methodology is illustrated with data collected through destructive tests in a concrete wall exposed to carbonation. The database encompasses information about the concrete porosity, saturation degree , density, and carbonation depth. Recommendations are hence provided in this work for the choice of input parameters that should be modelled as random fields. These recommendations were applied and then confirmed by comparing measured and modelled spatially distributed carbonation depths. The results highlight that uncertainties in measurements and statistical uncertainties have significant impact when dealing with spatial variability.

International audience; As current attention of the offshore industry is drawn by developing pilot farms of Floating Wind Turbines (FWTs) in shallow-water between 50m and 100m, the application of nylon as a mooring component can provide a more cost-effective design. Indeed, nylon is a preferred candidate over polyester for FWT mooring mainly because of its lower stiffness and a corresponding capacity of reducing maximum tensions in the mooring system. However, the nonlinear behaviors of nylon ropes (e.g. load-elongation properties, fatigue characteristics, etc.) complicate the design and modeling of such structures. Although previous studies on the mechanical properties and modeling of polyester may be very good references, those can not be applied directly for nylon both on testing and modeling methods. In this study, first, an empirical expression to determine the dynamic stiffness of a nylon rope is drawn from the testing data in the literature. Secondly, a practical modeling procedure is suggested by the authors in order to cope with the numerical mooring analysis for a semi-submersible type FWT taking into account the dynamic axial stiffness of nylon ropes. Both the experimental and numerical results show that the tension amplitude has an important impact on the dynamic stiffness of nylon ropes and, as a consequence, the tension responses of mooring lines. This effect can be captured by the present modeling procedure. Finally, time domain mooring analysis for both Ultimate Limit State (ULS) and Fatigue Limit State (FLS) is performed to illustrate the advantages and conservativeness of the present approach for nylon mooring modeling.

Installation, calibration protocol and data analysis of multi-electrode sensors embedded in concrete are proposed in this study. Measurements of resistivity are performed in a port wharf and analyzed in parallel with measurements of humidity, temperature, and evolution of the mechanical strength of concrete. The correlation between the evolution of the compressive strength and the resistivity, allows to validate the measurement protocol proposed. To visualize the distribution of resistivities in the studied volume, pseudo-sections of apparent resistivity were displayed. A methodology to plot and use them as an indicator of corrosion adapted to civil engineering structures is proposed.

International audience; In pipelines, one of the primary testing procedures used to identify the e↵ects and evolution of corrosion over time is through In-Line Inspections (ILI). ILI inspections provide detailed information regarding the inner and outer pipeline condition based on the remaining wall thickness. Based on this information, di↵erent approaches have been proposed to predict the degradation extent of the defects detected. However, these predictions are subject of uncertainties due to the inspection tool and the degradation process that poses some challenges for assessing an entire pipeline within the timespan between two inspections. To address this problem, ILI data was used to formulate a degradation model for steel-pipe degradation based on a Mixed Lévy Process. The model combines a Gamma and Compound Poisson Processes aimed for a better description of the degradation reported by the ILI data. The model seeks to estimate corrosion lifetime distribution and the mean time to failure (MTTF) more accurately. The model was tested on an actual segment of an oil pipeline, and the results have been used to support a preventive maintenance program.

This paper presents an approach to build a multi-fidelity kriging metamodel from finite element computations on different meshes for stuctural reliability assessment. The proposed method takes advantage of the computation of bounds on the dis-cretization error, which enables to guarantee the state (safe or failure) of each computation of the performance function. An algorithm to build the meta-model from the different levels of fidelity and estimate the failure probability is provided. Illustrations are presented on a two dimensional mechanical crack opening problem. Bounds on the failure probability are also post-processed.

The first-order Markov Chain (MC) is used to predict the degradation of three types of pavements (rigid, semi-rigid, and mix) utilising database in the five departments in the West of France. The a...

Novel attempts to optimize the design and requalification of offshore structures draws attention to the importance of updating information about the environmental forces. One of the important steps to design or re-assess offshore structures is the re-evaluation/evaluation of bio-colonization’s effects. This paper presents a review of studies that considered biofouling in marine/offshore structures. Most of the previous researchers conducted the effects of biofouling as a surface roughness; however, some others proved that despite the surface roughness, other marine fouling components such as surface coverage ratio, biofouling species, and aggregation, may significantly influence hydrodynamic force coefficients, particularly at higher Reynolds numbers (Re). In addition, a new approach is proposed in this paper to estimate the drag coefficient of circular members covered by biofouling. The new approach relies on a multiple parameter equation and builds on the existing measurement of the drag force coefficient. Two relationships between biofouling parameters and drag coefficient are given for hard biofouling at the post-critical Re regime.

