مجله مهندسی مکانیک
پیاپی 150 (امرداد و شهریور 1402)

The most important goal of the craftsmen is to maximize the material removal rate while controlling the surface quality. In this article, according to the regression equation obtained from the design of the experiment using the response surface method, to investigate the extent and manner of influence of seven process parameters including, pulse on time, pulse off time, arc off time, gap voltage, wire feeding rate, wire tension and water pressure has been studied on two characteristics of material removal rate and surface roughness using Sobol sensitivity analysis method. The purpose of this research is to select the most optimal parameter in the machining process in order to increase the material removal rate and reduce the surface roughness. According to the results obtained from the sensitivity analysis, it can be seen that the factor of pulse on time and pulse off time each have an effect of 59% and 28%, respectively, the most effective parameters on the material removal rate, and the parameters of pulse on time and water pressure, respectively, with 81% and 18% influence are the most effective parameters on surface roughness.

This paper presents the initial structural analysis and geometric optimization of a rotating disk used in an aircraft turbine engine. The disk is homogeneous and subject to mechanical and thermal loads. The governing equations for the thermoelastic analysis of the assumed disk were derived under the assumption of plane stress conditions and subsequently analyzed using the MATLAB computational software. Three different optimization methods were implemented for the geometric optimization of the rotating disk: The Counting Sort Algorithm (CSA), the non-gradient Genetic Algorithm (GA), and the Artificial Bee Colony algorithm (ABC). The optimization methods resulted in a reduction of the disk mass by 36.49%, 39.51%, and 36.43%, respectively. Also, the approximate time required to reach the optimization results was 3,500, 120, and 100 minutes, respectively. The results show that the non-gradient genetic algorithm (GA) method has the greatest improvement in results. The convergence speed of the non-gradient GA and ABC methods is also about 30 to 35 times faster than the CSA method. As a result, the importance of non-gradient methods in saving time and computational costs has become more evident, due to the time-consuming nature of gradientbased analyses. Based on the results, the use of the GA method has been proposed as an accurate and efficient method for the optimization of rotating problems under thermoelastic loading.

Due to the complexity of turbulent flows, it is not possible to solve the governing equations in full detail. Therefore, different numerical approaches have been proposed to solve the governing equations and analyze the flow characteristics. The most important methods include Direct Numerical Simulation (DNS), Large Eddy Simulation (LES) and Reynolds Averaged Navier-Stokes Equations (RANS). In terms of accuracy and computational cost, large eddy simulation is in between two other methods. In this method, large and small scales are separated by applying a low-pass filter. Large scales are solved and small scales are modeled. So far, various models have been presented for small or subgrid scales. Eddy viscosity models are the most common models used for this purpose. The first and simplest eddy viscosity model is the standard Smagorinsky model. The accuracy of this model is low, especially for complex geometries. Therefore, various studies have been conducted to increase the accuracy of this model. The dynamic Smagorinsky model, dynamic localization model, and scale-dependent dynamic model are among the most widely used models. In this paper, the progress of eddy viscosity models used in large eddy simulation is presented.

Grinding, as one of the machining processes, is considered as one of the most important final production processes. During this process, very high heat is generated, which is a problem in the machining process, and efforts are made to remove it. Recently, efforts have been made to use this problem as an opportunity. By controlling the amount of heat transferred to the workpiece, its surface can be heat treated. Therefore, grind hardening is a new and non-traditional machining process that can be used for surface hardening and grinding of metal parts. Grind hardening process has the potential to replace the traditional methods of surface heat treatment by integrating this process in the grinding phase. The key advantage of this method is the elimination of workpiece movement during production, reduce cost, increase efficiency, and the reduction of redundant setups. In this research, the functional principles of the process, the latest developments of this method and a comparison between this process and alternative methods of surface heat treatment have been discussed. Its challenges have been discussed and examined, and the opportunities and situations of using grind hardening by have been stated.

Additive manufacturing is a set of modern manufacturing technologies with a novel revolutionary point of view that addresses most of limitations that were around due to using conventional manufacturing methods. Due to the lack of references for additive friction stir manufacturing, in the present paper the new developments in friction stir additive manufacturing of metals, alloys, and metal matrix composites are presented and summarized. Friction stir additive manufacturing is a solid-state process that yields a dense and homogeneous structure with a significant microstructural refinement with no fusion defects such as shrinkage cavities, porosity, and cracks. The rest of the paper was arranged as follows: friction stir welding is discussed as the base technology. Then, the two additive manufacturing methods that are based on friction stir welding, i.e. additive friction stir manufacturing and additive friction stir deposition are presented.

The investigation of the properties of two hybrid nano-lubricants MWCNT (30%)/ZnO(70%)-SAE40 and MWCNT(50%)/ZnO(50%)-SAE40 in different conditions by experimental and modeling methods and introducing a better nano-lubricant are done in this study. Experiments are performed in the temperature range of 25-50°C, volume fraction of 0.0625-1% and shear rate of 666.5-9331s-1 and the viscometer of Brookfield CAP 2000+ is used the results showed that both nano-lubricants have non-Newtonian and pseudo-plastic behavior. The highest increase of viscosity is occurred for nano lubricant of MWCNT-ZnO (50%-50%)/SAE40 by 28%, and the highest drop is occurred for nanolubricant MWCNT-ZnO (30%-70%)/SAE40 by 3% and therefore MWCNTZnO (30%-70%)/SAE40 nanolubricant has better performance. The results of the correlation provided by rsm method are in good agreement with the experimental data and R2 = 0. 9998 is obtained. The value of -0.95% <MOD < 1.10% is obtained and indicates a low modeling error. The sensitivity of nano-oil also increased with increasing the volume fraction.