Undamaged State Research Articles

External Strengthening of Corrosion-Defected Beam–Column Members Using a CFRP Sheet

The efficiency of external strengthening using CFRP (Carbon Fiber Reinforced Polymer) sheets to rehabilitate corrosion-defected RC (Reinforced Concrete) beam–column members is experimentally studied. ALL specimens were tested under a combined axial force and transverse load until failure. The axial forces were applied with two levels either 25% or 50% of the ultimate design load of control specimen. The accelerated corrosion process was used to get steel reinforcement corrosion inside the concrete at three levels, 0% and approximately 5% and 20%, according to Faraday’s law. External strengthening with a CFRP sheet was used in this study to overcome the effect of deterioration in the mechanical properties of the corroded steel bars. A significant deterioration in the load carrying capacity, stiffness, and serviceability was recorded for corrosion-defected specimens. The increase of the axial force was recorded as a positive effect on the ultimate strength, stiffness, and serviceability of the testing specimens. This effect was clearly evident for the defected specimens, with an increasing corrosion level, by decreasing the adverse effects of corrosion. The external strengthening with a CFRP sheet restored the load-carrying capacity, stiffness, and serviceability to an undamaged state.

Damage assessment of smart composite structures via machine learning: a review

Composite materials are heterogeneous in nature and suffer from complex non-linear modes of failure, such as delamination, matrix crack, fiber-breakage, and voids, among others. The early detection of damage in composite structures, such as airplanes, is imperative to avoid catastrophic failure and tragic consequences. This paper reports on the use of machine learning techniques for the damage assessment (i.e., detection, quantification, and localization) of smart composite structures. The success of the machine learning paradigm for damage assessment depends on the representational capability of the discriminative features for the problems of interest. However, from a practical standpoint, it is not possible to define a global or superset of discriminative features that could discriminate between damaged and undamaged states of the structures, and simultaneously make a distinction between various modes of failures. In addition, one machine learning algorithm may show optimum performance for the discriminative features of a particular problem but fails for others. This article focuses on a review of discriminative features and the corresponding machine learning algorithms (both supervised and unsupervised), for various types of damage in smart composite structures.

Dismantling and electrochemical copper recovery from Waste Printed Circuit Boards in H2SO4–CuSO4–NaCl solutions

The worldwide growing of electrical and electronic equipment makes increasingly urgent to find environmentally friendly treatments for e-waste. In this paper, the attention has been focused on i) the eco-friendly dismantling of the electronic components from Waste Printed Circuit Boards and ii) recovering of pure metallic copper, which is the most abundant metal and one of the most valuable in Printed Circuit Boards. After an experimental optimization study, we found that a solution containing 0.5 M H2SO4, 0.4 M CuSO4, and 4 M NaCl can be successfully used to disassemble the electronic components from the boards by leaching of all exposed metals. Air was blown into the leaching solution in order to regenerate Cu2+ ions, which acts as the predominant oxidant specie. The key role in dismantling/leaching process is played by Cl− ion that stabilizes Cu+ through the chloro-complexes formation. The results show that, in this manner, the electronic components can be easier disassembled in undamaged state, allowing the efficient recycling and valorization of the base materials. The feasibility to recover electrochemically the copper from the solution resulting from dismantling/leaching tests was verified through a preliminary cyclic voltammetry study aimed to investigate the copper electrodeposition in sulphate-chloride solutions in the presence of other metal ions such as Ni2+, Fe2+, Zn2+, Pb2+, Sn2+. A two-compartment electrochemical cell operating in either galvanostatic or potentiostatic mode was employed to investigate simultaneous copper recovery and leaching solution regeneration. The results indicate that, in both modes, pure copper can be obtained after the removal of all surface impurities by dipping in acidic concentrated sodium chloride solution. The galvanostatic mode leads to deposit of higher quality, meanwhile the potentiostatic one determines a faster deposition and leaching solution regeneration.

An Inverse Approach of Damage Identification Using Lamb Wave Tomography.

