Local Damage Research Articles

Efficacy of modal curvature damage detection in various pre-damage data assumptions and modal identification techniques

The efficacy of modal curvature approach for damage localization is discussed in the paper in the context of input data. Three modal identification methods, i.e., Eigensystem Realization Algorithm (ERA), Natural Excitation Technique with ERA (NExT-ERA) and Covariance Driven Stochastic Subspace Identification (SSI-Cov), and four methods of determining baseline data, i.e., real measurement of the undamaged state, analytical function, Finite Element (FE) model and approximation of current experimental mode shape, are considered. Practical conclusions are formulated based on analysis of two cases. The first is a laboratory beam with a notch and the second is a stonemasonry historic lighthouse with modern restoration in its upper part. The analysis shows that NExT-ERA and SSI-Cov in combination with approximation of current mode shape provide high efficacy in damage localization alongside relatively straightforward determination of baseline data. It proves that the construction of advanced FE models of a structure can be replaced with a much simpler method of baseline data acquisition. Furthermore, the research shows the structural mode shapes identified with ERA may not always indicate the presence of damage.

Research on Damage Detection of Dual-Rotor Synchronous Excitation Mine Screen Beams Based on Strain Mode Difference Vibration Mode Analysis

The frame beam structure of the mine screen, subjected to various excitations, is a critical component of mining machinery. Its stress is intricate, the operational environment is severe, and damage can lead to catastrophic failures resulting in machinery destruction and fatalities. Based on the characterization of the vibration response of mine screen frame beams with varying degrees of damage at the same location and with the same degree of damage but at different locations, this paper develops a method of strain modal difference vibration pattern analysis and damage feature extraction for the detection of structural damage in beams. This method is based on the sensitivity of the sudden change in vibration strain modal difference to small deformations. This method solves the problem of using the conventional structural finite element analysis or experimental modal analysis methods to obtain the displacement mode, intrinsic frequency, and other characteristics, which make it difficult to effectively identify the actual engineering, with the damage conditions of the damage state and damage location of the mine screen frame beam problems. The feasibility and validity of the engineering application of the concept are demonstrated through instances.

Thermal ablation of soft tissue by a single shock wave sonication of discrete foci within the given volume

New protocols have been developed for shockwave irradiation of soft tissue volumes using trajectories uniformly filled within the given shape by discrete foci, while pulsed millisecond sonication immediately formed a single ablation. The influence of the initial peak power with the same time-average power, the interfocus distance and the geometry of the external contour of the trajectory on the shape, volume and ablation rate was analyzed. The most advantageous is the saturation mode using a trajectory with an interfocus step 1.5 times greater than the transverse size of a single lesion. To obtain volumes of thermal ablation on the order of cubic centimeters, layer-by-layer sonication protocols are proposed, which allow to 2.5 times greater thermal ablation rate compared with protocols used in clinical practice. The advantage of the proposed shockwave protocols is the possibility of obtaining localized and predictable thermal damage without accompanying MRI monitoring.

Computer vision-based substructure isolation method for localized damage identification

In recent years, vision-based structural damage identification techniques have garnered significant attention due to their simplicity and cost-effectiveness. Nevertheless, dynamic response-based vision methods face challenges related to the limitations of the field of view (FOV), i.e., the extent of the FOV is often sacrificed in order to ensure sufficient monitoring accuracy, which reduces the amount of data available for structural health monitoring (SHM). This study presents a solution to this problem by employing the substructure isolation method (SIM), which focuses on local vibrations of the structure and enables local damage identification by isolating the area of interest. Additionally, a method combining kernelized correlation filter (KCF) with sub-pixel template matching is used to extract vibration information recorded by visual sensor. This strategy balances both the efficiency and accuracy of displacement extraction. In numerical simulations, the performance of the SIM based on acceleration response and displacement response is compared, demonstrating the potential compatibility of visual sensors with the SIM. Finally, the effectiveness of the proposed vision-based local damage identification method is validated through vibration testing of a shear frame model.

Advances of Oxidative Stress Impact in Periodontitis: Biomarkers and Effective Targeting Options.

