Damage Metrics Research Articles

Understanding damage in polymer-bonded explosive composites

Polymer matrix particulate composites comprise the majority of solid-phase high explosives, and most show considerable deterioration in mechanical properties when damaged. We have quantified this effect in three RDX–HTPB composites by measuring four damage metrics; the change in compressive strength, modulus, thermal conductivity and porosity, with increasing impact strain (the causal metric). This approach was applied to three RDX–HTPB composites containing (a) coarse, (b) fine and (c) both coarse and fine particles. Damage was applied by compression to predetermined levels of strain at strain-rates of the order of 103 s−1. All three materials exhibited deterioration in strength and storage modulus, but only the composites containing coarse particles showed significant changes in porosity or thermal conductivity with increasing specific impact energy. This is because the fine-particle composites mask internal damage by recovering their initial form, the resultant cracks are closed, whereas the coarse particles underwent grain reorientation when impacted and are left open. This last point highlights the difference between active and passive assessments of damage since the former do not change the density or thermal conductivity of the material. The deterioration of secant modulus that results from damage can also be predicted using a simple energy-activation model.

Application of electromechanical impedance-based SHM for damage detection in bolted pipeline connection

The work discusses the effectiveness of the electromechanical impedance-based Structural Health Monitoring system for damage detection in a laboratory test stand – a bolted pipeline section. The impedance-based system developed by the authors and equipped with 12 piezoelectric transducers was used to acquire the data. Different damage scenarios related to loosened bolts and measurement configurations are analysed. Both point and transfer frequency response functions are applied to deterministic and stochastic damage metrics, which are used to assess the condition of the monitored structure. The thresholds levels are proposed for different measurement configurations. Moreover, the authors discuss the perspective to determine the size and localisation of a damage. As confirmed in the work, the stochastic damage metric, preferably applied with a transfer frequency response, is found as of the most practical significance for the tested structure. The carried out analyses consider an outlier removal technique, which becomes necessary to prevent from errors due to temporary variation of the acquired characteristics after initialisation of the measurements.

Damage Identification in Active Plates with Indices Based on Gaussian Confidence Ellipses Obtained of the Electromechanical Admittance

Structural health monitoring (SHM) is an important area of study in the diagnosis of structural failures. Through SHM, structures can be diagnosed by electromechanical impedance (EMI) technique to detect changes in operative state. The signals of EMI obtained from piezoelectric transducers (PZT) are processed to quantify and classify damage severities by means of indices. These indices are studied and analyzed to recognize damage patterns in the electrical signals emitted by PZTs. In this research, an experimental analysis is carried out to identify structural damage in active plates with indices based on Gaussian confidence ellipses of the EM admittance. Three experimental tests are performed to assess the feasibility of the indices in the damage identification. A damage metric is depicted in each test together with the conductance (G) and susceptance (B), which were analyzed from different points of view. A probabilistic procedure is established to estimate Gaussian ellipses from a structure without damage with the aim to establish an alert baseline before that damage is induced. The results show that using the proposed methodology, the damage identification is a feasible procedure in the proposed case studies. Therefore, the presented analysis can be extrapolated to other applications to identify damage and so to test the feasibility of the methodology in other context.

Differentiation between Subtypes of Primary Progressive Aphasia by Using Cortical Thickness and Diffusion-Tensor MR Imaging Measures.

