In dry turning operation, various parameters influence the cutting force and contribute in machining precision. Generally, the numerical cutting models are adopted to establish the optimum cutting parameters and results are substantiated with the experimental findings. In this paper, the optimal turning parameters of AA2024-T351 alloy are determined through Abaqus/Explicit numerical cutting simulations by employing the Johnson-Cook thermo-viscoplastic-damage material model. Turning simulations were verified with published experimental data. Considering the constrained and nonlinear optimization problem, the artificial neural networks (ANN) were executed for training, testing, and performance evaluation of the numerical simulations data. Two feedforward backpropagation neural networks were developed with ten hidden neutrons in each hidden layer. The Log-Sigmoid transfer function and the Levenberg-Marquardt algorithm were applied in the model. The ANN models were studied with four input parameters: the cutting speed (200, 400, and 800 m/min), tool rake angle (5 • , 10 • , 14.8 • , and 17.5 •), cutting feed (0.3 and 0.4 mm), and the contact friction coefficients (0.1 and 0.15).The two target parameters include the tool-chip interface temperature and the cutting reaction force. The performance of the trained data was evaluated using root-mean-square error and correlation coefficients. The ANN predicted values were compared both with the Abaqus simulations and the published experimental findings. All of the results are found in good approximation to each other. The performance of the ANN models demonstrated the fidelity of solving and predicting the optimum process parameters.

Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.

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International audienceThis paper presents the development of a fatigue damage model able to carry out simulation of evolution of delamination in the laminated composite structures under cyclic loadings. A classical interface damage evolution law, which is commonly used to predict static debonding process, is modified further to incorporate fatigue delamination effects due to high cycle loadings. The proposed fatigue damage model is identified using fracture mechanics tests DCB, ENF and MMB. Then a non-monotonic behaviour is used to predict the fatigue damage parameters able to carry out delamination simulations for different mode-mixtures. Linear Paris plot behaviour of the above mentioned fracture mechanics tests are successfully compared with available experimental data on HTA/6376C and AS4/PEEK unidirectional materials

This article presents the development of two-dimensional and three-dimensional finite element-based turning models, for better prediction of chip morphology and machined surface topology. Capabilities of a commercial finite element code Abaqus Ò /Explicit have been exploited to perform coupled temperature-displacement simulations of an aerospace grade aluminum alloy A2024-T351 machining. The findings show that two-dimensional cutting models predict chip morphologies and machined surface textures on a plane section (with unit thickness) passing through the center of workpiece width, and not at the edges. The contribution highlights the importance of three-dimensional machining models for a close corroboration of experimental and numerical results. Three-dimensional cutting simulations show that a small percentage of material volume flows toward workpiece edges (out of plane deformation), augmenting the contact pressures at the edges of tool rake face-workpiece interface. This enhances the burr formation process. Computational results concerning chip morphologies and cutting forces were found in good correlation with experimental ones. In the final part of the article, numerical simulation results with a modified version of a particular turning tool have been discussed. It has been found that the proposed geometry of the tool is helpful in reducing burr formation as well as cutting force amplitude during initial contact of cutting tool with the workpiece material.

For qualitative prediction of chip morphology and quantitative prediction of burr size, 2D and 3D finite element (FE) based turning models have been developed in this paper. Coupled temperaturedisplacement machining simulations exploiting the capabilities of Abaqus r with a particular industrial turning insert and a newly proposed geometrical version of this insert have been performed. Limitations of 2D models in defining the chip morphologies and surface topologies have been discussed. The phenomenological findings on the Poisson burr (Side burr) formation using 3D cutting models have been highlighted. Bespoke geometry of the turning insert has been found helpful in reducing the Poisson burr formation, as it reduces the contact pressures at the edges of tool rake face-workpiece interface. Lower contact pressures serve to decrease the material flow towards workpiece edges (out of plane deformation). In contrast, higher contact pressures at tool rake face-workpiece interface lead to more material flow towards workpiece edges resulting in longer burr. Simulation results of chip morphologies and cutting forces for turning an aluminum alloy A2024-T351 have been compared with the experimental ones. Finally, it has been concluded that the newly proposed geometry of the insert not only decreases the burr but also helpful in lessening the magnitude of tool-workpiece initial impact.

The use of composite laminates is increasing in these days due to desired directional properties and low densities in comparison of metals. Delamination is a major source of failure in composite laminates where a crack like entity can initiate and propagate between different layers of composite laminates under given loading conditions. Damage mechanics based theories are employed to simulate the delamination phenomena between composite laminates. These damage models are inherently local and can cause the concentration of stresses around the crack tip. In the present study integral type non-local damage formulation is proposed to avoid the localization problem associated to damage formulation. A comprehensive study is carried out for the selection of different non-local variables. Finite element simulations based on proposed non-local damage models and classical local damage model are performed and results are compared with available experimental data for UD IMS/924 Carbon/fiber epoxy composite laminate.