•Single and multiple cracks identification in plate structures.•Proper Orthogonal Decomposition (POD).•Radial Basis Functions (RBF).•eXtended IsoGeometric Analysis (XIGA).
An inverse algorithm based ...on Proper Orthogonal Decomposition (POD) and Radial Basis Functions (RBF) for single and multiple cracks identification in plate structures is presented. The inverse analyses combine experimental fracture mechanics tests with numerical models based on the eXtended IsoGeometric Analysis (XIGA) method. The proposed technique identifies the location of cracks in a plate using static strains as input data. Simple and powerful algorithms, namely Jaya and Cuckoo search algorithms are coupled with the proposed XIGA-POD-RBF technique. The objective function is expressed as the difference between the strains of the actual cracks and those of the estimated ones. It is found that the proposed methodology is able to accurately estimate the cracks' locations with high accuracy and much faster than other techniques used in the literature. The stability of the identification algorithm based on Jaya is tested against measurement uncertainty by introducing a white Gaussian noise in the input data. The results show high stability for noise levels up to 4%.
Fretting wear is a material damage in contact surfaces due to micro relative displacement between two bodies. It causes some unexpected results, such as loosening of fasteners or sticking in ...components supposed to move relative to each other. Since this micro motion of fretting wear is difficult to measure in experiments, finite element method (FEM) is widely used for investigating the evolution of contact variables and wear scars during fretting wear process. In most FEM simulations of fretting wear, coefficient of friction (CoF) is assumed to be constant in order to simplify the models. As measured in experiments, however, the evolution of CoF has a relation with the wear number of cycles, especially during the running-in stage. In this research, the effects of variable CoF are considered in both gross sliding and partial slip conditions of fretting wear. The wear scar and wear volume predicted by FEM models for constant and variable CoF cases are calculated. Results indicate that, in gross sliding condition, whether or not using a variable CoF has little effect on wear volume at the end of the steady state stage of fretting wear cycles. However, when considering partial slip or running-in stage of gross sliding conditions, FE models with variable CoF achieve predictions that are closer to experimental results.
•Effect of variable CoF in gross sliding and partial slip conditions on fretting wear.•Prediction of wear scar and wear volume by FEM.•In gross sliding condition, a variable CoF has little effect in steady state stage.•Lager effect of a variable CoF in partial slip or running-in stage of gross sliding.
Recently, more attention has been paid to Artificial Neural Network (ANN) in the field of damage identification of engineering structures based on modal analysis. This paper proposes a new modified ...damage indicator, using transmissibility technique to improve Local Frequency Response Ratio (LFCR), combined with ANN. The main objective of the proposed damage indicator is to reduce the number of collected data for fast prediction and with higher accuracy instead of collecting all modal analysis data, i.e. natural frequencies, damping ratios, and mode shapes, or using inverse analysis for damage quantification. The suggested approach is tested using three layers laminated cross-ply 0°/90°/0° composite beam and plate having single and multiple damage(s). The reliability and accuracy of the proposed application are demonstrated by predicting the severity of damages in the considered composite structures after analysing four damage scenarios.
In this paper, two-stage approaches are proposed to study damage detection, localization and quantification in Functionally Graded Material (FGM) plate structures. Metal and Ceramic FGM plates are ...considered using three different composite materials: Al/Al2O3, Al/ZrO2-1, and Al/ZrO2-2. The FGM plates are modelled using IsoGeometric Analysis (IGA), which is more efficient than the classical Finite Element Method (FEM). Using a power-law distribution of the volume fractions of the plate constituents, the material properties of the plates are expected to vary continuously through their thickness. Improved damage indicator based on Frequency Response Function (FRF) is employed to predict the damaged elements in the first stage. A robust and efficient Improved Artificial Neural Network using Arithmetic Optimization Algorithm (IANN-AOA) is implemented for damage quantification problem in the second stage. The main idea is based on eliminating the healthy elements from the numerical model by the improved indicator. Next, collected data from damaged element based on damage index of an improved indicator is used as input and damage level as output. To prove the robustness of IANN-AOA, a Balancing Composite Motion Optimization (BCMO) is considered to improve ANN (IANN-BCMO) and is used for comparison. The results show that the improved indicator can predict the damaged elements with high precision. For damage quantification, IANN-AOA provides more accurate results than IANN-BCMO.