To test a multimodal magnetic resonance (MR) imaging-based approach composed of cortical thickness and white matter (WM) damage metrics to discriminate between variants of primary progressive aphasia (PPA) that are nonfluent and/or agrammatic (NFVPPA) and semantic (SVPPA). This study was approved by the local ethics committees on human studies, and written informed consent from all patients was obtained before their enrollment. T1-weighted and diffusion-tensor (DT) MR images were obtained from 13 NFVPPA patients, 13 SVPPA patients, and 23 healthy control participants. Cortical thickness and DT MR imaging indices from the long-associative and interhemispheric WM tracts were obtained. A random forest (RF) analysis was used to identify the image features associated with each clinical syndrome. Individual patient classification was performed by using receiver operator characteristic curve analysis with cortical thickness, DT MR imaging, and a combination of the two modalities. RESULTS RF analysis showed that the best markers to differentiate the two PPA variants at an individual patient level among cortical thickness and DT MR imaging metrics were diffusivity abnormalities of the left inferior longitudinal and uncinate fasciculi and cortical thickness measures of the left temporal pole and inferior frontal gyrus. A combination of cortical thickness and DT MR imaging measures (the so-called gray-matter-and-WM model) was able to distinguish patients with NFVPPA and SVPPA with the following classification pattern: area under the curve, 0.91; accuracy, 0.89; sensitivity, 0.92; specificity, 0.85. Leave-one-out analysis demonstrated that the gray matter and WM model is more robust than the single MR modality models to distinguish PPA variants (accuracy was 0.86, 0.73, and 0.68 for the gray matter and WM model, the gray matter-only model, and the WM-only model, respectively). A combination of structural and DT MR imaging metrics may provide a quantitative procedure to distinguish NFVPPA and SVPPA patients at an individual patient level. The discrimination accuracies obtained suggest that the gray matter and WM model is potentially relevant for the differential diagnosis of the PPA variants in clinical practice.

Advanced Fatigue Crack Detection Using Nonlinear Self-Sensing Impedance Technique for Automated NDE of Metallic Structures

This article reports the application of a nonlinear impedance technique under a low-frequency vibration to detect contact-type structural defects such as fatigue cracks. If the contact-type damage is developed within the structure due to the low-frequency dynamic load, the vibration can cause a nonlinear fluctuation of the structural impedance because of the contact acoustic nonlinearity (CAN). This nonlinear effect can lead to amplitude modulation and phase modulation of the current flow. The nonlinear characteristics of the structural impedance can be extracted by observing the coupled electromechanical impedance of a piezoelectric active sensor and utilizing nonlinear wave modulation spectroscopy. Experimentally, a low-frequency vibration was applied to a notched coupon at a certain natural frequency by a shaker, so that a nonlinear fatigue crack can be artificially formed at the notch tip. Then, the nonlinear features are extracted based on a self-sensing impedance measurement from a host structure under a low-frequency vibration. The damage metric was established based on the nonlinear fluctuation of the impedance due to the CAN.

Impedance-based fault detection methodology for rotating machines

Visual examination, ultrasonic tests, and dye penetrant inspection are some examples of nondestructive techniques widely used for crack detection in rotors. These methods have proved to be costly, since satisfactory results rely on detailed and periodic inspections. Significant research effort has been directed in recent years to online monitoring techniques, that is, based on vibration signals measured during rotor operation. However, most of them are able to only detect deep cracks. The uniqueness of this article relies on the possibility of detection of incipient transverse cracks in rotating shafts using the so-called, electromechanical impedance method. This method has become a promising tool for structural health monitoring of systems due to its sensitivity to small local damage. Basically, the method monitors changes in the electric impedance of piezoelectric transducers, bonded to (or embedded into) the host structure, through specific mathematic functions, the so-called damage metrics, to detect damage. This is possible because the electrical impedance of the transducer is directly related to the mechanical impedance of the structure. In this context, successful experimental tests were performed in a horizontal rotor supported by roller bearings. Lead zirconate titanate (PZT) patches were bonded along the shaft of the rotor in which saw cuts approximating a breathing transverse crack were machined. The technique was validated under different rotating speeds and unbalance conditions.

