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To overcome the inaccurate frequency band division in empirical wavelet transform (EWT) induced by high noise and modulation edge band, this study proposes an improved EWT (IEWT) and applies it to operational modal analysis (OMA) in civil structures. The IEWT segments the frequency band using spectral trend determined with removing the high-frequency components of the Fourier spectrum. The synchroextracting transform is employed to denoise the frequency components obtained from IEWT combined with the random decrement technique and Hilbert transform to identify modal parameters. The effectiveness of IEWT and the proposed modal analysis method is comprehensively verified by a full-scale cable-stayed footbridge. The results demonstrate that the proposed IEWT, random decrement technique, and Hilbert transform can accurately identify the modal parameters from multi-setup ambient vibration measurements.

In this paper, damage detection, localization and quantification are performed using modal strain energy change ratio (MSEcr) as damage indicator combined with a new optimization technique, namely slime mould algorithm (SMA) developed in 2020. The SMA algorithm is employed to assess structural damage and monitor structural health. Two structures, including a laboratory beam and a bar planar truss are considered to study the effectiveness of the proposed approach. Another recent algorithm called marine predators algorithm (MPA) is also used for comparison purposes with SMA. The MSEcr is utilized in the first stage to predict the location of the damaged elements. Single and multiple damages cases are analysed based on different number of modes to study the sensitivity of the proposed indicator to the total number of modes considered in the analysis. Next, this indicator is used as an objective function in a second stage to solve the inverse problem using SMA and MPA for damage quantification of the elements identified in the first stage. Experimental validation is conducted using a 3D frame structure with four stories that have damaged components. It is demonstrated that the proposed approach, using MSEcr and SMA, provides superior results for the considered structures. The effectiveness of this technique is tested by introducing a white Gaussian noise with different levels, namely 2% and 4%. The results show that the provided approach can predict the location and level of damage with high accuracy after introducing the noise.

The track geometry is essential for the safety, stability and comfort of passing trains. Track irregularities, which have been extensively studied with specified single irregularity type, frequently exist in complex form, leading to potential derailment accidents especially in curved lines. This study investigates the dynamic vehicle-track interaction considering a series of complex irregularities. Furthermore, the safety indices indicating the possibility of derailment, e.g., derailment coefficient, wheel unloading rate and wheelset lateral force, are obtained for both C70 freight train track and 25 tons passenger train. The results indicate that the most dangerous situation is continuous multi-wave reverse complex irregularity of cross level and alignment on the high rail at the point of curve to spiral. We also found that the most unfavorable wavelength of complex irregularity is 10 m, and derailment risk of light freight train passing is obviously greater than that of passenger trains and heavy freight trains. Certain results can give further guideline for the condition monitoring and maintenance of the rail management.

The static bending behavior of porous functionally graded (PFG) micro-plate under the geometrically nonlinear analysis is studied in this article. A small-scale nonlinear solution is established using the Von-Karman hypothesis and the modified couple stress theory (MCST). To obtain the deflection of the plate, the Reddy higher-order plate theory coupled with isogeometric analysis (IGA) is utilized. The distribution of porosities is assumed to be even and uneven across the plate’s thickness and the effective material properties of porous functionally graded micro-plate are calculated using the refined rule-of-mixture hypothesis. The influence of power index, porosity parameter and material length scale parameter on the nonlinear behaviors of static bending of porous FGM micro-plates are also investigated using several numerical examples.

Damage can be detected by vibration responses of a structure. Damage changes the modal properties such as natural frequencies, mode shapes, and damping ratios. Natural frequency is one of the most frequently used damage indicators. In this paper, the natural frequency is used to monitor damage in a free-free beam. The modal properties of the intact free-free beam are identified based on a setup of 15 accelerometers. A finite element model is used to model the free-free beam. Three models are considered: beam (1D), shell (2D), and solid (3D). The numerical models are updated based on the first five bending natural frequencies. The free-free beam is damaged by a rectangle cut. The experiment is re-setup and the model properties of the damaged beam are re-identified. The cuttings are modeled in the numerical simulations. The first five numerical bending natural frequencies of the damaged beam are compared with the experimental ones. The results showed that the 1D beam element model has the highest errors, while the 2D and 3D models have approximately the same results. Therefore, the 2D representation can be used to model the damaged beam for fast computation.