Periodontitis is the most common inflammatory oral disease that affects around 15% of adults and contributes to severe periodontal tissue destruction with subsequent tooth loosening and loss. Among the main pathogenic mechanisms underlying periodontitis, excessive reactive oxygen species production and oxidative stress play a predominant role in inducing both local and systemic damage. Current therapeutic approaches have expanded the conventional methods combined with herbal antioxidant compounds to free radical-scavenging nanomaterials and infrared laser therapy, offering promising pre-clinical evidence in periodontitis management. Herein, we review the pathogenic mechanisms of reactive oxygen species tissue damage, along with recent advances in oxidative stress biomarkers and novel targeting options.

Multi-damage detection of composite blades via the curvature modal shape approach in combination with surface interpolation and extreme learning machine

In recent years, there has been a rise in renewable energy, which has led to an increase in equipment maintenance. The damage detection technique for wind turbine blades (WTBs) can reduce maintenance costs. The majority are not immediately applicable to structures that are in an operating condition. Motivated by the current constraints, a novel two-stage multi-damage quantitative detection approach in WTBs during operation has been proposed. The multiple damage locations are first identified by calculating the curvature modal shape (CMS) difference for the WTBs after the interpolation of the operating deflection shape (ODS) using surface interpolation (SI). Then the relationship between the natural frequencies and damage severities for the WTBs is determined utilizing the finite element method (FEM). The established correlation provides a natural frequency database that can be utilized for identifying the corresponding damage severities through the application of the Extreme Learning Machine (ELM) method, upon measuring the natural frequencies of the damaged WTB. The efficacy of the suggested damage detection methodology has been confirmed through simulations conducted on WTBs featuring two or three instances of damage. Moreover, the ODS along with natural frequencies of the WTBs exhibiting two or three damages are experimentally assessed using a Scanning Laser Doppler Vibrometer. The simulation and experiment verify that the presented method has satisfactory effectiveness in damage detection.

Detecting damage in composites using volume decomposition analysis of tomographic data

Detection of damage in a single tow ceramic matrix composite specimen has been achieved using orthogonal decomposition of volumetric tomographic datasets collected at four tensile loads. This decomposition approach has been applied at two different length scales: (i) individual fibres and (ii) bulk volumes containing fibres and matrix material. Volumes were first decomposed to feature vectors, orders of magnitude smaller than the original volume they describe, and then comparisons between datasets at different load levels were made in feature vector space. The results show quantitative measurements of damage location, damage morphology and the relative growth of this damage with increased load when compared with a dataset with less or no damage. No prior knowledge of the dataset or training of algorithms is required for damage to be detected, it is only necessary that at least two datasets are available for comparison, e.g. from in situ or repeated scanning measurements. Results are generated on significantly shorter timescales when compared with previous automated approaches to tomography data processing. This approach has the potential to be applied to damage detection in a range of materials through comparisons of volumetric datasets from a range of measurement or computational techniques.

A Novel Damage Localization Method of Circular Phased Array using Minimum Variance Distortionless Response Beamforming with Autocorrelation Matrix Diagonal Loading

A Novel Damage Localization Method of Circular Phased Array using Minimum Variance Distortionless Response Beamforming with Autocorrelation Matrix Diagonal Loading

A Stacked Neural Network Model for Damage Localization

A Stacked Neural Network Model for Damage Localization

Role of molecular damage in crack initiation mechanisms of tough elastomers

Tough soft materials such as multiple network elastomers (MNE) or filled elastomers are typically stretchable and include significant energy dissipation mechanisms that prevent or delay crack growth. Yet most studies and fracture models focus on steady-state propagation and damage is assumed to be decoupled from the local stress and strain fields near the crack tip. We report an in situ spatial-temporally resolved 3D measurement of molecular damage in mechanophore-labeled MNE just before a crack propagates. This technique, complemented by digital image correlation, allows us to compare the spatial distribution of both damage and deformation in single network (SN) elastomers and in MNE. Compared to SN, MNE have a wide-spread damage in front of the crack and, surprisingly, delocalize strain concentration. A continuum model, where damage distribution is fully coupled to the crack tip fields, is proposed to explain these results. Additional measurements of time-dependent molecular damage during fixed grips relaxation in the presence of a crack reveal that the less localized damage distribution delays fracture initiation. The observations and exploratory modeling reveal the dynamic fracture mechanism of MNE, providing guidance for rational design of high-performance tough elastomers.