Development and validation of a novel earthquake damage estimation scheme based on the continuous wavelet transform of input and output acceleration measurements

SummaryThis paper presents the development and validation of several novel data‐driven damage sensitive features. The proposed features are based on the Continuous Wavelet Transform of both the input acceleration signal to the structure and the output acceleration response. The combination of the input and output wavelet coefficients and the derivation of the features is presented. The features are applied to experimental data obtained from shake table tests on reinforced concrete bridge columns. The results are compared against typically used damage metrics, such as hysteretic energy, and exhibit high correlation with damage. The performance of the features in binary damage detection is evaluated using numerical simulations of reinforced concrete columns under earthquake loading. A damage classification scheme based on the developed features and established damage indices is proposed and validated through Monte Carlo simulation. The proposed features are applied to experimental and simulated data from a multistory frame, illustrating the features' capabilities for damage localization in civil structures. Due to its data‐driven nature and use of strong motion recordings, the proposed damage detection scheme can be tailored to a wide variety of applications and deliver damage information immediately after an earthquake. Copyright © 2014 John Wiley & Sons, Ltd.

Non-destructive assessment of the fatigue strength and damage progression of satin woven fiber reinforced polymer matrix composites

The aim of this study is to utilize infrared thermography to assess the critical damage states, and to capture the evolving damage processes, of 5HS and 8HS woven carbon fiber/epoxy composites subjected to uniaxial in-plane tensile quasi-static and fatigue loading. Quasi-static test results revealed that the dominant damage mechanisms were matrix cracks contained within the weft yarns, which initiated at the thermally-detected material thermoelastic limit and were confirmed through SEM observations. An established thermographic technique was also used to confirm the existence of a high cycle fatigue limit, which may in fact be a characteristic of all fabric reinforced polymeric composites. Temperature profiles captured during cyclic testing directly correlated with corresponding stiffness degradation profiles, providing support for thermography as an accurate fatigue damage metric. The infrared camera was able to detect the evolution of weft yarn cracking during the initial stage, as well as the initiation and growth of interply delamination cracking during the final stage of three-stage cyclic damage evolution. The reported results and observations provide an important step in the validation of thermography as a powerful non-destructive tool for assessing the development of damage, as well as predicting the critical damage states of fiber reinforced polymeric composite materials.

Damage resistance of aluminum core honeycomb sandwich panels with carbon/epoxy face sheets

The damage resistance of composite sandwich structures with eight and 16 ply quasi-isotropic, carbon/epoxy face sheets and aluminum honeycomb core is evaluated. The external damage is induced quasi-statically, using spherical steel indentors under displacement control, to be in the vicinity of the barely visible threshold. In addition to the face sheet thickness, other parameters that are varied include the core thickness, core density, face sheet layup, and indentor diameter. The effect of these parameters on the extent of damage is evaluated using the damage metrics of dent depth, dent diameter, and planar area of delamination. When dent depth or dent diameter is considered as the damage metric, specimens containing a higher density core are always found to be the most damage resistant. When planar area of delamination is considered as the damage metric, the eight ply configuration comprised of a lower density core and face sheets containing only small ply angle changes are found to be the most damage resistant. However, this configuration is found to be the least damage resistant when this damage metric is applied to the 16 ply specimens. Rather, the best delamination resistance is provided by a 16 ply configuration with a high density core and face sheets that have ±45° ply groups at the beginning and ending of their stacking sequence.

Damage assessment based on general signal correlation. Application for delamination diagnosis in composite structures

Abstract This work presents a Vibration-Based Structural Health Monitoring (VSHM) technique which is developed and applied for delamination assessment in composite laminate structures. It suggests the mutual information as a measure for nonlinear signal cross correlation. The mutual information between two signals measured on a vibrating structure is suggested as a damage metric and its application for the purposes of damage assessment is discussed and compared to the application of the traditional linear signal cross-correlation. The cross correlation is capable to detect linear dependence between two signals and thus can be used for diagnosing damage on linearly vibrating structures. On the other hand the mutual information is a nonlinear metric, and it is shown that it can detect linear as well as nonlinear signal dependence and thus it is particularly appropriate for structures with nonlinear dynamic behavior and for composite structures as such. The application of the mutual information as a damage metric is demonstrated and discussed first for the case of a simple 2 DOF system with a nonlinear stiffness. Eventually the application of the suggested damage metric is developed and demonstrated for the purposes of delamination diagnosis in a composite laminate beam.