This study aims to provide an overview of numerical and experimental work, related to crack nucleation under fretting fatigue conditions. In fretting fatigue, multiaxial loads and severe stress ...gradients are present at the contact interface, which can lead to failure. The damage process, in general, is considered as a two-phase phenomenon, namely, nucleation and propagation. Various damage models and approaches are available in literature to model each phase. In the present work, different criteria, related to nucleation phase, are classified based on the approach used to define failure. These approaches include, critical plane approach, stress invariant approach, fretting specific parameters and continuum damage mechanics. Apart from theoretical background, the work related to the applications of these approaches to fretting fatigue problems is also presented. It is observed that, to analyse various aspects, intricate details near the contact interface and mechanisms involved in fretting fatigue, the strength of finite element method can be employed. In the light of numerical and experimental observations, comparison between different approaches, common sources of errors in prediction and generalized conclusions are presented.
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.
•A novel method for detecting damage in slab structures•A damage indicator based on 2D curvature mode shapes•A combination of curvature mode shape and Faster Region-based Convolutional Neural ...Networks
This paper proposes a novel method based on the two-dimensional (2D) curvature mode shape method, Convolutional Neural Networks (CNN), and Faster Region-based Convolutional Neural Networks (faster R-CNN) for detecting damage in slab structures. The 2D curvature mode shapes could be measured directly or calculated from the measured mode shapes using the central difference method. The damage indicator is defined as the absolute differences between the 2D curvature mode shapes of the damaged and intact slabs. The contour plot is chosen to convert the damage indicators into images. Four hundred damage scenarios are created using a Finite Element (FE) model of the slab. Images created from those damage scenarios are then used to train CNN and faster R-CNN. Four damage types are considered in this research, namely a single small hole, a single big hole, two small holes, and two large holes. After training, CNN can predict the damage types and faster R-CNN can predict the bounding boxes around the damaged areas. A test sample set is created to test the performance of the proposed method. The effect of noise in the mode shape data is considered. Results show that the classification accuracy for damage type is high. The overlap ratios between the predicted bounding boxes and the real damaged areas are more than 40% for 80% of tested scenarios. Furthermore, the low influence of noise on the predicted results is investigated. The proposed method is robust and has great potential for application to real structures.
•CPU Time for XIGA and XFEM based on inverse problem.•Jaya and PSO for crack idetification.•XIGA is much better than XFEM.•The objective of NURBS order for best convergence and fast simulation is ...provided.
In this paper, a creative and intelligent approach based on an inverse problem that accurately predicts crack location in plate structures is presented. The eXtended Finite Element (XFEM) and the eXtended IsoGeometric Analysis (XIGA) are combined with two optimization techniques, namely Particle Swarm Optimization (PSO) and Jaya algorithm to predict the crack location. The superiority of XIGA is demonstrated by using various NURBS orders to reduce the number of elements, provide fast simulation and achieve best convergence compared with XFEM. Four numerical-optimization techniques are considered in this paper, namely XFEM-Jaya, XIGA-Jaya, XFEM-PSO and XIGA-PSO. In the optimization techniques, the objective function minimizes the difference between the calculated and measured displacements and strains. Convergence studies for various positions of a crack and a hole in plates are performed and the results show that Jaya algorithm significantly performs more accurate and faster than PSO. In addition, theproposedtechniques are validated using experimental data and another numerical-optimization technique, i.e. XFEM coupled with Genetic Algorithm (GA), presented in literature. The comparisons show that XIGA-Jaya performs the best of all considered techniques.
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-Kármán 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.
Fretting happens when there is an oscillatory displacement between two contact parts. In gross slip regime, wear is a dominant failure mode, which has a detrimental effect on the contact parts. To ...understand the wear behaviour in the fretting process, many experiments and simulations have been done. This phenomenal analysis is time-consuming, especially when fretting wear investigation is required under certain loading cases or during certain number of cycles. Under these conditions, fast prediction tools provide an alternative for this kind of problem. In this paper, a model reduction based on Proper Orthogonal Decomposition with Radial Basis Function (POD-RBF) is used to predict the wear characteristics of specimens under different slip amplitudes and at different fretting wear cycles based on simulation results. To demonstrate the advantages and disadvantages of POD-RBF, Grey Model and Curve Fitting are used to verify POD-RBF for one-parameter prediction, while Artificial Neural Network is applied to verify POD-RBF for three-parameter prediction. The results show that the approach of POD-RBF can predict the wear characteristics under different slip amplitudes and normal loads at different cycles with high accuracy and high computational efficiency.
•Predictive model for fretting wear characteristics.•Proper Orthogonal Decomposition with Radial Basis Function (POD-RBF).•Grey Model, Curve Fitting Artificial Neural Network are used to verify the results.•POD-RBF provides high computational efficiency.
