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.
This contribution presents three-dimensional turning operation simulations exploiting the capabilities of finite element (FE) based software Abaqus/Explicit. Coupled temperature-displacement simulations for orthogonal cutting on an aerospace grade aluminum alloy AA2024-T351 with the conceived numerical model have been performed. Numerically computed results of cutting forces have been substantiated with the experimental data. Research work aims to contribute in comprehension of the end-burr formation process in orthogonal cutting. Multi-physical phenomena like crack propagation, evolution of shear zones (positive and negative), pivot-point appearance, thermal softening, etc., effecting burr formation for varying cutting parameters have been highlighted. Additionally, quantitative predictions of end burr lengths with foot type chip formation on the exit edge of the machined workpiece for various cutting parameters including cutting speed, feed rate, and tool rake angles have been made. Onwards, to investigate the influence of each cutting parameter on burr lengths and to find optimum values of cutting parameters statistical analyses using Taguchi’s design of experiment (DOE) technique and response surface methodology (RSM) have been performed. Investigations show that feed has a major impact, while cutting speed has the least impact in burr formation. Furthermore, it has been found that the early appearance of the pivot-point on the exit edge of the workpiece surface results in larger end-burr lengths. Results of statistical analyses have been successfully correlated with experimental findings in published literature.
Copper/diamond (Cu/D) composites are famous in thermal management applications for their high thermal conductivity values. They, however, offer some interface related problems like high thermal boundary resistance and excessive debonding. This paper investigates interfacial debonding in Cu/D composites subjected to steady-state and transient thermal cyclic loading. A micro-scale finite element (FE) model was developed from a SEM image of the Cu/20 vol % D composite sample. Several test cases were assumed with respect to the direction of heat flow and the boundary interactions between Cu/uncoated diamonds and Cu/Cr-coated diamonds. It was observed that the debonding behavior varied as a result of the differences in the coefficients of thermal expansions (CTEs) among Cu, diamond, and Cr. Moreover, the separation of interfaces had a direct influence upon the equivalent stress state of the Cu-matrix, since diamond particles only deformed elastically. It was revealed through a fully coupled thermo-mechanical FE analysis that repeated heating and cooling cycles resulted in an extremely high stress state within the Cu-matrix along the diamond interface. Since these stresses lead to interfacial debonding, their computation through numerical means may help in determining the service life of heat sinks for a given application beforehand.
The purpose of this article is to present a simplified methodology for analysis of sandwich structures using the homogenization method. This methodology is based upon the strain energy criterion. Normally, sandwich structures are composed of hexagonal core and face sheets and a complete and complex hexagonal core is modeled for finite element (FE) structural analysis. In the present work, the hexagonal core is replaced by a simple equivalent volume for FE analysis. The properties of an equivalent volume were calculated by taking a single representative cell for the entire core structure and the analysis was performed to determine the effective elastic orthotropic modulus of the equivalent volume. Since each elemental cell of the hexagonal core repeats itself within the in-plane direction, periodic boundary conditions were applied to the single cell to obtain the more realistic values of effective modulus. A sandwich beam was then modeled using determined effective properties. 3D FE analysis of Three-and Four-Point Bend Tests (3PBT and 4PBT) for sandwich structures having an equivalent polypropylene honeycomb core and Glass Fiber Reinforced Plastic (GFRP) composite face sheets are performed in the present study. The authenticity of the proposed methodology has been verified by comparing the simulation results with the experimental bend test results on hexagonal core sandwich beams.
Summary In previous investigations, humidification‐dehumidification (HDH) solar‐assisted desalination systems were designed produce the daily fresh water during sun hours which lead to big sizes and unsteady systems. In the present study, integration of solar‐assisted HDH desalination system with heat recovery and thermal energy storage unit is developed to enhance system productivity, reduces auxiliary power consumptions and system size and assure system continuous operation. The mathematical modelling based on energy and mass conservation equations is presented and solved using iterative techniques by C++ and engineering equation solver software. Detailed parametric study of the developed system is conducted for wide ranges of operating conditions and design parameters to study the effects of integrating the HDH system with solar collectors, heat recovery and thermal energy storage units on the system performance. The results revealed that (i) this integration improves system productivity and reduces operating cost, (ii) increasing air to water mass ratio and sea water temperature and decreasing ambient humidity decrease water productivity and gained output ratio (GOR) and increase operating cost parameter (OCP) and (iii) increasing air inlet temperature and sea water flow rates increase GOR and decrease OCP. Comparison with previous systems showed that the proposed system reduces the electric heating power of the system at solar noon by 37% at MR = 0.5 and gives daily fresh water productivity (123.7 kg/h) two times more than previous systems with comparable OCP (0.099 $/kg).
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