Volume 66, Issue 4

For the design of thick-walled cast iron components used for wind energy turbines, large machines, presses, and engine parts made of nodular cast iron, the assessment of fatigue life of critical component areas is a crucial point to consider. Importance increases with the demand to safe resources by applying a lightweight design in combination with a certain resistance against extreme loads and misuse situations. Moreover, this gets more important when notches or deviations in the local microstructure are present. Nevertheless, due to accessibility, a lack in the description of the local strain-based material behavior still exists. Especially new cast iron grades such as ADI are not well investigated but offer an often-discussed potential for a lightweight design of the structure or to increase the highest admissible load on the structure. To determine the cyclic material behavior of nodular cast iron, different grades EN-GJS-400-18LT, EN-GJS-450-18, EN-GJS-500-14, EN-GJS-600-3, EN-GJS-700-2, and ADI in different wall thicknesses were investigated concerning their elastic–plastic material behavior under strain control. Moreover, new possibilities for the trilinear description of the strain-life and the stress–strain curve and the statistical and technological size effect are discussed in the following based on cyclic stress–strain and strain-life curves.

Bearing fault detection is an important part of mechanical equipment and rotating machinery. Bearing failure should be detected early because it can lead to property and safety losses. This study proposes convolutional neural network (CNN) based models for bearing fault detection. Since the main advantages of the proposed methods apply to different types of warehouse data, failure can be detected in a short time and applied directly to raw data. These new models achieve comparable or better performance compared to the existing models in the literature. Although the structure of the proposed models is simpler and the number of parameters used is smaller, these new models achieve successful empirical results. Data sets from CWRU and IMS were used to test the models. This study compares the proposed models with the existing models in the literature. It also compares the new models with the machine learning algorithms and obtains better empirical results.

In this study, Ce inoculated GX40CrNi25-20 material was produced by casting. The materials were subjected to heat treatment by being exposed to two different temperatures (1100, 1150 °C) and two different cooling intensities. The effects of heat treatment on primary and secondary carbide concentration, distribution, and type were investigated by using optical microscope, scanning electron microscope, energy dispersive spectrometry, X-ray diffraction, and microhardness tests. The adhesive wear behavior of the materials was determined. After the homogenization heat treatment, the increased cooling intensity application decreased the hardness of the samples. After the homogenization heat treatment, the size of the primary carbides decreased and their distribution became homogeneous. Secondary carbides were dispersed into smaller and equiaxed formin the matrix. EGR inoculating reduced the precipitation of carbides and changed the shape of the precipitate to granule.

(CoFeNiMn) 100−x Cr x (x = 5, 20, 35 at.%) HEAs were produced using vacuum arc melting followed by suction casting using industrial-grade raw materials and subsequent annealing at 1150 °C for 24 h. The increasing Cr content triggered the formation of the Cr 7 C 3 in the FCC matrix due to the presence of C impurity in the raw materials. The increasing Cr content from 5 to 35 at.% raised the hardness from 206 (±7) to 383 (±4) HV and yield strength from 210 to 350 MPa due to the embedded Cr 7 C 3 phases in the matrix. The HEA consists of 20 at.% Cr was found to be the most promising alloy due to the strength-ductility trade-off with the values of 350 MPa compressive yield strength and 10.7 % strain. The enhanced mechanical properties of the HEAs by using industrial-grade low-cost raw materials could make them more attractive materials for industrial applications.

The aluminum AA7050 alloy has high toughness and high strength. Despite the high machinability of the AA7050 alloy, hole quality can vary according to tool geometry and drilling parameters. This study investigated the effects of different cutting parameters and three different drill point angles on thrust force and torque. Numerical analyses for thrust force and torque were performed using the finite element method. The lowest thrust force and the highest torque were obtained with the drill at 130° drill point angle, while the highest cutting force and lowest torque were obtained with the drill at 118° drill point angle. There is an average difference of 5.37 and 6.9 % between the experimental and analysis values for thrust forces and torque, respectively, and the applicability of the finite element model has been proven. In the last part of the study, thrust force and torque are modeled with artificial neural networks. The statistical accuracy ( R 2 ) values for the learning and testing values in the thrust force of the equation are 0.997797 and 0.995739, respectively. Torque’s learning and testing accuracy values are 0.987247 and 0.937909, respectively. The obtained equations have a high accuracy rate.

Amidinothiourea crosslinked graphene oxide membrane was prepared by a multilayer self-assembly method along with (3-aminopropyl) triethoxysilane modification, while different thicknesses of the membrane layer were obtained by regulating the volume of graphene oxide dispersion. The removal rate of the membrane layer with different thicknesses of heavy metal ions was explored and its removal mechanism was explained. The results show that the membrane can maintain high stability after 90 days of immersion in water. When the volume of graphene oxide dispersant increases from 9 ml to 15 ml, the thickness of the membrane layer enhances from about 120 nm to about 200 nm. After filtration of 140 ml of different nitrate solutions, the water fluxes of different membranes are about 22.6 l m −2  h −1 ·bar −1 , 6.1 l m −2  h −1 ·bar −1 , and 1.4 l m −2  h −1 ·bar −1 , respectively. The removal rates of the preferred membrane for Pb 2+ , Cd 2+ , and Cu 2+ are 43.3 %, 41.2 %, and 39.7 %, respectively. The ion removal mechanism is mainly due to the Dornan effect.