A pulse laser combined LWT technique with a two-stage reconstruction algorithm was proposed to realize rapid damage location, or even the evaluation of damage size for plate-like structures. Since the amplitude of Lamb waves in propagation is highly sensitive to damage, including inside damage, the change of the attenuation coefficient of Lamb waves in the inspection region was used as a damage index to reconstruct damage images. In stage one, the rough area of the damage was identified by a comparison of the amplitude of the testing signal data and reference data (undamaged state). In stage two, the damage image was reconstructed using an inverse approach based on the least-square method. In order to verify the effectiveness of the proposed rapid approach, experiments on an aluminum plate with a non-penetrating notch and a carbon fiber-reinforced plastic laminated plate with internal delamination induced by a low-velocity impact were carried out. The results show that the notch can be detected with accurate location, and the delamination image can be reconstructed successfully.

Rehabilitation of Corrosion-Defected RC Beam-Column Members Using Patch Repair Technique

An experimental study was conducted to evaluate the efficiency of patch repair to rehabilitate corrosion-defected reinforced concrete (RC) beam-column members when exposed to bending moments and axial forces. Ten RC beam-column members were tested under combined constant axial force and four-point transverse load up to failure. Two levels of the constant axial force were applied at either 15 kN or 30 kN (i.e., 25% or 50% of the ultimate design load of the control specimen). The accelerated corrosion process was used to get steel reinforcement corrosion inside the concrete of three levels, 0% and approximately 5% and 20%, according to Faraday’s law. The patch repair technique of cleaning or replacing corroded steel bars and replacing the damaged concrete cover with new mortar was used in this study. The experimental results of the corrosion-defected specimens showed a significant deterioration in the structural performance and the integrity by reducing ultimate capacity, stiffness, serviceability, and ductility. Additionally, the effect of increasing axial force was recorded clearly by reducing the adverse effect of corrosion, especially for defected specimens with high corrosion level. The deterioration of corrosion reinforcement could be overcome when using a patch repair technique, which restored the undamaged state and was shown clearly by using a patch repair technique with replacing corroded steel bars.

Numerical Simulation of Damage on Cementitious Sprayed Fire-Resistive Materials Applied on Steel Plates

Cementitious Sprayed Fire Resistive Materials (SFRMs) are extensively employed for the fire protection of steel structural members due to their cost-effective fire proofing capabilities. They are susceptible, however, to brittle failure, cracking and spalling when the underlying structural member is subjected to mechanical deformations. A numerical method combining the smeared crack model and the discrete crack concept in a Finite Element mesh splitting scheme, is proposed for the simulation of the damage occurring in the body of the material, leading to a more realistic modeling of the material spalling, which, in conjunction with the loss of interface bond between the SFRM and steel, allows individual pieces of the SFRM coating to detach from steel, leaving it exposed to thermal actions. The proposed method is implemented in a series of numerical models, simulating steel plates bearing 20 mm or 30 mm SFRM coating, which are submitted to constant bending moment, axial tension or axial compression. The numerical results of the failure mechanisms of the SFRM coatings, regarding the failure of the interface bond and the formation of transverse cracks, are in good agreement with the reported observations of the corresponding experimental tests found in the literature. A subsequent numerical thermal analysis of three damaged configurations of the SFRM coated plate, missing 10% to 60.5% of the SFRM coating, submitted to ISO-834 thermal load, indicated that the critical yield stress of the plate due to the temperature rise, is reached 38% to 76% faster in comparison to the undamaged state. The proposed method can be a very effective tool in the assessment and prediction of SFRM damage, as it could be applied on any structural configuration, allowing the further study of the parameters space.

On the 3D extension of failure models for adhesive joints under mixed-mode fracture conditions: LEBIM and CZM

Interface models for triggering damage events have been extensively used in many engineering applications due to their inherent versatility and relatively simple numerical implementations. Usually, the non-linear behavior of interfaces and thin adhesive joints between solids has been modeled using Cohesive Zone Models (CZMs) although other alternative models have been proposed as well. This is the case of the recently proposed Linear Elastic-Brittle Interface Model (LEBIM). The LEBIM is characterized by a linear constitutive law (traction-relative displacement relationship) in the undamaged state up to failure. Damage occurs when a material point reaches a critical energy release rate leading to an abrupt failure representation. Currently, from the numerical point of view, a great deal of research dealing with interface debonds and adhesive failure is still mainly focused on 2D models. The aim of the present investigation is to extend the LEBIM (originally proposed for 2D problems) for its applications to 3D problems under general fracture conditions and to examine its reliability against experimental data and cohesive-based interfaces pinpointing the main theoretical and numerical differences with respect to alternative methods. Thus, we focus our attention on addressing the main advantages of the proposed LEBIM over the nonlinear CZMs: (i) a simple interface law without the need of triggering a gradual stiffness degradation, (ii) a reliable accuracy in comparison with experimental results, endowing a clear identification of the crack front due to the preclusion of the fracture process zone concept, and (iii) a very high efficiency in terms of mesh requirements stemming from the absence of nonlinear cohesive crack representation. To show that 3D LEBIM is feasible it is implemented into the general purpose Finite Element Method (FEM) package ABAQUS through the user subroutine UMAT. Finally, special attention is given to the adequate treatment of the mixed mode fracture that may appear in complex 3D crack propagation cases.