Fretting fatigue is a type of failure that may affect various mechanical components, such as bolted or dovetail joints, press-fitted shafts, couplings, and ropes. Due to its importance, many researchers have carried out experimental tests and analytical and numerical modelling, so that the phenomena that govern the failure process can be understood or appropriately modelled. Consequently, the performance of systems subjected to fretting fatigue can be predicted and improved. This paper discusses different aspects related to the finite element modelling of fretting fatigue. It presents common experimental configurations and the analytical solutions for cylindrical contact. Then, it discusses aspects of fretting fatigue crack initiation, such as crack location, orientation, and length, as well as stress averaging approaches. Then, it deals with the propagation stage; crack face interaction, orientation criteria, and crack growth rate are discussed. Lastly, additional aspects of recent research on fretting fatigue are reviewed: out-of-phase loading, cohesive zone modelling, wear effects, heterogeneity, and crystal orientation. Fretting fatigue is a phenomenon not well understood, and much more research is needed so that its understanding is increased and proper criteria and laws may be available for different cases.

This paper deals with modeling of the phenomenon of fretting fatigue in heterogeneous materials using the multi-scale computational homogenization technique and finite element analysis (FEA). The heterogeneous material for the specimens consists of a single hole model (25% void/cell, 16% void/cell and 10% void/cell) and a four-hole model (25% void/cell). Using a representative volume element (RVE), we try to produce the equivalent homogenized properties and work on a homogeneous specimen for the study of fretting fatigue. Next, the fretting fatigue contact problem is performed for 3 new cases of models that consist of a homogeneous and a heterogeneous part (single hole cell) in the contact area. The aim is to analyze the normal and shear stresses of these models and compare them with the results of the corresponding heterogeneous models based on the Direct Numerical Simulation (DNS) method. Finally, by comparing the computational time and % deviations, we draw conclusions about the reliability and effectiveness of the proposed method.

In this paper, a new method has been proposed to optimize the hyper parameters in Deep neural network (DNN). For this purpose, a new version of Grey Wolf Optimizer named New Balance Grey Wolf Optimizer (NB-GWO) is successfully developed for the first time. NB-GWO introduces an equation to control the movement strategies at each iteration. Based on this equation, the exploitation ability will be prioritized during the first few iterations to improve the convergence rate and gain quick access to potential search spaces. Meanwhile, during the last few iterations, the exploration ability will be biased toward exploitation to increase the opportunities of escaping the local optima's problem or exploring new spaces with the hope of finding better solutions. Because of the diversity of movement strategies, the NB-GWO has established a better balance between the ability of exploitation and exploration than that of in the original GWO. To demonstrate the effectiveness of NB-GWO, 23 classical benchmark functions combined with eight well-known optimization algorithms are used to evaluate the performance of NB-GWO as the first example. Then, NB-GWO will be used to optimize the hyper parameters in deep neural networks (DNN) for damage detection in 2D concrete frame. The results show that NB-GWO is a grown-up version of GWO, the results obtained in this work have proved the effectiveness and reliability of NB-GWO in solving optimization problems, especially, for optimizing the hyper parameters in DNN.

Both wear and fatigue occur in fretting condition, and they interact with one another during the whole process. Fretting fatigue is commonly analysed without considering the effect of wear in partial slip regime, although wear affects the lifetime of crack initiation. This paper investigates, for the first time, the effect of wear debris on fretting fatigue crack initiation. To investigate the effect of debris, first fretting wear characteristics in partial slip regime are analysed for loading conditions. Then, the effect of wear on fretting fatigue crack initiation is investigated using Ruiz parameters and critical plane methods without considering the debris effect. Through the results, we can see that loading conditions affect the wear profiles in different ways. Moreover, wear has a significant effect on the fatigue in partial slip regime without considering debris especially on the crack initiation location. Finally, considering wear debris in the analysis, its effect on critical plane parameters is investigated. It is found that by considering the wear debris effect, the fretting fatigue crack initiation location is shifted towards the trailing edge. The predictions of both crack initiation location and lifetime show a good agreement with the experimental data.

In this paper, we propose a systematic and time-efficient approach to calibrate 2D VARANS-VOF models for simulation of wave interaction with porous plate in numerical wave tank. To reach this goal, we develop a data-driven approach in combination with numerical and experimental data to figure out the optimal empirical coefficient associated with linear and non-linear drag force coefficients (a, beta). Advanced gradient boosting decision trees algorithms (GBDT) are adopted to capture the accuracy of the prediction model. Although only limited samples, for instance 72 samples are generated and chosen to train and test the prediction model, the GBDT model is able to identify the trend in non-linear influence of model parameters. The advantage of GBDT algorithm can obviously be seen through the regression analysis with very high regression coefficient (R-2 > 0.99). The developed model is subsequently employed for a large range of considered parameters as input features of the models to predict the possible hydrodynamics characteristics. The smallest mean squared error between predicted and experimental results, which is 0.00204, is found and used to determine the best performing combination of these model parameters. The numerical model together with selected values of empirical coefficients is then validated using available experimental data in literature. The free surface elevations in front of and behind the structure from the numerical model are nearly identical with the experimental data.

