مجله مهندسی ساخت و تولید ایران
سال دهم شماره 11 (بهمن 1402)

The movement of the poppet in the structure of hydraulic check valves is accompanied by vibration under the influence of oil pressure. In this article, to reduce vibration and wear in check valves, a poppet including the edge of the flow deviation is used. Therefore, to evaluate the performance of this sample check valves, the effect of oil pressure, displacement, and length of the flow deflection edge, on some dependent quantities, was investigated numerically and experimentally. Various evaluations showed that in all working conditions, the results of measurement of physical quantities have a difference of less than 5% from the results of numerical analysis. Further investigations showed that the creation of 2, 4, and 6 mm flow deflection edges in the end part of the poppet used in the internal structure of the hydraulic check valve, increases the axial force by 2.3, 18.1, and 22.9 percent, respectively. While the creation of the edge of the flow deviation poppet reduces the discharge coefficient of the valve by 1.57%. Also, creating a curve of 4 mm in the inlet port of the valve increases the axial force on the moving poppet by 14.2%. In addition, the increase in displacement of the poppet, while increasing the force on it, increased the force coefficient and the discharge coefficient of the valve. Also, in different valve displacements, the discharge coefficient of a check valve including a valve without a flow deviation edge is higher than the discharge coefficient of a valve including a valve with a flow deviation edge.

Improving the mechanical properties of the 3D printed parts by a 3D printer based on fused filament fabrication by continuous fibers (carbon, glass, and aramid) has been the focus of many researchers. Due to the nature of additive manufacturing processes that produce the parts layer by layer, in most of the research, continuous fibers are layered on a 2D surface. Robots with high degrees of freedom have been used in cases where fibers are placed on curved surfaces. In this research, a method for deposition of the continuous glass fibers on a curved surface is presented. This method is implemented on a simple and cheap 3D printer. The presented method is based on modifying the G-code, creating a rotating axis for the nozzle, and applying and using computer-aided design and manufacturing techniques. Finally, by 3D scanning of the printed sample and comparing it with the 3D model, the amount of deviation and tolerance of the surface form is determined. The obtained experimental results indicate the effectiveness of the presented method for the deposition of continuous fibers on curved surfaces. With the presented system, continuous fibers are deposited on a curved surface that consists of paths with different degrees of curvature, by simultaneous impregnation of fiber and polymer. Comparing the scanned sample with the printed sample shows that the maximum deviation is 0.1 mm. This error is acceptable due to the nature of shrinkage and distortion of thermoplastic polymer materials in forming processes according to the DIN 16901 standard.

In recent years, additive manufacturing has gained significant importance in the field of production. Most of the additive manufacturing technologies for metals involve melting and solidification processes, leading to metallurgical challenges. The friction stir additive manufacturing process is a novel solid-state method that does not face the common metallurgical challenges associated with the traditional melting methods. This process can be used for the production of aluminum-silicon carbide nanocomposites that find many applications in industries such as military, aerospace, automotive, etc. The primary objective of this research is to experimentally analyze the effect of tool rotational speed, tool traverse speed, and number of passes in friction stir additive manufacturing on the microhardness and wear amount of aluminum-silicon carbide nanocomposite manufactured by this method. To this end, the response surface method and Minitab software were used for experimental design, statistical analysis, and optimization of the parameters. Multi-objective optimization settings were selected to increase microhardness and reduce wear. The combinations of optimal values of the parameters were determined to achieve the optimization goals, and the results were validated. The optimization result with 0.87 desirability is obtained with a tool rotational speed of 1000 rpm, a tool traverse speed of 50 mm/min, and one pass. The predicted optimal responses of 104 Vickers for microhardness and 0.013 gr for wear had a small percentage of error compared to the experimental results.

In this research, fuel nozzles of GE-F9 turbine were tested, and fuel flow was measured using a Nozzle Layout device, which was designed and manufactured by Pardad Kameh Sanat Company. Then, the layout of nozzles was suggested by the special software of the device based on a specific algorithm, and it was installed on the turbine. The temperature spread was evaluated as the most important result of this research. The results show that by selecting a set of 14 out of the 30 initially provided nozzles and then using the layout recommended by the software, it is possible to reduce the gas flow difference by 2% and the temperature spread by 20 ℃. However, using two sets of nozzles out of the 30 provided can reduce the flow difference of the nozzles to 6% and 9%, respectively. In addition, with the help of the Nozzle Layout software, the temperature spread can be maintained below 28 ℃.

Considering the importance of surface roughness in machined parts, it is necessary to identify the factors that play an essential role in determining and improving surface quality. In this regard, they can be predicted and optimized by choosing suitable parameters. One of the methods used in this area is the prediction of surface roughness with traditional methods. However, limited studies were found on using meta-heuristic methods. As a result, this study proposed a model using A.I. algorithms and, more specifically, the fuzzy neural network algorithm and the combined algorithm of the fuzzy neural network. In total, 162 tests were used on three aluminum alloys 7075, 6061 and 2024, which include a variation of cutting speed, depth of cut, tool coating, feed rate, and surface roughness output. The fifth input parameter was the mechanical properties of materials, such as tensile strength, shear strength and hardness. During the modeling process, the corresponding data of two alloys were used as training data and the third as test data. The simulation performed on the data was evaluated using regression (R) and root mean square error (RMSE) criteria. The most accurate result among the two ANFIS and ANFIS-GA methods was obtained with a regression of 0.838 for the surface roughness of the test data.

In this paper, the effect of the parameters of flower pattern type (decreasing, increasing or constant), the amount of forming in each station, thickness, the number of forming stations and the type of raw material on the spring-back in the reshaping process of the square section pipe were investigated. A very effective factor in controlling product defects, including spring-back, is the design of the flower pattern. If it is not designed properly, the final product will suffer from spring-back or its separation defect. The effecting parameters on the spring-back phenomenon have been investigated and the appropriate flower pattern has been selected. Also, this flower pattern was compared with the flower patterns of Sepenta Company’s profiling line and an improvement in the amount of spring-back was observed. The results showed that the reduction forming method has a lower amount of spring-back compared to other methods. As the thickness decreases, the probability of separation defects increases, and as the thickness increases, it is necessary to allocate more shaping to the pipe in order to control the spring-back. Also, if the number of stations is reduced, which leads to over-allocation of shaping in each station, the probability of separation defects will increase. In high strength steels, increasing the number of forming stations is a suitable solution to control spring-back.