Modal flexibility-based damage detection of cantilever beam-type structures using baseline modification

Abstract This paper presents a new damage detection approach for cantilever beam-type structures using the damage-induced inter-storey deflection (DIID) estimated by modal flexibility matrix. This approach can be utilized for damage detection of cantilever beam-type structures such as super high-rise buildings, high-rise apartment buildings, etc. Analytical studies on the DIID of cantilever beam-type structures have shown that the DIID abruptly occurs from damage location. Baseline modification concept was newly introduced to detect multiple damages in cantilever beam-type structures by changing the baseline to the prior damage location. This approach has a clear theoretical base and directly identifies damage location(s) without the use of a finite element (FE) model. For validating the applicability of the proposed approach to cantilever beam-type structures, a series of numerical and experimental studies on a 10-storey building model were carried out. From the tests, it was found that the damage locations can be successfully identified by the proposed approach for multiple damages as well as a single damage. In order to confirm the superiority of the proposed approach, a comparative study was carried out on two well-known damage metrics such as modal strain-based damage index approach and uniform load surface curvature approach.

Experimental analyses of metal-composite bonded joints: damage identification

Abstract The advent of composite co-cured and co-bonded integrated construction in aircraft structures has lead to the replacement of fastened joints with bonded joints between the skins and the stiffeners. Skin-stiffener debondings could occur due to impact or other operational reasons and it is usually internal failure. Damage identification of bonded components, which are often vital elements in many structures, is crucial for the prevention of failure of the entire structure. Thus, different researchers have investigated vibration-based methods as an alternative technique to be used in the structural health monitoring (SHM) systems. Hence, this work consists of investigating experimentally through the vibration-based method, the dynamic behavior changes in a bonded metal-composite structure by using piezoelectric transducer and accelerometers in order to monitory the damage. The damage is an artificial debonding in the joint, which was simulated by inserting Teflon™ tapes within the joint. In-situ inspection as ensured by accelerometer and piezoelectric transducers (PZT) bonded to the structure. Indeed, with a simple comparison of the frequency response functions is difficult to conclude if there is damage in the structure, unless a large damage is presented. However, by using damage metrics, it is possible to identify the damage with more accuracy. Thus, the experimental results obtained by the accelerometers were compared to the data provided by the smart composite sensors (PZT). Finally, it was discussed the advantages and limitations of the experimental analyses and the identification technique proposal.

Night-time lights time series of tsunami damage, recovery, and economic metrics in Sumatra, Indonesia

On 26 December 2004, a magnitude 9.2 earthquake off the west coast of the northern Sumatra, Indonesia, resulted in 160,000 Indonesians killed. We examine the Defense Meteorological Satellite Program-Operational Linescan System night-time light imagery brightness values for 307 communities in the Study of the Tsunami Aftermath and Recovery (STAR), a household survey in Sumatra from 2004 to 2008. We examined nightlight time series between the annual brightness and extent of damage, economic metrics collected from STAR households and aggregated to the community level. There were significant changes in brightness values from 2004 to 2008 with a significant drop in brightness values in 2005 due to the tsunami and pre-tsunami night-time light values returning in 2006 for all damage zones. There were significant relationships between the night-time imagery brightness and per capita expenditures, and spending on energy and on food. Results suggest that Defense Meteorological Satellite Program night-time light imagery can be used to capture the impacts and recovery from the tsunami and other natural disasters and estimate time series economic metrics at the community level in developing countries.

