Investigation on Applicability and Limitation of Cosine Similarity-Based Structural Condition Monitoring for Gageocho Offshore Structure

The key to coping with global warming is reconstructing energy governance from carbon-based to sustainable resources. Offshore energy sources, such as offshore wind turbines, are promising alternatives. However, the abnormal climate is a potential threat to the safety of offshore structures because construction guidelines cannot embrace climate outliers. A cosine similarity-based maintenance strategy may be a possible solution for managing and mitigating these risks. However, a study reporting its application to an actual field structure has not yet been reported. Thus, as an initial study, this study investigated whether the technique is applicable or whether it has limitations in the real field using an actual example, the Gageocho Ocean Research Station. Consequently, it was found that damage can only be detected correctly if the damage states are very similar to the comparison target database. Therefore, the high accuracy of natural frequencies, including environmental effects, should be ensured. Specifically, damage scenarios must be carefully designed, and an alternative is to devise more efficient techniques that can compensate for the present procedure.

Damaged cable identification in cable-stayed bridge from bridge deck strain measurements using support vector machine

A new two-step approach is developed for damaged cable identification in a cable-stayed bridge from deck bending strain responses using Support Vector Machine. A Damaged Cable Identification Machine (DCIM) based on support vector classification is constructed to determine the damaged cable and a Damage Severity Identification Machine (DSIM) based on support vector regression is built to estimate the damage severity. A field cable-stayed bridge with a long-term monitoring system is used to verify the proposed method. The three-dimensional Finite Element Model (FEM) of the cable-stayed bridge is established using ANSYS, and the model is validated using the field testing results, such as the mode shape, natural frequencies and its bending strain responses of the bridge under a moving vehicle. Then the validated FEM is used to simulate the bending strain responses of the longitude deck near the cable anchors when the vehicle is passing over the bridge. Different damage scenarios are simulated for each cable with various severities. Based on damage indexes vector, the training datasets and testing datasets are acquired, including single damaged cable scenarios and double damaged cable scenarios. Eventually, DCIM is trained using Support Vector Classification Machine and DSIM is trained using Support Vector Regression Machine. The testing datasets are input in DCIM and DSIM to check their accuracy and generalization capability. Different noise levels including 5%, 10%, and 20% are considered to study their anti-noise capability. The results show that DCIM and DSIM both have good generalization capability and anti-noise capability.

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning

Damage detection based on modal parameter changes becomes popular in the last decades. Nowadays are available robust and reliable mathematical relations to predict the natural frequency changes if damage parameters are known. Using these relations, it is possible to create databases containing a large variety of damage scenarios. Damage can be thus assessed by applying an inverse method. The problem is the complexity of the database, especially for structures with more cracks. In this paper, we propose two machine learning methods, namely the random forest (RF) and the artificial neural network (ANN) as search tools. The databases we developed contain damage scenarios for a prismatic cantilever beam with one crack and ideal and non-ideal boundary conditions. The crack assessment is made in two steps. First, a coarse damage location is found from the networks trained for scenarios comprising the whole beam. Afterward, the assessment is made involving a particular network trained for the segment of the beam on which the crack is previously found. Using the two machine learning methods, we succeed to estimate the crack location and severity with high accuracy for both simulation and laboratory experiments. Regarding the location of the crack, which is the main goal of the practitioners, the errors are less than 0.6%. Based on these achievements, we concluded that the damage assessment we propose, in conjunction with the machine learning methods, is robust and reliable.

ON THE STABILITY OF FAST FERRY IN DAMAGE SCENARIOS

The ro-ro ships are characterized by a large garage compartment extending from stern to bow. Damage conditions, heavy weather and large floodable spaces could create serious accidents, with the loss of life and goods at sea, both for conventional ferries and fast ferries. The occurred accidents showed the need of a more accurate approach to the damaged ship stability in waves, also in head sea and following sea conditions, because of the great movements of water on the car deck. With this aim a tool for analysing the ship response in wave with damaged compartments has been developed and applied on a typical fast ferry. The ship dynamic is simulated in time domain, including non-linear effects, taking into account critical scenarios on the damaged ship. The applications regard ship grounding, assuming head sea, modelled by regular wave. In addition to that, also the particularly critical condition of a transversal wind heeling moment has been applied to compute non symmetrical behaviour. Moreover the stability problems arising from the presence of trapped water in the garage compartment are investigated assuming the same environmental scenarios.