Online Monitoring of Flexural Damage Index of a Cable‐Stayed Bridge

This work introduces a recent application of the online nondestructive damage assessment system into a cable‐stayed bridge. A set of ambient modal parameters are automatically extracted every 20 minutes using real‐time signal data collected from a total of 26 accelerometers attached on the deck plate of the bridge. Then, a set of modal flexibilities are reconstructed by the combination of the extracted modal parameters with the approximated modal mass of the girder. Next, the curvature of the modal flexibility is approximated by a central difference formula. Finally, the set of flexural damage index equations is constructed by comparing the modal curvature of the damaged state to that of the undamaged state. Solving the overdetermined flexural damage index equations, the desired damage index is finally quantified. The resulting index clearly indicates the location and severity of the potential structural damage on the girder. Based on the overall performance of the implemented health monitoring system, the bridge operator’s damage index control criteria are set to ±20% of the undamaged state.

Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network

This paper proposes a Convolutional Neural Network (CNN) based approach for the classification and prediction of various types of in-plane and through-the-thickness delamination in smart composite laminates using low-frequency structural vibration outputs. An electromechanically coupled mathematical model is developed for the healthy and delaminated smart composite laminates, and their structural vibration responses are obtained in the time domain. Short Time Fourier Transform (STFT) is employed to transform the transient responses into two-dimensional spectral frame representation. A convolutional neural network is incorporated to distinguish between the damaged and undamaged states, as well as various types of damage of the laminated composites, by automatically extracting discriminative features from the vibration-based spectrograms. The CNN showed a classification accuracy of 90.1% on one healthy and 12 delaminated cases. The study of the confusion matrix of CNN provided further insights into the physics of the problem. The predictive performance of a pre-trained CNN classifier was also evaluated on unseen cases of delamination, and physically consistent results were obtained.

Modal curvature-based damage localization in weakly damaged continuous beams

Abstract Modal curvatures have been claimed to contain local information on damage and to be less sensitive to environmental variables than natural frequencies. However, simply using the difference between modal curvatures in the undamaged and damaged states can result into localization errors, due to the complex pattern that this quantity presents when considering broad damages or higher order modes. In this paper, we consider weakly damaged continuous beam and we exploit a perturbative solution of the beam equation of motion to obtain an analytical expression of the modal curvature variations in terms of damage distribution. The solution is then used to introduce a filtering technique of the modal curvature variation and to set up the inverse problem of damage localization based on modal curvatures only. Using numerical examples and experimental tests, we show that modal curvatures can be used for precise damage localization, once properly filtered.

Structural Damage Identification of Bridges from Passing Test Vehicles.

This paper presents two approaches for the structural damage identification of a bridge from the dynamic response recorded from a test vehicle during its passage over the bridge. Using the acceleration response recorded by the vibration sensors mounted on a test vehicle during its passage over the bridge, along with the computed displacement response, the bending stiffness of the bridge can be determined using either: (1) the frequency-domain method based on the improved directed stiffness method with the identified frequency and corresponding mode shape, or (2) the time-domain method based on the residual vector of the least squares method with a fourth-order displacement moment. By comparing the bending stiffness values identified from the vehicle-collected data for the bridge under the undamaged and damaged states that are monitored regularly by the test vehicle, the bridge damage location and severity can be identified. Through numerical simulations and field tests, the present approaches are shown to be effective and feasible.