Local stress concentration occurs when faults are present in pipelines under pressure. An example of such defects is the problem of corrosion caused by the environment in the field of pipeline installation. In the first part of this paper, we attempt to model the corrosion in the hemi-ellipsoidal form in order to study the locations of stress concentration in the specimens by several experimental cases and their influence on the stress resistance. The Gurson-Tvergaard-Needleman (GTN) mesoscopic damage model is used to simulate the specimens with good accuracy. In the second part, the investigation is extended to a pipe under static pressure with and without the presence of a glass fibre reinforced polymer (GFRP) composite patch. The maximum stress and percent stress reduction in a defected pipe with a hemi-ellipsoidal defect are determined using a 3D finite element model. This part examines the impact of the geometry of the composite patches on the percentage reduction of the maximum stresses in a section of pipeline subjected to static pressure. In the third part, the stresses and the percentage reduction in the maximum stresses are predicted using an artificial neural network (ANN). An inverse problem using ANN and Jaya algorithm is proposed to predict the group level of different sizes of defects under composite patches based on the maximum stress and percentage reduction of stress that the pipe withstands. The new method relates directly to real-world pipeline construction and repair applications. It could be also used for structural safety monitoring.

In this paper, a new hybrid YUKI-ANN is implemented for Structural Health Monitoring (SHM) of laminated composite plates. A finite element model is constructed and used to identify damage at five randomly selected elements in a laminated composite plate. The process of damage identification is divided into two main steps, namely damage localization and quantification. During the localization step, damaged elements are identified using a damage indicator based on Modal Strain Energy change ratio (MSEcr). After excluding the healthy el-ements, the level of damage is predicted using ANN modified with four optimization algorithms: Arithmetic Optimizing Algorithm (AOA), Balancing Composite Motion Optimization (BCMO), Particle Swarm Optimization (PSO), and YUKI algorithm. The performance of these optimization algorithms is evaluated, and it is found that the YUKI algorithm (YA) outperforms AOA, BCMO, and PSO algorithms without exception. YA gives better predictions with lower errors when compared to PSO and BCMO algorithms with equivalent computational time. In some cases, AOA provides slightly better predictions than YA, but the computational time for these predictions is eight times more that of YA. If both performance and efficiency are considered, YA seems to be the best choice. Find the MATLAB code for YUKI-ANN at https://github.com/Brahim-Benaissa/YUKI_ANN.

Artificial neural network (ANN) is the study of computer algorithms that can learn from experience to improve performance. ANN employs backpropagation (BP) algorithms using gradient descent (GD)-based learning methods to reduce the discrepancies between predicted and real targets. Even though these differences are considerably decreased after each iteration, the network may still face major risks of being entrapped in local minima if complex error surfaces contain too numerous the best local solutions. To overcome those drawbacks of ANN, numerous researchers have come up with solutions to local minimum prevention by choosing a beneficial starting position that relies on the global search capability of other algorithms. This strategy possibly assists the network in avoiding the first local minima. However, a network often has many local bests widely distributed. Hence, the solution of choosing good starting points may no further be beneficial because the particles are probably entrapped in other local optimal solutions throughout the process of looking for the global best. Therefore, in this work, a novel ANN working parallel with the stochastic search capacity of evolutionary algorithms, is proposed. Additionally, to increase the efficiency of the global search capacity, a hybrid of particle swarm optimization and genetic algorithm (PSOGA) is applied during the process of seeking the best solution, which effectively guarantees to assist the network of ANN in escaping from local minima. This strategy gains both benefits of GD techniques as well as the global search capacity of PSOGA that possibly solves the local minima issues thoroughly. The effectiveness of ANNPSOGA is assessed using both numerical models consisting of various damage cases (single and multiple damages) and a free-free steel beam with different damage levels calibrated in the laboratory. The results demonstrate that ANNPSOGA provides higher accuracy than traditional ANN, PSO, and other hybrid ANNs (even a higher level of noise is employed) and also considerably decreases calculational cost compared with PSO.

