Marine growth is a known problem for oceanic infrastructure and has been shown to negatively impact the reliability of bottom-fixed or floating offshore structures submitted to fatigue or extreme ...loading. Among other effects, it has been shown to change drag forces by increasing member diameters and modifying the roughness. Bio-colonization being highly random, the objective of this paper is to show how one-site inspection data increases reliability by decreasing uncertainties. This can be introduced in a reliability-based inspection framework for optimizing inspection and maintenance (here, cleaning). The modeling and computation are illustrated through the reliability analysis of a monopile in the European Atlantic area subjected to marine growth and according to the plastic collapse limit state. Based on surveys of structures in the North Sea, long-term stochastic modeling (space and time) of the marine growth thickness is first suggested. A Dynamic Bayesian Network is then developed for reliability updating from the inspection data. Finally, several realistic (10–20 measurements) inspection strategies are compared in terms of reliability improvement and the accuracy of reliability assessment.
► We study the effects of climate change on the durability of corroding RC structures. ► Simplified climate models including climate change scenarios are presented. ► Climate change could reduce RC ...durability significantly. ► The time-to-failure and service life decrease by up to 31% or 15years, respectively. ► We outlined the needs for an optimal risk-based selection of adaptation strategies.
Chloride ingress and carbonation cause corrosion of reinforced concrete (RC) structures affecting its operational life. Experimental evidence indicates that these deterioration processes are highly influenced by CO2 emissions and climatic conditions in the surrounding environment – i.e., temperature, humidity, etc. Since studies on global warming announce changes in climate, the impact of changing climate on RC durability should also be considered. This paper links RC deterioration mechanisms to CO2 emissions and global warming. Based on various studies on climate change, models for estimating the effect of CO2 emissions and temperature/humidity changes due to global warming are described. Furthermore, various scenarios of global warming that can be used to assess the effect of climate change in structural reliability are proposed. The proposed approach is then illustrated with a numerical example that calculates the probability of failure of a RC bridge beam for future climate scenarios. The paper then outlines some adaptation strategies, particularly focusing on the needs for risk-based selection of optimal adaptation measures.
Imaging‐based damage detection techniques are increasingly being utilized alongside traditional visual inspection methods to provide owners/operators of infrastructure with an efficient source of ...quantitative information for ensuring their continued safe and economic operation. However, there exists scope for significant development of improved damage detection algorithms that can characterize features of interest in challenging scenes with credibility. This article presents a new regionally enhanced multiphase segmentation (REMPS) technique that is designed to detect a broad range of damage forms on the surface of civil infrastructure. The technique is successfully applied to a corroding infrastructure component in a harbour facility. REMPS integrates spatial and pixel relationships to identify, classify, and quantify the area of damaged regions to a high degree of accuracy. The image of interest is preprocessed through a contrast enhancement and color reduction scheme. Features in the image are then identified using a Sobel edge detector, followed by subsequent classification using a clustering‐based filtering technique. Finally, support vector machines are used to classify pixels which are locally supplemented onto damaged regions to improve their size and shape characteristics. The performance of REMPS in different color spaces is investigated for best detection on the basis of receiver operating characteristics curves. The superiority of REMPS over existing segmentation approaches is demonstrated, in particular when considering high dynamic range imagery. It is shown that REMPS easily extends beyond the application presented and may be considered an effective and versatile standalone segmentation technique.
Offshore wind substations are subjected to uncertain loads from waves, wind and currents. Sea states are composed of irregular waves which statistics are usually characterized. Irregular loads may ...induce fatigue failure of some structural components of the structures. By combining fatigue damage computed through numerical simulations for each sea state endured by the structure, it is possible to assess fatigue failure of the structure over the whole deployment duration. Yet, the influence of the discretization error on the fatigue damage is rarely addressed. It is possible to estimate the discretization error on the quantity of interest computed at the structural detail suspected to fail. However, the relation between this local quantity of interest and the fatigue damage is complex. In this paper, a method that allows propagating error bounds towards fatigue damage is proposed. While increasing computational burden, computing discretization error bounds is a useful output of finite element analysis. It can be utilized to either validate mesh choice or guide remeshing in case where potential error on the fatigue damage is too large. This method is applied to an offshore wind substation developped by Chantiers de l’Atlantique using two discretization error estimators in a single sea state.
Recent breakthroughs in the computer vision community have led to the emergence of efficient deep learning techniques for end-to-end segmentation of natural scenes. Underwater imaging stands to gain ...from these advances, however, deep learning methods require large annotated datasets for model training and these are typically unavailable for underwater imaging applications. This paper proposes the use of photorealistic synthetic imagery for training deep models that can be applied to interpret real-world underwater imagery. To demonstrate this concept, we look at the specific problem of biofouling detection on marine structures. A contemporary deep encoder–decoder network, termed SegNet, is trained using 2500 annotated synthetic images of size 960 × 540 pixels. The images were rendered in a virtual underwater environment under a wide variety of conditions and feature biofouling of various size, shape, and colour. Each rendered image has a corresponding ground truth per-pixel label map. Once trained on the synthetic imagery, SegNet is applied to segment new real-world images. The initial segmentation is refined using an iterative support vector machine (SVM) based post-processing algorithm. The proposed approach achieves a mean Intersection over Union (IoU) of 87% and a mean accuracy of 94% when tested on 32 frames extracted from two distinct real-world subsea inspection videos. Inference takes several seconds for a typical image.
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.
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.
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.
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’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.
Wind energy is expected to play a significant role in meeting emission targets over the next 20 years. Offshore wind turbines in deep water (>150 m) must be developed due to resource quality, ...environmental, and activity constraints. Floating offshore wind turbines (FOWT) will be the best technology for reaching these targets. The dynamic submarine electrical cable (DSEC) is a key component of FOWT. Its electric insulation system is intended to withstand a maximum conductor temperature of 90 °C. However, biofouling growth, particularly mussels, can modify the heat transfer around the cable and thus its maximum conductor temperature, as well as temperature fluctuation, affecting the fatigue lifetime. In our work we estimate the effective thermal conductivity of mussels of various ages, as well as the heat transfer coefficient of the water around them. The results revealed that the effective thermal conductivity of juvenile mussels is lower than that of mix (both juvenile and adult) and only adult mussels. This variation in effective thermal conductivity with mussel age is related to the water porosity of the mussel’s layer. Then, the thermal effect of the resulting global thermal resistance can lead the DSEC conductor wire to either overheat (colonized by juvenile and mixed mussels) or cool down (colonized by adult mussels). Numerical simulations are used to quantify this effect.
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