A NEW METHOD FOR ASSESSING THE SAFETY OF SHIPS DAMAGED BY GROUNDING

The primary aim of the present study is to propose an innovative method for assessing the safety of ships which have suffered accidental or in-service damages. Only a small number of probable scenarios for accidental or in-service damage representing all possible damage scenarios are selected using a sampling technique in which the random variables affecting the damage are probabilistically characterized. A damage index for the corresponding damage scenario is defined as a function of damage characteristics such as location and extent of the damage. The residual strength performance of a ship with the corresponding damage scenario can then be calculated by analytical or numerical methods. Once this process has been carried out for each of the damage scenarios selected, a diagram relating the residual strength performance to the damage index (abbreviated as the R-D diagram) can be established. This diagram will be very useful for a first-cut assessment of a ship’s safety immediately after it has suffered structural damage. The diagram can also be used to determine acceptance criteria for a ship’s safety against accidental or in-service damage. An applied example is shown to demonstrate the applicability of the proposed method in terms of developing a diagram between the ultimate longitudinal strength versus grounding damage index for four types of double-hull oil tankers – VLCC, Suezmax, Aframax, and Panamax.

A Technological System for Post-Earthquake Damage Scenarios Based on the Monitoring by Means of an Urban Seismic Network

A technological system capable of automatically producing damage scenarios at an urban scale, as soon as an earthquake occurs, can help the decision-makers in planning the first post-disaster response, i.e., to prioritize the field activities for checking damage, making a building safe, and supporting rescue and recovery. This system can be even more useful when it works on densely populated areas, as well as on historic urban centers. In the paper, we propose a processing chain on a GIS platform to generate post-earthquake damage scenarios, which are based: (1) on the near real-time processing of the ground motion, that is recorded in different sites by MEMS accelerometric sensor network in order to take into account the local effects, and (2) the current structural characteristics of the built heritage, that can be managed through an information system from the local public administration authority. In the framework of the EU-funded H2020-ARCH project, the components of the system have been developed for the historic area of Camerino (Italy). Currently, some experimental fragility curves in the scientific literature, which are based on the damage observations after Italian earthquakes, are implemented in the platform. These curves allow relating the acceleration peaks obtained by the recordings of the ground motion with the probability to reach a certain damage level, depending on the structural typology. An operational test of the system was performed with reference to an ML3.3 earthquake that occurred 13 km south of Camerino. Acceleration peaks between 1.3 and 4.5 cm/s2 were recorded by the network, and probabilities lower than 35% for negligible damage (and then about 10% for moderate damage) were calculated for the historical buildings given this low-energy earthquake.

Improvement on modal curvatures methods for multiple damage identification in beams

PurposeThe purpose of this paper is to present a study on the application of four damage factors to several single and multiple damage scenarios of aluminium beams. Each one of these damage factors is defined by the information given by modal curvatures of the beams.Design/methodology/approachThe methodology consisted of a first experimental stage in which the modal rotations were measured with shearography and a subsequent numerical analysis in order to obtain the modal curvatures. To this end, three finite difference formulae were applied. The modal curvatures were then used to calculate the damage factors.FindingsIt was found that the profile of the damage factors varies according to the finite difference formula used. In view of the findings, the differences among the damage factors analysed are highlighted and some final recommendations to improve damage identifications via modal curvature-based are presented.Originality/valueTo the best of the authors’ knowledge, the application and comparison of several finite difference formulae and corresponding optimal sampling has not been carried out before. With the proposed approach, it is possible to identify multiple damages, which is still a great challenge. The post-processing of shearography measurements with a numerical method, which is inherently a multidisciplinary approach, is also a substantial improvement upon other type of approaches found in the literature.

A Parametric Scan-to-FEM Framework for the Digital Twin Generation of Historic Masonry Structures

Historic masonry buildings are characterised by uniqueness, which is intrinsically present in their building techniques, morphological features, architectural decorations, artworks, etc. From the modelling point of view, the degree of detail reached on transforming discrete digital representations of historic buildings, e.g., point clouds, into 3D objects and elements strongly depends on the final purpose of the project. For instance, structural engineers involved in the conservation process of built heritage aim to represent the structural system rigorously, neglecting architectural decorations and other details. Following this principle, the software industry is focusing on the definition of a parametric modelling approach, which allows performing the transition from half-raw survey data (point clouds) to geometrical entities in nearly no time. In this paper, a novel parametric Scan-to-FEM approach suitable for architectural heritage is presented. The proposed strategy uses the Generative Programming paradigm implementing a modelling framework into a visual programming environment. Such an approach starts from the 3D survey of the case-study structure and culminates with the definition of a detailed finite element model that can be exploited to predict future scenarios. This approach is appropriate for architectural heritage characterised by symmetries, repetition of modules and architectural orders, making the Scan-to-FEM transition fast and efficient. A Portuguese monument is adopted as a pilot case to validate the proposed procedure. In order to obtain a proper digital twin of this structure, the generated parametric model is imported into an FE environment and then calibrated via an inverse dynamic problem, using as reference metrics the modal properties identified from field acceleration data recorded before and after a retrofitting intervention. After assessing the effectiveness of the strengthening measures, the digital twin ability of reproducing past and future damage scenarios of the church is validated through nonlinear static analyses.