Seismic Response Characteristics of a Utility Tunnel Crossing a River Considering Hydrodynamic Pressure Effects

As a long lifeline system of buried structures, the utility tunnel (UT) is vulnerable to earthquake invasion. For utility tunnels with inverted siphon arrangements crossing rivers, the seismic response is more complex due to the basin effect of acceleration in the topography and the influence of fluctuating hydrodynamic pressure, but there is currently a gap in targeted seismic response analyses and references. Based on a UT project in Haikou, this paper studied seismic responses of a cast-in-place UT considering the coupled model of water–soil–tunnel structure on ABAQUS software. Herein, the dynamic fluctuation of hydrodynamic pressure is simulated using an acoustic–solid interaction model. A viscoelastic artificial boundary was used to simulate the soil boundary effect, and seismic loads were equivalent to nodal forces. Considering seismic invading direction and varying water elevation, this paper investigates the dynamic response characteristics and damage mechanisms of river-crossing utility tunnels. This study shows that the basin effect causes the soil acceleration around the UT to show variability in different sections, and the amplification factor of the peak acceleration at the central location is almost doubled. The damage and dynamic water pressure of the UT are intensified under bidirectional seismic excitation, and the damage location is concentrated at the junction of the horizontal section and the vertical section. Bending moments and axial forces are the main mechanical behaviors along the axial direction. Changes in river levels have a certain positive effect on the UT peak MISES, DAMAGEC, and SDEG, and it exhibits a certain degree of energy dissipation and seismic damping effect. For the aseismic design of cross-river cast-in-place utility tunnels, bidirectional seismic calculations should be performed, and the influence of river hydrodynamic pressure should not be neglected.

Experiments for the Assessment of the Probabilistic Multistage Algorithm for Damage Detection in Flat and Curved CFRP Panels

The Probabilistic Multistage (PM) algorithm was developed by authors for identifying and localizing damages in isotropic plates. More specifically, PM algorithm consists of a fully automated probabilistic damage imaging methodology based on ultrasonic guided wave propagation and a 5-sensor array working in a pitch-catch approach. The algorithm processes the gathered data in three steps to identify key features associated with damage. The aim of this work is to assess the effectiveness of the PM algorithm on more complex structures. Specifically, the study investigates three cases of study, made of Carbon Fiber Reinforced Plastic (CFRP) composite, characterized by different geometries and layups. The algorithm is initially tested on panels with artificial damage in the form of a Teflon disk located in a specific location between the middle laminae of the panels, which is used to replicate the effect of delamination. In order to expand the experimental dataset without incurring additional costs or waste, new damage conditions are simulated by adding masses on the upper surface of the panels. Each plate is investigated considering three different damage sizes and 16 different damage locations. The proposed algorithm successfully detects damages both within and outside the sensor network. The PM algorithm produces a clear damage positioning map and a positioning (probabilistic field) range for the identified damage. This information can be used to assist operators in conducting inspections more efficiently by focusing on the highlighted areas, which may potentially lead to reduced maintenance and repair expenses.

Potential for 50% Mechanical Strength Decline in Sandstone Reservoirs Due to Salt Precipitation and CO2–Brine Interactions During Carbon Sequestration

AbstractPredictive modeling of CO2 storage sites requires a detailed understanding of physico-chemical processes and scale-up challenges. Dramatic injectivity decline may occur due to salt precipitation pore clogging in high-salinity aquifers during subsurface CO2 injection. This study aims to elucidate the impact of CO2-induced salt crystallization in the porous medium on the geomechanical properties of reservoir sandstones. As the impact of salt precipitation cannot be isolated from the precursor interactions with CO2 and acidified brine, we present a comprehensive review and discuss CO2 chemo-mechanical interactions with sandstones. Laboratory geochemical CO2–brine–rock interactions at elevated pressures and temperatures were conducted on two sandstone sets with contrasting petrophysical qualities. Interaction paths comprised treatment with (a) CO2-acidified brine and (b) supercritical injection until brine dry-out, salt crystallization, and growth. Afterward, the core samples were tested in a triaxial apparatus at varying stresses and temperatures. The elastic moduli of intact, CO2-acidified brine treated, and salt-affected sandstones were juxtaposed to elucidate the geochemical–geomechanical-coupled impacts and identify the extent of crystallization damages. The salt-affected sandstones showed a maximum of 50% reduction in Young’s and shear moduli and twice an increase in Poisson’s ratio compared to intact condition. The deterioration was notably higher for the tighter reservoir sandstones, with higher initial stiffness and lower porosity–permeability. We propose two pore- and grain-scale mechanisms to explain how salt crystallization contributes to stress localization and mechanical damage. The results highlight the potential integrity risk imposed by salt crystallization in (hyper)saline aquifers besides injectivity, signaling mechanical failure exacerbated by pressure buildup.