Optimization-based method for structural damage detection with consideration of uncertainties- a comparative study

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three well-known optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

An impedance-based structural health monitoring approach for looseness identification in bolted joint structure

The task of structural safety has been always vital throughout the life span of a structure. The situation deteriorates, when it is subject to repeated loading as seen in cases of railway joints. Generally, the bolted joints are frequently used connections for mainteinance of structural integrity. The most common type of fault observed in bolted joints is looseness of the nuts and bolts which leads to a damaging change by contact pressure that may cause an untoward incident. To avoid such incidents, it is required to monitor the bolted joints very meticulously and regularly. This study presents an investigational work for the looseness assessment of bolted butt joint structure using glued piezoelectric transducer and the implementation of an analytical approach based on the electro-mechanical impedance (EMI) method. For the purpose of investigation, the experiments are being conducted in pristine condition of the structure, wherein the plate bars and girder beam are bolted with four similar bolts without being pressed adequately and no part of the joint is glued. The test measurement of undamaged state and loosed state has been conducted using impedance-based monitoring approach. To study the effectiveness of the proposed method, an experimental investigation is conducted using the impedance chip AD5933 on a bolted joint structure. The results provide cogent indication about the use of piezoelectric lead zirconate titanate sensor based on EMI method for monitoring the status of the bolted joint structures.

Structural Damage Recognition Based on Perturbations of Curvature Mode Shape and Frequency

A new method for structural damage identification is presented based on perturbations of curvature mode shape and frequency. Firstly, the structure’s mass and stiffness matrices are expressed as functions of its elements’ physical parameters, which reflect their damage states. According to differences in the curvature mode shape of the structure in undamaged and damaged states, possible damage equations and determined damage equations are established and used to solve for the elements’ damage parameters. Then, to ensure the accuracy of the recognition result, a reasonable solution is substituted into a damage-checking equation based on the change of frequency of the damaged structure. Numerical examples are used to show that, to identify the damage, only one order mode needs to be tested. When the degree of damage is low, first-order perturbation equations can be used to recognize the damage with sufficient accuracy. If the extent of the damage is high, second-order perturbation equations can be used to provide more accurate identification results.

Robustness‐evaluation of a stochastic dynamic system and the instant equivalent extreme‐value event

AbstractMany theoretical methods for evaluating robustness have been developed in the last decades. Especially probability‐based robustness quantification promises to provide a rational basis for decision‐making. To allow for this type of robustness evaluation, the probability of failure (or the corresponding reliability index) of the structural system in the damaged and the undamaged state has to be determined. In this paper, the Probability Density Evolution Method (PDEM) is used to evaluate the dynamic reliability, taking into account the randomness which comes both from the excitation and from the stochastic system properties. The efficiency of the PDEM for robustness quantification is evaluated through a simple cargo crane example case. In addition, the instant equivalent extreme‐value event, which is quite different from the equivalent extreme‐value event for one variable, is applied to obtain the extreme value of reaction forces for each sample at instant time.

The Surface Interpolation Method for damage localization in plates

Abstract This paper presents a vibration based procedure for locating reductions of stiffness in plate-like structures. This procedure is a generalization to the two-dimensional case of the Interpolation Method (IM) previously published by the author. The method is based on the definition of a damage sensitive feature in terms of the accuracy of a spline function in interpolating the operational displacement shapes of the structure. In the previous works the IM was applied as a method of level 2 for damage identification that is able to detect and localize damage. In this paper an analytical relationship between the damage feature and the curvature discontinuity is proved. For two-dimensional structures, a bi-cubic spline surface is defined herein to interpolate the operational shapes. In order to account for the uncertainties related to random variations of the damage feature, an approach based on the definition of an acceptable value of the probability of false alarm was formerly proposed by the author. A simplified version of the algorithm is presented herein for the case whereby the statistical distribution of the damage feature in the original (undamaged) state is not available, and the damage diagnosis has to be carried out based on just two sets of responses recorded on the original and on the (possibly) damaged structure. The proposed two-dimensional Surface Interpolation Method (SIM) is checked herein via numerical simulations using the FE model of a plate and modeling local reductions of stiffness through a reduction of the elastic modulus of the material. Results demonstrate that the algorithm provides a reliable tool for damage identification of plate-like structures. The performance of the method can be affected by noise in recorded data, however a careful choice of the accepted probability of false alarm can reduce this drawback.

