Damage Configurations Research Articles

Post-Failure Behavior of Point-Fixing Laminated Glass Plates under Out-of-Plane Uniform Pressure

This paper presents the results of an experimental and numerical investigation of the mechanical response of undamaged and damaged 2-ply laminated glass plates. Two types of glass plies, thermally toughened and heat-strengthened, coupled with SentryGlas (SG) were considered. Laminated glass plates supported with articulated point fixing bolt under out-of-plane uniform pressure were investigated under four different damage configurations: (i) undamaged; (ii) partially damaged, with the bottom ply broken; (iii) partially damaged, over-flipping the specimen of mode II; (iv) both two glass plies broken, which was applicable for LG plates made by heat-strengthened glass. In the above four modes, the top ply is always subjected to compression while the bottom one is in tension. The different responses of each configuration (different glass types and damage modes) were discussed and compared in this study. In addition, numerical models were adopted to reproduce the experimental results. The influence of the hitting location and glass types on the mechanical behavior of LG plates was analyzed. The results showed that the contribution of the broken glass ply could not be disregarded in the evaluation of the global stiffness of partially damaged LG plates and their bearing capacity.

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model.

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

Wavelet technique and FEA for modal identification in damaged URM shear walls

In existing masonry buildings, the structural capacity with respect to horizontal actions is due to the in-plane response of shear walls, usually evaluated in terms of effective stiffness and drift capacity. The objective of this work is to provide first results to the damage sensitivity in diagonal cracking of URM shear walls and a study methodology based on vibration tests to assess the structural health of existing masonry buildings. The state of pre-existing discontinuities caused by previous damage events or material degradation may play a role in the in-plane response of shear walls. For this, an experimental campaign was carried out on three typologies of UnReinforced Masonry (URM) walls, simulating different damage situations, subjected to Shear-Compression (SC) and vibration tests in order to correlate the structural behaviour with changes in modal parameters. From the vibrational response acquired during the SC test, the modal parameters related to the pre-damage and post-damage condition were identified using the Continuous Wavelet Transform identification technique. The experimental results are then used to implement a Finite Element Model (FEM) with a 2D homogenization approach to simulate the behaviour of URM walls. A parametric study through FEM analysis is carried out in order to investigate the change in modal parameters for different damage configurations and for triggering strut mechanisms.

Experimental studies of CFRP laminates under repetitive low-velocity impact loading

Due to their exceptional properties such as high strength-to-weight ratio and fatigue tolerance, laminated composites are widely used in aircraft structures. When subjected to impact loading, composite structures experience intra/inter-laminar damages, and it is crucial to investigate the effect of damages on the strength of the laminate. Single and multiple impact tests are performed on CFRP laminates with different stacking sequences. Cross-ply [0/90]4S and quasi-isotropic [45/90/-45/0]2S laminates are fabricated and tested. Damage size as a function of the number of impacts and impact energy for different stacking sequences are studied. The damage configuration of impacted specimens is studied using the immersion ultrasonic technique. Damage size and shape of multiple impacted specimens are compared with single impacted specimens.

A modified mode shape data-based method for beams structural damage detection

Damage detection methods based on changing modal parameters have received considerable attention in engineering applications due to the satisfactory results and the low associated cost compared with other techniques. The Mode Shape Data Based Indicator (MSDBI) is a damage indicator available in the literature, being used to identify damage in beam structures from the mode shape, mode shape slope and mode shape curvature, in the undamaged and damaged configurations of the element under study. However, in some situations, the configuration of the displacement mode shape of the ith mode, of the undamaged structure compared to the damaged one, presents mirroring. The damage identification algorithm could be a better indicator when these situations occur. Them, this paper presents a proposal to modify this method, called MSDBIM. The proposed modified method (MSDBIM) and the traditional method (MSDBI) were applied in two numerical examples that were elaborated in commercial software of finite elements, namely a simply supported concrete beam and a fixed-end steel beam in different single and multiple damage scenarios with sensitivity studies. A new discretization for the fixed-end beam was performed to assess whether there is a direct influence on the damage identification method. The results show that the proposed method (MSDBIM) performs better than the traditional method (MSDBI).