The deployment of tidal technology is affected by the general bottlenecks associated with all new renewables in respect of finance and integration with the grid. In this research, a development strategy is defined for tidal range projects based on geodynamics, civil engineering, and economics with the aim of assisting policy makers and industry. Criteria related to hydrodynamics, bathymetry, marine structure safety and cost recovery apply to relevant sites and to real data power prices. The case study described is that of the Bay of Bourgneuf on the French Atlantic coast, where a tidal range power plant of 900 MW could optimally be built with respect to sedimentation, water depth, and tidal coefficients. It has been determined that a 30 m-high artificial dam could maximise the harvestable energy (3 TWh). Numerical simulations show that a tidal plant sized at just 700 MW would be cost-efficient, due to the constraints of the grid and to high power curtailment rates (30%). The expected value of the Levelised Cost of Electricity would be around 200€2016/MWh. Integration into the grid could be improved through addition of an innovative underwater energy storage system, rated to one third of the size of the tidal plant. The economics would improve (the LCOE would drop to 170€2016/MWh) due to lower curtailment and to price arbitrage opportunities. Issues related to missing investor money (>3Bln€2016) and unquantifiable positive externalities such as flood protection, energy independency, and clean energy provision are discussed, underpinning the need for regulator support.

Inflatable structures are part of the family of tensioned textile membrane structures. The operating principle is common for all these type of structures: the stiffness of the structure relies on t...

While design optimization under uncertainty has been widely studied in the last decades, time-variant reliability-based design optimization (t-RBDO) is still an ongoing research field. The sequential and mono-level approaches show a high numerical efficiency. However, this might be to the detriment of accuracy especially in case of nonlinear performance functions and non-unique time-variant most probable failure point (MPP). A better accuracy can be obtained with the coupled approach, but this is in general computationally prohibitive. This work proposes a new t-RBDO method that overcomes the aforementioned limitations. The main idea consists in performing the time-variant reliability analysis on global kriging models that approximate the time-dependent limit state functions. These surrogates are built in an artificial augmented reliability space and an efficient adaptive enrichment strategy is developed that allows calibrating the models simultaneously. The kriging models are consequently only refined in regions that may potentially be visited by the optimizer. It is also proposed to use the same surrogates to find the deterministic design point with no extra computational cost. Using this point to launch the t-RBDO guarantees a fast convergence of the optimization algorithm. The proposed method is demonstrated on problems involving nonlinear limit state functions and non-stationary stochastic processes.

International audience; Structural reliability assessment is largely influenced by the spatial variability of material properties or defaults; however, there are still various challenges for their characterization and modeling. Structural Health Monitoring (SHM) could provide useful information in space and time for spatial variability characterization of material properties and mechanical solicitations; nevertheless, this challenge is arduous because of the large number of potential sensor positions of local disruptions/failures. This paper proposes a methodology to optimize the spatial distribution of embedded sensors used for spatial variability assessment of stationary random fields. The optimization criterion relies on the width of the confidence interval of statistics for the characteristics to identify. For sake of simplicity, the paper illustrates the method for one-dimensional problems. The proposed method is applied firstly to a numerical example were several hypothetical structural configurations that could be found in practice are studied. It is finally applied to two case studies (a reinforced concrete beam and a steel wharf) where water content and loss of steel thickness are respectively measured. The results show that the stationary property is useful to deduce the minimum quantity of sensors and their position for a given quality requirement. They also allow us to propose a criterion for defining if regular or non-regular spacing of sensors along the inspection zone is more appropriate depending on the component length and autocorrelation structure of the random field.

Image processing-based methods, capable of detecting and quantifying cracks, surface defects or recovering 3D shape information are increasingly being recognised as a valuable tool for inspecting underwater structures. It is of great practical importance for inspectors to know the effectiveness of such techniques when applied in conditions. This paper considers an underwater environment characterised by poor visibility chiefly governed by the lighting and turbidity levels, along with a range of geometry and damage conditions of calibrated specimens. The paper addresses the relationship between underwater visibility and the performance of image-based methods through the development and calibration of a first open-source underwater lighting and turbidity image repository (ULTIR). ULTIR contains a large collection of images of submerged specimens that have been photographed under controlled lighting and turbidity levels featuring various forms of geometry and damage. ULTIR aims to facilitate inspectors when rationalising the use of image processing methods as part of an underwater inspection campaign and to enable researchers to efficiently evaluate the performance of image-based methods under realistic operating conditions. Stakeholders in underwater infrastructure can benefit through this first large, standardised, well-annotated, and freely available database of images and associated metadata. Irish Research Council for Science, Engineering and Technology Science Foundation Ireland CAPACITES/IXEAD Society Marine Research Energy Ireland (MaREI)