A method combining crystal plasticity (CP), the eXtended Finite Element Method (XFEM), and cohesive zone model (CZM) with traction separation law is developed for an Al-Cu-Mg alloy to predict the effect of grain orientation on fatigue crack propagation (FCP) during stage Iota Iota within a single crystal. The simu-lation results show that of all the orientations, Goss grain possesses the largest fatigue crack deflection, then followed by Cube orientation. Comparatively, Brass, Copper, S and Random grains have relatively small crack deflection angles. Besides, it is found that Goss grain with the largest fatigue crack deflection possesses the lowest FCP rate as compared with other orientations. The results of simulations are consis-tent with previous experimental observations. This indicates that this coupled CP XFEM CZM simulation method is capable of well predicting the effect of grain orientation on FCP during fatigue stage Iota Iota of Al-Cu -Mg single crystal. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Identifying cracks in the incipient state is essential to prevent the failure of engineering structures. Detection methods relying on the analysis of the changes in modal parameters are widely used because of the advantages they present. In our previous research, we have found that eigenfrequencies were capable of indicating the position and depth of damage when sufficient vibration modes were considered. The damage indicator we developed was based on the relative frequency shifts (RFS). To calculate the RFSs for various positions and depths of a crack, we established a mathematical relation that involved the squared modal curvatures in the healthy state and the deflection of the healthy and damaged beam under dead mass, respectively. In this study, we propose to calculate the RFS for beams with several cracks by applying the superposition principle. We demonstrate that this is possible if the cracks are far enough from each other. In fact, if the cracks are close to each other, the superposition method does not work and we distinguish two cases: (i) when the cracks affect the same beam face, the frequency drop is less than the sum of the individual frequency drops, and (ii) on the contrary, cracks on opposite sides cause a decrease in frequency, which is greater than the sum of the frequency drop due to individual damage. When the RFS curves are known, crack assessment becomes an optimization problem, the cost function being the distance between the measured RFSs and all possible RFSs for several vibration modes. Thus, the RFS constitutes a benchmark that characterizes damage using only the eigenfrequencies. We can accurately locate multiple cracks and estimate their severity trough experiments and thus prove the reliability of the proposed method.

The effects of vibration on the emergency braking tribological behaviors of the brake shoe of a deep coal mine hoist were investigated in this study. The thermal, frictional and mechanical parameters of the brake shoe were obtained. The vibration characteristics of the brake shoe during emergency braking were investigated, employing multibody dynamics analysis. The effect of vibration on the emergency braking tribological behaviors (temperature and stress distributions) of brake interfaces was explored using the finite element method. The self-made tribo-brake test rig of a brake shoe was employed to reveal the friction deterioration behaviors of the brake shoe during emergency braking. The results show obvious vibrations of all brake shoes along the direction of positive braking pressure during emergency braking. The vibration causes increases in the equivalent Von Mises stress and temperature at the contact interfaces between the brake disc and the brake shoe as compared to the case of ignoring the vibration. Along the rotation direction of the brake disc, the equivalent stress and temperature of the brake disc surface present three overall rapid increases, as well as two slight decreases during emergency braking. As compared to cyclic emergency braking, continuous emergency braking exhibits more obvious tribological degradation of the brake shoe, attributed to enhanced vibration. The wear loss of the brake shoe increases with increasing emergency braking cycles and continuous emergency braking time.

We present numerical computation of stresses under fretting fatigue conditions derived from closed form expressions. The Navier-Cauchy equations, that govern the problem, are solved with strong and weak form meshless numerical methods. The results are compared to the solution obtained from well-established commercial package ABAQUS, which is based on finite element method (FEM). The results show that the weak form meshless solution exhibits similar behavior as the FEM solution, while, in this particular case, strong form meshless solution performs better in capturing the peak in the surface stress. This is of particular interest in fretting fatigue, since it directly influences crack initiation. The results are presented in terms of von Mises stress contour plots, surface stress profiles, and the convergence plots for all three methods involved in the study.

In this paper, a new experimental study of the bending static and fatigue behaviors of a composite material reinforced with 40% by mass of short glass fibers (type E) and polypropylene matrix is presented. The composite material is obtained in the form of plates by an injection process, which inevitably affects the distribution of the fibers and therefore the behavior of the material studied. To do this, several techniques are implemented on specimens by cutting them in transverse and longitudinal directions. The effect of aging in distilled water at 40℃ on the mechanical characteristics is studied under static and fatigue loading conditions. The static tests, three-point flexure up to failure, allow us to choose the levels of stress for the fatigue tests. The endurance curves as a function of the number of cycles are plotted by adapting the end-of-test criteria N5, N10, and N20, which represent a rigidity drop of 5%, 10%, and 20%, respectively. An interpretation of the Wöhler curve equations defined for the end-of-test criteria allows defining the kinetics of material damage. The results highlighted the influence of distilled water on the mechanical behavior and the lifetime of the material. We also perform macroscopic observations of fracture and microscopic facies in order to identify the damage mechanisms of the composite material.