Composite Panel Damage Classification Based on Guided Waves and Machine Learning: An Experimental Approach

Ultrasonic guided waves (UGW) are widely used in structural health monitoring (SHM) systems due to the sensitivity of their propagation mechanisms to local material changes, i.e., those induced by damage. Post-processing of the signals gathered by piezoelectric sensors, typically used for both the excitation and the sensing of UGW, is a fundamental step to extract all the peculiar features that can be related to both damage location and severity. This research probes the efficacy of machine learning (ML) models in discerning damage location (R-Classification) and size (S-Classification). Seven supervised ML classifiers were examined: Ensemble-Subspace K-Nearest Neighbors (KNN), Ensemble-Bagged Trees, KNN-Fine, Ensemble-Boosted Trees, Support Vector Machine (SVM), Linear Discriminant, and SVM-Quadratic. The experimental dataset comprised measurements from varied reversible damage configurations on a composite panel, represented by wooden cuboids of single and three different sizes. Signal noise was minimized by performing a low-pass filter, and sequence forward selection-aided feature selection. The optimized ensemble classifier proved to be the most precise for R-Classification (95.83% accuracy), while Ensemble-Subspace KNN excelled in S-Classification (98.1% accuracy). This method offers accurate, efficient damage diagnosis and classification in composite structures, promising potential applications in aerospace, automotive, and civil engineering sectors.

Resilience surface for quantifying hazard resiliency of transportation infrastructure

Resilience assessment of transportation infrastructure is a crucial aspect of ensuring the continued functionality of a city or region in the face of various disruptions. However, these infrastructures are also vulnerable to various types of disruptions, such as natural disasters. The ability of transportation infrastructures to withstand and recover from such disruptions is referred to as their resilience. This research presents a comprehensive framework to develop the resilience surface for assessing the resilience of transportation infrastructure such as bridges, roads, and tunnels. The framework involves the identification of the unique damage configurations through performing the fragility analysis, and the restoration of the infrastructures through developing recovery curves for each damage configuration by considering the relevant restoration data. The framework also considers the inherent uncertainty in the hazard intensity, modeling uncertainty, and restoration process. The framework is illustrated through the application to a case study of a highway bridge in Canada. The aim of this paper is to provide a useful tool for decision-makers to evaluate and improve the resilience of transportation infrastructures.

Guided wave ultrasonic feature determination in Type IV composite overwrapped pressure vessels towards the digital twin

The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.

Nonlinear Dynamic Assessment of a Steel Frame Structure Subjected to Truck Collision

The progressive collapse of structures subjected to a truck collision with ground floor columns is numerically investigated in this paper. For this purpose, a four-story steel building with a dual system (including an intermediate steel moment frame, with a special concentric steel bracing system in the longitudinal (x) direction, and an intermediate steel moment frame in the transversal (y) direction) is considered. The structure, which was designed according to AISC, ASCE7 and 2800 Iranian seismic standard guidelines, is located in seismic-prone area and subjected to eight different truck collision scenarios. The nonlinear dynamic analyses carried out in ABAQUS on a three-dimensional finite element (FE) numerical model include variations in collision features (i.e., mass and speed of the truck, the height of collision point), and are used to support the analysis of expected damage. The presented results confirm that increasing the truck mass and speed increases damage entity for the column and structure. Several influencing parameters are involved in damage location and progressive evolution. The height of the collision point from the ground also significantly affects the magnitude of structural damage, especially in terms of stress peaks in the panel zones for the target column. Finally, the perimeter columns are more vulnerable to impact than corner columns, in structures with dual system as with the examined four-story building. The presence of a bracing system parallel to the impacting vehicle can in fact reduce the deformation—and thus the expected damage—of the adjacent target column. Most importantly, it is shown that the numerically reproduced collision scenarios (and the associated damage configurations) based on truck impact are significantly more severe than those artificially created based on the conventional column removal method (i.e., alternate path (AP) analysis approach), which confirms the importance of more sophisticated numerical calculation procedures to investigate and assess the progressive collapse of structures.