Buckling Behaviour of Q355 Angles with Simulated Local Damages at Bolted Connections

Transmission towers in service are highly susceptible to corrosion caused by environmental conditions. It is crucial to assess the residual load capacity of corroded angles in transmission towers. In this study, corrosion at the connection of angels was simulated by local damage using a mechanical cutting method, and compression tests and numerical simulations were performed to investigate the load capacity of corroded angles. A total of 24 angles were designed and tested in the experiments, and the parameters considered included the location and thickness of damage and slenderness. The local damage was designed on the loaded or non-loaded legs, with slendernesses of 80 and 140, and a thickness of damage of 1 mm and 2 mm. The residual load capacity, failure modes, and strain of the angles were analysed based on experimental results. Furthermore, corrosion was simulated by reducing the local thickness of angles using ABAQUS. The accuracy of numerical models was verified after comparing the numerical results with experimental data. Based on the verified model, parameter analysis was conducted, in which the slendernesses was extended to 100 and 120, and the local damage thickness was also set to be 0.5 mm and 1.5 mm to quantitatively study the influence on the residual load capacity. The tests results showed that with the damage depth at the ends of the angle increased, and the load capacity of the angle decreased by up to 6.7%. Finally, a design equation for calculating the residual load capacity of corroded angles was proposed using the numerical results. By comparing the design equation, experimental results, and load capacity calculated per existing standards, it was found that the load-bearing capacity of corroded angles can be accurately predicted by the equation.

Mechanics-informed autoencoder enables automated detection and localization of unforeseen structural damage

Structural health monitoring ensures the safety and longevity of structures like buildings and bridges. As the volume and scale of structures and the impact of their failure continue to grow, there is a dire need for SHM techniques that are scalable, inexpensive, can operate passively without human intervention, and are customized for each mechanical structure without the need for complex baseline models. We present a novel “deploy-and-forget” approach for automated detection and localization of damage in structures. It is a synergistic integration of entirely passive measurements from inexpensive sensors, data compression, and a mechanics-informed autoencoder. Once deployed, the model continuously learns and adapts a bespoke baseline model for each structure, learning from its undamaged state’s response characteristics. After learning from just 3 hours of data, it can autonomously detect and localize different types of unforeseen damage. Results from numerical simulations and experiments indicate that incorporating the mechanical characteristics into the autoencoder allows for up to a 35% improvement in the detection and localization of minor damage over a standard autoencoder. Our approach holds significant promise for reducing human intervention and inspection costs while enabling proactive and preventive maintenance strategies. This will extend the lifespan, reliability, and sustainability of civil infrastructures.

Exploration on flutter mechanism of a damaged transonic rotor blade using high-fidelity fluid–solid coupling method

Structural damage in turbomachinery is a primary origin of aeronautic accidents, which is receiving increased attention. This study is thus focused on the aeroelastic analysis of damaged blades, including the onset of flutter and underlying mechanisms. First, a high-fidelity fluid–solid coupling system is established with computational fluid dynamics (CFD) and computational structural dynamics (CSD) technologies, via which the dynamic aeroelastic analysis is conducted based on static aeroelastic deformation. Second, a damaged rotor blade is parametrically modelled with variable damage levels, extents, and positions. Finally, the modal identification method of spectral proper orthogonal decomposition (SPOD) is applied to observe flow details and provide physical insight into the flutter mechanism for damaged blades. Numerical analysis finds that there is a critical damage level below which the aeroelastic stability is positively improved with increasing damage level; otherwise, a significant loss of stability is induced. The damage location and extent further affect this critical damage level and the change rate crossing the threshold. The simulation with CFD/CSD finds that the high pressure near the trailing edge induced from boundary layer separation suppresses vibrations in stable conditions, but motivates vibrations during flutter, which is because of the high-pressure spread to nearing blades. SPOD modes reveal that high-frequency disturbances with large scale are primary factors inducing flutter, which is further stimulated by the high-order disturbances with small scale. This study provides a crucial foundation for the fatigue prediction for rotor blades in service and the optimisation design for high-performance turbomachinery in the near future.