The present paper deals with the stochastic modeling of bio-colonization for the computation of stochastic hydrodynamic loading on jacket-type offshore structures. It relies on a multidisciplinary study gathering biological and physical research fields that accounts for uncertainties at all the levels. Indeed, bio-colonization of offshore structures is a complex phenomenon with two major but distinct domains: (i) marine biology, whose processes are modeled with biomathematics methods, and (ii) hydrodynamic processes. This paper aims to connect these two domains. It proposes a stochastic model for the marine organism&rsquo, s growth and then continues with transfers for the assessment of drag coefficient and forces probability density functions that account for marine growth evolution. A case study relies on the characteristics (growth and shape) of the blue mussel (Mytilus edulis) in the northeastern Atlantic.

The results of in-water vortex-induced vibration (VIV) experiments on circular cylinders artificially covered with barnacles are reported. The paper focusses on the effects of the partial coverage and the shape of the fouling elements. An artificial barnacle typical of marine fouling was synthesised using 3-D printing. Coverage ratios of 80, 50 and 30% were examined and the results compared with those from a smooth cylinder. The Reynolds number ranged from 5.8 × 103 to 6.6 × 104. The experimental results show that the fouling reduced the peak VIV amplitude, narrowed the synchronisation region and lowered the hydrodynamic force coefficients such as the coefficients of lift force RMS, the mean drag force and the fluctuating drag force RMS. The shape of the artificial barnacles had little effect on the maximum oscillation amplitude. The coverage ratio appeared to have a lower impact on the lift force than those on the amplitude and the frequency responses.

Welded joints are used in various structures and infrastructures like bridges, ships and offshore structures, and are submitted to cyclic stresses. Their fatigue behaviour is an industrial key issue to deal with and still offers original research subjects. One of the available methods relies on the computing of the stress concentration factor. Even if some studies were previously driven to evaluate this factor onto some cases of welded structures, the shape of the weld joint is generally idealized through a deterministic parametric geometry. Previous experimental works however have shown that this shape plays a key role in the lifetime assessment. We propose in this paper a methodology for computing the stress concentration factor in presence of random geometries of welded joints. In view to make the results available by engineers, this method merges stochastic computation and semi-probabilistic analysis by computing partial safety factors with a dedicated method.

International audience; This article is within the context of decision models aimed for maintenance of structures and infrastructures in civil engineering. The contribution relies on the construction of a degradation model oriented toward risk analysis. The proposed model can be defined as a meta-model in the sense that it is based on observations while incorporating key features from the degradation process necessary for the maintenance decision. We propose to stimulate the construction of the degradation model based on the crack propagation of a submerged reinforced concrete structure subject to chloride-induced corrosion. Furthermore, a set of numerical illustrations is performed to demonstrate the advantages and applicability of the proposed approach in risk management and maintenance contexts.

Physics-based models are intensively studied in mechanical and civil engineering but their constant increase in complexity makes them harder to use in a maintenance context, especially when degradation model can/should be updated from new inspection data. On the other hand, Markovian cumulative damage approaches such as Gamma processes seem promising; however, they suffer from lack of acceptability by the civil engineering community due to poor physics considerations. In this article, we want to promote an approach for modeling the degradation of structures and infrastructures for maintenance purposes which can be seen as an intermediate approach between physical models and probabilistic models. A new statistical, data-driven state-dependent model is proposed. The construction of the degradation model will be discussed within an application to the cracking of concrete due to chloride-induced corrosion. Numerical experiments will later be conducted to identify preliminary properties of the model in terms of statistical inferences. An estimation algorithm is proposed to estimate the parameters of the model in cases where databases suffer from irregularities.

Due to both wave and wind fluctuations, the steel foundations of offshore wind turbines are highly submitted to fatigue. To date, current methods of fatigue design proposed in the regulations are not devoted to structural optimization and to the consideration of time-variant hazards. We propose hence an incremental two-scale model of damage in order to follow the time evolution of the damage. This temporal evolution allows the updating of model parameters using records from Structural Health Monitoring. In this paper, we focus on Bayesian updating of damage parameters and sensitivity analysis of damage assessment to material parameters.