Performance of Corrugated-Plate-Shaped Bridge Piers under Uniaxial Loading

The current research examines the seismic performance of irregular cross-section of bridge piers that has rarely been investigated. Preceded by a successful validation, the study was numerically conducted by ABAQUS/Explicit program containing a comprehensive series of FE bridge piers under unidirectional cyclic loading and axial dead load. Three corrugated shapes with a net depth of 60, 80 and 146 mm mainly formed the cross-sectional configuration of concrete-filled steel bridge piers. The aim was to examine the load-bearing capacity, ductility and buckling mode of such models and compare their behavior with traditional circular-shaped steel columns. Afterwards, a parametric study involved the grade of concrete (20, 30, and 40 MPa), corrugation geometry (C60, C80, and C146 mm), radius-to-thickness ratio (0.131, 0.149, and 0.116), and axial force ratio (10%, 15%, 20% and 30%). FE results suggested that concrete-filled corrugated-shaped columns revealed nearly 50% more load-bearing capacity and ductility as compared to circular-section columns. The damage configuration among corrugated-shaped columns was seen less severe than circular-section columns, where the local buckling in the latter one was premature and concentrated in particular zone. The findings herein urge to consider implementing corrugated-shaped piers in structures due to their significant addition in strength, ductility, and failure control.

BIM oriented applications of structural health monitoring based on magnified digital image correlation point-clouds

Three-dimensional Digital Image Correlation (3D-DIC) gained popularity as a line-of-sight, high-resolution Structural Health Monitoring (SHM) technique. Nonetheless, 3D-DIC is still impractical when the natural frequencies and the mode shapes of the structure have to be correlated. Recently, the integration of Motion Magnification (MM) as a pre-processing tool for 3D-DIC has been explored to enhance the capabilities of DIC for structural analysis and defined a Magnified DIC (M-DIC) workflow. However, such applications do not take full advantage of the potential of the 3D-DIC to produce point-clouds informed of the dynamic properties of a structure. Hence, the definition of a straightforward workflow to manage 3D-DIC point-clouds for real-world applications should be addressed. Moreover, the large amount of raw output coming from MM and 3D-DIC combination requires appropriate tools to systematically visualise and analyse the data. In this context, Building Information Modelling (BIM) has emerged as a robust repository as well as a data management tool to store and exchange data related to the built environment, including long sequences of SHM data. This research proposes a novel Cloud to Model (C2M) tool called M-DIC2BIM that translates the Scalar Fields (SFs) of the M-DIC point-cloud directly into the faces of the BIM model instances. As a case study, a three-storey aluminium frame structure excited with broadband noise is used to validate the developed methodology. The comparison among undamaged and damaged configurations tests made the evolution of the frame's Operational Deflection Shapes (ODSs) computable by quantifying structural changes in its global and local behaviour and mapping them onto the BIM instances.

DETECT-AGING blind prediction contest: a benchmark for structural health monitoring of masonry buildings

The installation of monitoring systems on buildings allows analyzing variations in structural parameters over time, creating room for detection of damage. Structural Health Monitoring (SHM) systems have the potential to support pro-active risk management, where structural interventions are planned if specific thresholds related to target performance losses are achieved.DETECT-AGING is a research project of relevant national interest that was funded by the Italian Ministry of University and Research (MUR) through the PRIN 2017 programme. The project started in September 2019 and involves the universities of Bologna, Genova, Napoli Federico II, and Perugia. The main goal of the project is to develop a new analytical-instrumental approach aimed at the quantitative assessment of the effects of aging and material degradation on structural safety of cultural heritage, with special focus on masonry structures. Based on a combined use of structural models and health monitoring systems, indications and operational tools will be provided for the identification and quantification of structural damage, supporting the management of built cultural heritage. To this purpose, a two-storey masonry building, having a single room with a vault at the first floor and a timber roof, was built with the aim of being monitored and progressively and will be damaged during the project. It is equipped with a hybrid SHM system managed by the University of Perugia, which is based on both vibration and strain measurements. The present paper illustrates the main features of the case-study building and presents the results of the experimental program aimed at characterizing the mechanical properties of masonry the materials used. The final part of the paper presents a blind prediction contest based on prediction of modal features of the building in different damaged configurations.