Discrete multi-pulse laser ablation depth profiling with a single-collector ICP-MS: Sub-micron U–Pb geochronology of zircon and the effect of radiation damage on depth-dependent fractionation

A discrete multi-pulse method for single-collector ICP-MS laser ablation systems is presented that interrogates isotopic variation as a function of sample depth. The fidelity of the method is assessed with a 183-sample U–Pb analysis session of zircons with known age. By using bursts of 5 laser pulses the method resolves integration-level ages with ~0.55μm depth resolution and ~6% 2σ age uncertainty. To avoid signal aliasing, isotopic ratios are calculated using total ion counts for each integration, instead of on a cycle-by-cycle basis. Fractionation correction is achieved by constructing a continuous-function, non-parametric 3D surface from which discrete values for any time and sample depth can be calculated. At the sample level (15 integrations for this study), average 2σ uncertainty is ~2.5% for 206Pb/238U ages; 95% of samples and ~90% of integrations overlap with their accepted age at 2σ. The data reduction software developed here is designed to be flexible and a discussion of the effects of varying method parameters is provided. Total ablation depth is measured using white light interferometry, ranges between 7 and 10μm and is found to vary as a function of parent radionuclide concentration, measures of crystal lattice disorganization from Raman spectroscopy, and metrics of radiation damage (alpha dose). These data indicate that radiation damage exerts a fundamental control on laser ablation efficiency, although the exact physical process is unknown at present. Consequently, fractionation correction factors derived for a reference material may not be appropriate for unknowns with vastly different crystal structure.

Damage Detection of Composite Plates by Lamb Wave Ultrasonic Tomography with a Sparse Hexagonal Network Using Damage Progression Trends

Lamb wave based structural health monitoring shows a lot of potential for damage detection of composite structures. However, currently there is no agreement upon optimal network arrangement or detection algorithm. The objective of this research is to develop a sparse network that can be expanded to detect damage over a large area. To achieve this, a novel technique based on damage progression history has been developed. This technique gives an amplification factor to data along actuator-sensor paths that show a steady reduction in transmitted power as induced damage progresses and is implemented with the reconstruction algorithm for probabilistic inspection of damage (RAPID) technique. Two damage metrics are used with the algorithm and a comparison is made to the more commonly used signal difference coefficient (SDC) metric. Best case results show that damage is detected within 12 mm. The algorithm is also run on a more sparse network with no damage detection, therefore indicating that the selected arrangement is the most sparse arrangement with this configuration.

Probabilistic Neural Network and Fuzzy Cluster Analysis Methods Applied to Impedance-Based SHM for Damage Classification

Impedance-based structural health monitoring technique is performed by measuring the variation of the electromechanical impedance of the structure caused by the presence of damage. The impedance signals are collected from patches of piezoelectric material bonded on the surface of the structure (or embedded). Through these piezoceramic sensor-actuators, the electromechanical impedance, which is directly related to the mechanical impedance of the structure, is obtained. Based on the variation of the impedance signals, the presence of damage can be detected. A particular damage metric is used to quantify the damage. Distinguishing damage groups from a universe containing different types of damage is a major challenge in structural health monitoring. There are several types of failures that can occur in a given structure, such as cracks, fissures, loss of mechanical components (e.g., rivets), corrosion, and wear. It is important to characterize each type of damage from the impedance signals considered. In the present paper, probabilistic neural network and fuzzy cluster analysis methods are used for identification, localization, and classification of two types of damage, namely, cracks and rivet losses. The results show that probabilistic neural network and fuzzy cluster analysis methods are useful for identification, localization, and classification of these types of damage.

Motor recovery from constraint induced movement therapy is not constrained by extent of tissue damage following stroke.