In this study, we exploit the flexibility and advantages of polyhedral finite elements in modeling 3D hollow concrete block revetments. In the present method, a new concept is proposed, in which the polyhedral elements are subdivided into sub-tetrahedrons through virtual nodes located at the centroids of the faces and element. Piecewise linear shape functions of polyhedral elements are constructed for the sub-tetrahedrons. Then, the shape functions are used to formulate the stiffness and mass matrices. By this way, the present approach yields lower computational cost than that of the standard polyhedral finite element method based on rational basis functions. The presented method suits well general polyhedral meshes including concave elements, which are used to model 3D complicated structures in design of coastal defenses system protection such as interlocking revetments. Reliability and effectiveness of the present approach are validated by the well-known commercial ANSYS software through static and dynamic analysis.

This paper proposes a two-stage approach for damage assessment in beam-like structures using two-dimensional Isogeometric Analysis (IGA) and Finite Element Method (FEM) combined with optimization techniques. In the first stage, the Local Frequencies Change Ratio (LFCR) indicator and a newly developed damage indicator based on normalized Modal Strain Energy Indicator (nMSEDI) are introduced to locate effectively the potential damaged elements. In order to verify nMSEDI, different scenarios based on single and multiple damages are studied using numerical experiments. In the second stage, the Teaching-Learning-Based Optimization Algorithm (TLBO) is utilized and its performance is compared with that of Particle Swarm Optimization (PSO) and Bat Algorithm (BA). The three optimizations techniques are combined with IGA using nMSEDI as objective function. In addition, experimental vibration tests using laboratory steel been are conducted to validate the proposed technique. The obtained results clearly indicate that the proposed approach can be used to determine accurately and efficiently both damage location and severity in beam-like structures.

Fretting fatigue involves multiaxial stress field due to presence of contact between two bodies. Near the contact edge, high stress gradient may be present depending on load and geometrical conditions. To account for high stress gradient or singular results, a regularization method may be required for better prediction of crack initiation angle and life. In the present work, conventional point and volume averaging methods are compared with a proposed quadrant averaging method to predict crack initiation angle and life. It is found that quadrant method produce more realistic results for initial crack orientation than other methods. Two multiaxial critical plane damage parameters, McDiarmid (MD) and Fatemi Socie (FS) are employed for this purpose. In addition, the influence of stress averaging on crack initiation life is analysed for two different geometries. It is observed that critical radius for stress averaging depends on stress gradient or rate of decay of damage parameter under the surface of the contact.

The aim of this study is to determine the effect of cataphoretic and powder coatings and also the method of application the primer on the adherends surface on the strength and failure modes of EN AW-5754 aluminium alloy adhesive joints. The study is performed on lap joints made of EN AW-5754 aluminium alloy, subjected to three different types of surface treatment; namely a) polyurethane cataphoretic coating, b) powder coating based on black mat RAL 9005 UL polyester resin and c) no coating. The tested adhesive joints were made using a one-component polyurethane adhesive Terostat 8596, which was dedicated for automotive and cured under a constant load of 0.018 MPa at 20 ± 2 °C. In addition, this study investigates the effect of the application of Terostat 8519P adhesion promoter which is a liquid polyurethane-based primer containing solvents and which is corresponding to Terostat 8596 polyurethane adhesive. Terostat 8519P adhesion promoter was applied in two different ways: a) to one substrate and b) to both substrates. The produced adhesive joints were subjected to strength tests using the Zwick/Roell Z150 testing machine. The examination of fracture in the tested adhesive joints was performed in accordance with the EN ISO 10365 standard. The shear strength results have demonstrated that both the method of application of the adhesion promoter (Terostat 8519 P) and the presence of cataphoretic coating had an influence on adhesive joints strength. The use of the adhesion promoter significantly affects the strength of both uncoated EN AW-5754 aluminium alloy adhesive joints and the adhesive joints subjected to powder coating. The use of the adhesion promoter has a less significant effect on the cataphoretic-coated samples.