Data-driven method for damage localization on soft robotic grippers based on motion dynamics.

Damage detection is one of the critical challenges in operating soft robots in an industrial setting. In repetitive tasks, even a small cut or fatigue can propagate to large damage ceasing the complete operation process. Although research has shown that damage detection can be performed through an embedded sensor network, this approach leads to complicated sensorized systems with additional wiring and equipment, made using complex fabrication processes and often compromising the flexibility of the soft robotic body. Alternatively, in this paper, we proposed a non-invasive approach for damage detection and localization on soft grippers. The essential idea is to track changes in non-linear dynamics of a gripper due to possible damage, where minor changes in material and morphology lead to large differences in the force and torque feedback over time. To test this concept, we developed a classification model based on a bidirectional long short-time memory (biLSTM) network that discovers patterns of dynamics changes in force and torque signals measured at the mounting point. To evaluate this model, we employed a two-fingered Fin Ray gripper and collected data for 43 damage configurations. The experimental results show nearly perfect damage detection accuracy and 97% of its localization. We have also tested the effect of the gripper orientation and the length of time-series data. By shaking the gripper with an optimal roll angle, the localization accuracy can exceed 95% and increase further with additional gripper orientations. The results also show that two periods of the gripper oscillation, i.e., roughly 50 data points, are enough to achieve a reasonable level of damage localization.

Integrating flexibility-based curvature with quasi-static features induced by traffic loads for high-resolution damage localization in bridges

Curvature is one of the most popular damage-sensitive features in vibration-based structural health monitoring applications, typically calculated from identified modal features. While the relevant strategic or historical importance of bridges may justify dense sensor networks, a limited budget is generally assigned to monitor “minor” viaducts, thus involving inexpensive devices or extremely sparse sensing solutions. Modal parameters can only be obtained at instrumented locations. Thereby, damage assessment methods based on identified features typically have a low spatial resolution, especially when using low-cost monitoring setups with a modest number of sensing devices. This paper proposes an original identification method for the curvature of bridges based on sparse acceleration measurements that can be collected using standard accelerometers. The raw acceleration signal is processed through a particular filter bank that extracts dynamic and quasi-static signal components. The first components are employed to identify modal parameters, from which sparse yet robust estimates of the structural curvature are retrieved. On the other hand, the quasi-static acceleration generated by the structural deflection induced by traffic load is used to identify the curvature influence lines of the bridge, which are fused with modal estimates using a Kalman filter. The state variable of the analyzed system, representing a dense curvature profile of the structure subjected to concentrated loads, can be used as a damage-sensitive feature for high-resolution damage localization. The method is applied to a steel truss bridge subject to different damage configurations.

Phased Array Ultrasonic Imaging Of Damage In CFRP Laminates Under Low-Velocity Impact

In the last few decades, fibre-reinforced composites have seen significant growth in use in aircraft and automotive structures because of their superior properties such as high specific strength and stiffness, good fatigue and wear tolerance. During operation, these structures are subjected to different loading conditions including impact which may cause damage to them. Damage caused by lowvelocity impacts is more severe since it is undetectable in general visual inspections but it may reduce structural integrity significantly. In this work behavior of CFRP laminates under low-velocity impact is investigated. The effect of the impact energy on the damage is studied for the different stacking sequences of CFRP laminates. Composite laminates are fabricated with different stacking sequences and tested with a drop weight impact testing machine under different impact energies. Phased array ultrasonic technique is used to investigate the damage configuration of impacted specimens. A comparative study on damage shape and size as a function of the impact energy is done for different stacking sequences.