The purpose of this study was to delineate the relationship between several types of T1-weighted MRI pathology and motor rehabilitation potential following Constraint Induced Movement therapy (CI therapy) in chronic stroke. Stepwise regression was employed (n = 80) to identify predictors of motor recovery (prior to therapy) and of response to Constraint-Induced Movement therapy [measured via the Wolf Motor Function Test (WMFT) and Motor Activity Log (MAL)] from among the following: age, side of motor deficit, chronicity, gender, lesion volume, peri-infarct damage volume, white matter hypointensity volume, ventricular asymmetry, and lesion location. Although extent of total stroke damage weakly correlated with poorer performance on the WMFT prior to therapy, this relationship was mediated by the location of the damage. No metric of tissue damage examined here was associated with real-world arm use at baseline (MAL at pre-treatment) or with CI therapy-induced improvement in either best motor performance upon request (WMFT) or spontaneous arm use for daily activities (MAL). In sum, the extent of brain tissue damage of any type examined here poorly predicted motor function and response to rehabilitation in chronic stroke.

Response of impedance measured by polyvinylidene fluoride film sensors to damage propagation for wind turbine blade

To establish an effective operation and maintenance system for the wind turbine system, techniques for early detecting the damage, which may occur during its operation, may be required. In this study, responses of impedance, which can be a technique to early detect the damage, to the damage extension in the wind turbine blade were investigated through the full-scale structural test of the 100 kW wind blade. The impedance was measured with polyvinylidene fluoride film sensors with dimension of 25 × 20 mm2 patched on the blade skin. The damages were initiated along the trailing and leading edges and extended with increasing static load level. Impedance signatures varied with increasing the damage size were analyzed in the frequency ranging from 1 to 300 MHz. It was found that the patterns of the impedance signatures are remarkably dependent upon the static load level and sensor location. The change in the signatures was quantitatively quantified by the damage metric. The scalar metric values were closely correlated to the damage extension size and the sensor locations to the extended damage.

Mechanisms of microbubble–vessel interactions and induced stresses: A numerical study

Oscillating microbubbles within microvessels could induce stresses that lead to bioeffects or vascular damage. Previous work has attributed vascular damage to the vessel expansion or bubble jet. However, ultra-high speed images of recent studies suggest that it could happen due to the vascular invagination. Numerical simulations of confined bubbles could provide insight into understanding the mechanism behind bubble-vessel interactions. In this study, a finite element model of a coupled bubble/fluid/vessel system was developed and validated with experimental data. Also, for a more realistic study viscoelastic properties of microvessels were assessed and incorporated into this comprehensive numerical model. The wall shear stress (WSS) and circumferential stress (CS), metrics of vascular damage, were calculated from these simulations. Resultant amplitudes of oscillation were within 15% of those measured in experiments (four cases). Among the experimental cases, it was numerically found that maximum WSS values were between 1.1-18.3 kPa during bubble expansion and 1.5-74 kPa during bubble collapse. CS was between 0.43-2.2 MPa during expansion and 0.44-6 MPa while invaginated. This finding confirmed that vascular damage could occur during vascular invaginations. Predicted thresholds in which these stresses are higher during vessel invagination were calculated from simulations.

Consumed Fatigue Life Assessment of Composite Material Structures by Optical Surface Roughness Inspection

A strong knowledge of the fatigue state of highly advanced carbon fiber reinforced polymer composite (CFRP) structures is essential to predict the residual life and optimize intervals of structural inspection, repairs, and/or replacements. Current techniques are based mostly in measurement of structural loads throughout the service life by electric strain gauge sensors. These sensors are affected by extreme environmental conditions and by fatigue loads in such a way that the sensors and their systems require exhaustive maintenance throughout system life.This work is focused on providing a new technique to evaluate the fatigue state of CFRP structures by means of evaluating the surface roughness variation due to fatigue damage. The surface roughness is a property that can be measured in the field by optical techniques such as speckle and could be a useful tool for structural health monitoring. The relation between surface roughness and fatigue life has been assessed on CFRP test specimens. A tensile fatigue load with an R=0.1 (T-T) and a maximum load of 60% of the material ultimate strength has been applied. The surface roughness of the specimens has been determined from the surface topography measured by a high precision confocal microscope. Results show that the surface roughness of the specimens increases with the accumulation of fatigue cycles in such a way that the roughness could be taken into account as a fatigue damage metrics for CFRP.