Robustness of Dry‐Assembled Precast Wall and Coupled Wall‐Frame High‐Rise Structures With Voided Prestressed Slabs

ABSTRACTPrecast concrete structures are recognized among the structural typologies that may mostly suffer from progressive collapse as a consequence of local unpredicted damage, also due to past accidents occurred in buildings employing old precast technologies neglecting the basic robustness criteria and characterized by poorly detailed and/or executed joints and connections. Although vertical ties may relatively easily be provided in both frame and wall panel structures by employing ductile connection devices, dry‐assembled precast systems avoiding concrete pouring in the whole superstructure typically struggle to provide horizontal ties as strong as required by the current standards concerning progressive collapse, in which they are not fully framed yet. Nevertheless, these systems may exploit alternative sources of robustness to stop collapse progression arising from their structural arrangement, the shape of the slab elements employed, and the slab mechanical connections. This article presents the results of a numerical investigation focused on the structural behavior of a dry‐assembled precast floor system consisting of prestressed box‐section slab elements employed in either wall panel or coupled wall‐frame structural systems following the loss of one or multiple primary load‐bearing vertical elements. Nonlinear static simulations of different loss scenarios occurring in prototypes of 100‐m‐tall high‐rise buildings were carried out based upon spread plasticity modeling of the structural elements and experimentally calibrated nonlinear behavior of mechanical connections.

Damage detection and localization in a cantilever beam structure via regression-and-classification-based machine learning

Damage detection and localization in a cantilever beam structure via regression-and-classification-based machine learning

Impact of Various High Intensity Earthquake Characteristics on the Inelastic Seismic Response of Irregular Medium-Rise Buildings

In the twenty-first century, the seismic design of buildings seems to have become a fully recognized topic. There are guidelines and standards which should be taken into account by designers in seismic areas. Designers using modern international guidelines have ascertained that the behavior of structures is not as expected. New challenges in the construction industry result in the construction of structures with new, unusual shapes. These are structures that do not meet the assumptions of safe construction in seismic areas. Contemporary buildings are also characterized by their irregular distribution of structural elements. Such solutions are not beneficial from the point of view of seismic engineering and can lead to reduced dynamic resistance and damage in such structures. In this paper, a five-storey, irregular-shaped reinforced concrete (RC) building model was subjected to different earthquakes with varying magnitudes, PGA (peak ground acceleration) and PGV (peak ground velocity) values, and durations of the intense shock phase. Once the model was verified using previous in situ measurements, the building model was subjected to five earthquakes. A numerical nonlinear analysis of the building was performed using a verified FEA (finite element analysis) model in the time domain through non-linear time history analysis with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method. The building’s dynamic properties were measured using various methods of excitation. The model was influenced, among others, by two far-field representative events caused by the last earthquake in Turkey, which resulted in strong ground motion. The analysis results identified the locations of structural damage and allowed for the assessment of the structure’s dynamic resistance. The results of the calculations prove that the duration of the intensive phase of extortion is one of the reasons for building damage in earthquake-prone areas. Building damage occurs with earthquakes that are characterized by an intensive phase of excitation with a long duration and high values of velocity in the earthquake components. The article highlights the inadequate dynamic resistance of the building, leading to excessive displacements and unfavorable structural solutions. Damage to buildings at this earthquake intensity caused damage to the load-bearing structure, which was not designed for such intensities. This paper is a research report with a specific case study of medium-rise irregular RC buildings.

Robustness of wavelet features for damage detection with neural network and digital twin

Recent studies demonstrate that the wavelet energy–based features are highly sensitive to local damages, and accurate damage identification could be achieved by integrating such features with neural networks. However, the robustness of the features in practical applications and the feasibility of generating damage information with a digital twin to facilitate training of neural networks have not been systematically investigated. This paper aims to provide new insight into the practicality of using wavelet energy–based features for accurate damage detection of structures. A systematic investigation into the tolerance of the normalised wavelet packet node energy features with neural network (NWPNE-NN) approach against measurement noises, excitations uncertainties and limited frequency range in the measured responses is carried out, with consideration of data fusion from multiple measurement points. The feasibility of a digital twin to simulate damage scenarios and generate training data for neural networks is explored, and the use of relative WPNE as a new feature is proposed. The results show that the NWPNE-NN approach is capable of detecting and quantifying the main damage in a structure. The neural networks trained by data generated from a well-calibrated digital twin is capable of identifying damage in the actual structure.