Eigenpropertiesof multi-cracked circular arches>

Despite the numerous explicit solutions of free vibration of arches with regular cross sections, in case of concentrated defects such as cracks, no procedure is available to analyse arch vibrations without sub-division of the integration domain. As a result, curved sub-elements comprised between crack and external constraints, or successive cracks, are considered.In this paper a distributional approach is adopted to provide a formulation of the free vibration differential governing equations of circular inextensible arches over a unique integration domain in presence of multiple concentrated open (non-breathing) cracks. Discontinuities due to the presence of an arbitrary number of cracks are modelled by means of Dirac's deltas. An integration procedure is devised to offer closed form solutions of the relevant vibration modes together with the relevant frequency determinantal equation. Natural frequencies and mode shapes of damaged arches with different damage and restraint configurations have been evaluated and compared with experimental results available in the literature as well as finite element numerical simulations. The presented closed form solutions are also employed for two parametric studies to evaluate the influence of an increasing number of along axis concentrated cracks as well as of the location of cracks along the arch span.

Deep learning paradigm for prediction of stress distribution in damaged structural components with stress concentrations

Scientists and engineers agree that solving complex problems requires integrating traditional physics-based modeling techniques with state-of-the-art deep learning (DL) methods. This paper aims to integrate physics knowledge into a convolutional neural network (CNN) to boost learning within a feasible solution space in a specific domain. Our proposed method uses deep neural networks in the form of (CNNs) augmented with custom loss functions which uses physics rules to bypass the need for Finite Element Analysis and predict high-resolution stress distributions on damaged steel plates with variable loading and boundary conditions. We embedded physics constraints into the loss function to enforce the model training, precisely capturing stress concentrations around the tips of various structural damage configurations. The CNN was designed and trained to use the geometry, boundary conditions, and load as input and predict the stress contours. The proposed framework’s performance is compared to Finite-Element simulations using partial differential equation (PDE) solver. The trained DL model can predict the stress distributions of damaged steel plates with a mean absolute error of 0.22% percent and an absolute peak error of 1.5% for the Von Mises stress distribution

Estimators for Structural Damage Detection Using Principal Component Analysis

Structural damage detection is an important issue in conservation. In this research, principal component analysis (PCA) has been applied to the temporal variation of modal frequencies obtained from a dynamic test of a scaled steel structure subjected to different damages and different temperatures. PCA has been applied in order to reduce, as much as possible, the number of variables involved in the problem of structural damage detection. The aim of the PCA study is to determine the minimum number of principal components necessary to explain all the modal frequency variation. Three estimators have been studied: T2 (the square of the vector norm of the projection in the principal component plan), Q (the square of the norm of the residual vector), and the variance explained. In the study, the results related to the undamaged structure needed one principal component to explain the modal frequency variation. However, the high damage configurations need five principal components to explain the modal frequency. The T2 and Q estimators have been arranged in order of increasing damage for all the performed experimental tests. The results indicate that these estimators could be useful to detect damage and to distinguish among a range of intensities of structural damage.

Free vibration analysis of in-plane circular curved beams with crack damage: a semi analytical solution

In this paper, a semi-analytical method for solving circular curved beams is proposed to study the free vibration of in-plane circular curved beams in both undamaged and damaged configurations. The crack damage of the structure is represented by the cross-sectional reduction of the damaged element. Based on the discrete circular curved beam model, the coupling stiffness matrices of shear, compression and bending are derived. Combined with the lumped mass matrix and the dynamic characteristic equation of the multi-degree-of-freedom system, the frequencies and modes of the damaged and undamaged structures are calculated. The results are compared with the finite element method, and the good consistency between them is verified.

NLFEA based design optimization of GFRP strips in partially confined concrete

The present study aims to introduce a nonlinear finite element approach (NLFEA) carried out on repaired concrete members under axially compressive loading. The main objective is to assess the effect of design parameters of FRP stirrups based on various confinement rate. The constitutive materials were modeled according to numerical models embedded in ABAQUS software namely: Concrete Damaged Plasticity model to take into account the nonlinear behavior of compressive and strained concrete, coupled with damage theory to represent the cracks evolution. An orthotropic-elastic model to predict FRP behavior with Tsai-Wu failure criteria is used. Indeed, the proposed approach is validated by experimental models available in the literature. In conclusion, the predicted numerical results for various design of FRP stirrups and damage configurations highlight the promising of used FRP composites in the repair of concrete members in terms of mechanical performances enhancement.