An iterated IRS technique for cross-sectional damage modelling and identification in beams using limited sensors measurement

ABSTRACTThis paper presents an effective method for cross-sectional damage localization and quantification in beams. First, a new strategy is suggested for cross-sectional damage modelling by means of Iterated Improved Reduction System (IIRS) approach. Then, a novel damage localization index is proposed employing Grey System Theory (GST) as a geometrical criterion for quantifying the amount of correlation between vectors of the calculated curvatures for the diagonal members of the flexibility matrices in the damaged and undamaged states. Since the method employs only the modal data of the translational degrees of freedom, it can be interpreted as damage identification method by utilizing incomplete modal data or installing a limited number of sensors. After detecting the damage location, to estimate the exact parameters of the cross-sectional damage, the problem is defined as a finite element model-updating problem which is solved with a new evolutionary optimization approach named Imperialist Competitive Algorithm (ICA). The applicability of the method is demonstrated by studying different damage patterns on two numerical examples of beams. In addition, its robustness is investigated in the presence of random noises and modelling errors. Obtained results emphasize the high accuracy and promising performance of the method, especially when noisy incomplete modal data are used.

A baseline-free structural damage indicator based on node displacement of structural mode shapes

Most widely studied Structural Health Monitoring methods need baseline data from the undamaged state and a high number of sensors attached to the structure, which makes these methods difficult to be applied in real structures for on-line monitoring. In order to deal with that, the NOde DISplacement (NODIS) method is proposed by considering the structural damage indicator. The idea of the present work is to develop a baseline-free damage location and quantification method based on the node displacement of structural mode shapes. The damage location procedure is developed by combining the nodes from different mode shapes and the damage quantification is achieved by the proposed Transfer-Function-based Damage Indicator (TFDI). The advantages of this method are: (1) baseline-free, in terms of the comparison with a reference signal is not needed, (2) only a relatively small number of sensors is required for real-time damage location and (3) with the proposed TFDI, the damage detection result can be quantified. In the present paper, the baseline-free damage location algorithm is proposed and validated on a steel beam with an analytical model, a numerical model and experiments. In addition, the influence of temperature, the additional weight of the sensor and the error in sensor location on the NODIS method are studied. After that, the TFDI is developed and improved for the experiment. Finally, the method is applied to a supporting structure of a sailplane under complex boundary condition and different environmental temperatures.

Fuzzy clustering of time-series model to damage identification of structures

Time-series methods have been popularly used for damage identification of civil structure because of its output-only and non-model approach. Since the existence of structural damage is usually vague and not focussed on any particular time point, the switches in damage patterns from one time state to another are necessary to be treated in a fuzzy way. This article develops a damage identification method based on the fuzzy clustering of time-series model. The changes of model coefficients of time-series model are proposed to indicate the undamaged and damaged states by the fuzzy c-means clustering algorithm. The residual errors of time-series model are used to identify the damage location and damage severity. The proposed method is applied to an experimental segment lining and a numerical study of a practical bridge. The results verify that the proposed method is accurate and efficient to detect the structural damage location and severity. Since the computational process of time-series model and fuzzy clustering require low computational cost, the proposed data-based damage identification method is applicable to the online structural health monitoring system of large-scale civil structures.

DÜŞÜK DAYANIMLI BETONARME ÖRNEK BİR YAPIDA OLUŞAN KOLON HASARI VE BU HASARIN YAPISAL DAVRANIŞA ETKİSİ

In recent years, a new urban transformation process has been started to minimize the seismic hazard risk in Turkey. The main aim of this process is to avoid uncontrolled urbanization and faulty structuring by replacing old buildings with new seismic-resistant structures. Unfortunately, it brings new risks. The most important risk is formed with the damages which may occur on the adjacent buildings during the demolition. There are several cases and lawsuits reached to local authorities and courts about this issue. The main cause of these damages is the violation of the rules in regulations and ignorance of engineering principles related to demolition applications. In this study, a low-strength building in Istanbul is investigated which has been damaged by the demolition of an adjacent building. The effects of these damages to the seismic performance level of the building are analyzed with three different numerical models. Primarily, both seismic performance levels of undamaged and damaged states are evaluated using nonlinear analysis method. Furthermore, a new structural member is added to the analysis model using the damaged state’s results to strengthen the damaged zone. The local structural behavior of the damaged zone and overall seismic performance of the building are investigated by three different cases aforementioned above to assess the results of this kind of damages. As a result of this study, the necessary strengthening approach is revealed by means of strengthening the local damaged zone or whole structure to provide necessary seismic performance level of the low-strength buildings having this type of damages.