AZ31B Mg alloy were welded to AISI 304 stainless steel (which is a very challenging task because of their huge different chemical and physical features) by friction stir spot welding (FSSW) at different tool rotation speeds (700, 1000, and 1300 rpm) while keeping other conditions the same. Welds were evaluated and compared by examining their cross-sectional geometry, XRD pattern, tensile shear strength, fracture way and area. From cross-sections of welds, it was obtained that joining area expanded when speed was enhanced and the weld made through 1300 rpm had the largest one. Therefore, weld fabricated with the highest speed of 1300 rpm displayed the biggest tensile shear load of 3741 N while that manufactured with the lowest speed of 700 rpm possessed the lowest of 2430 N. All welds showed tensile shear type fracture and fracture occurred from the hooking regions where joining took place. From the fracture joint region, the weld of 700 rpm had the smallest joined area, whereas that of 1300 rpm showed the biggest. Higher speed produced a stronger joint, which agreed with a bigger bonding area and broken joint region. Also, joint became more ductile with increasing speed. Some phases were detected in joints.

Nature-inspired metaheuristic optimization algorithms have many applications and are more often studied than conventional optimization techniques. This article uses the mountain gazelle optimizer, a recently created algorithm, and artificial neural network to optimize mechanical components in relation to vehicle component optimization. The family formation, territory-building, and food-finding strategies of mountain gazelles serve as the major inspirations for the algorithm. In order to optimize various engineering challenges, the base algorithm (MGO) is hybridized with the Nelder–Mead algorithm (HMGO-NM) in the current work. This considered algorithm was applied to solve four different categories, namely automobile, manufacturing, construction, and mechanical engineering optimization tasks. Moreover, the obtained results are compared in terms of statistics with well-known algorithms. The results and findings show the dominance of the studied algorithm over the rest of the optimizers. This being said the HMGO algorithm can be applied to a common range of applications in various industrial and real-world problems.

In this study, DIN AlZnMgCu1.5 alloy surface (Al + SiC) was coated with metal matrix composite (MMC) by using hot press sintering method (HPSM). Al was used as matrix material and SiC powders were used as reinforcing material in the coating process on DIN AlZnMgCu1.5 alloy surface. Al/SiC MMC coating was produced at 600 °C under 120 MPa pressure and with varying SiC content (5, 10 and 15 vol.%). Optical microscopy (OM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) were used to examine the microstructure, elemental analysis and phase structure of both the coating zone and the transition zone between the substrate and the coating. The hardness was measured and a dry sliding linear reciprocating wear test was run to determine the mechanical properties of the coating layer. Consequently, the coefficient of friction (COF) and wear volume were determined. OM and SEM images showed a homogeneous distribution of SiC particles and a less porous structure. The hardness of the MMC coating increased with increasing SiC content. Also, the numerical analysis of the wear test simulation was done based on Archard’s law. The results of both wear tests showed that the volume loss values were consistent with each other and the amount of wear significantly reduced by increasing the rate of SiC reinforcement.

Deep cryogenic treatment (DCT), a technique of deep subzero processing, is utilized after quenching and well preceding tempering. In DCT, the materials are subjected to a soaking period of typically 24 h at a temperature of −196 °C. The optimal soaking period varies depending on the material to be cryotreated. The microstructural characteristics and mechanical properties of ferrous and nonferrous materials are significantly enhanced using DCT resulting in improved durability and functional performance of the mechanical components. The DCT is generally performed on tool steel, stainless steel, aluminum alloys, and magnesium alloys to improve its mechanical properties. The complete transition of residual austenite to martensite and finer secondary carbide precipitation correlates with an increase in the mechanical properties of tool steel. The nonferrous materials such as aluminum and magnesium alloys showed improved mechanical properties owing to the precipitation of finer second phases in the matrix. The main objective of this review paper is to provide an overview on the history and theories of DCT, important processing parameters, and the effect of DCT on microstructure and mechanical properties of tool steel, aluminum alloys, and magnesium alloys.

In this study, reinforced composite panels with hat-shaped profile were produced from woven carbon fiber fabrics by vacuum infusion method. Holes were drilled on the crown surface of these panels and repaired with composite patches. The mechanical behavior was examined by performing a three-point bending test on the obtained patched and unpatched specimens. The contribution of the repair to the failure load of the damaged specimens under bending load has been clearly determined. In the numerical part, Hashin damage criterion was used for the beginning of damage. For damage progression, both Continuum Damage Mechanics and Material Property Degradation methods were preferred and compared. In the analysis carried out using the finite element package program Workbench, the cohesive zone model (CZM) was added to the model and its effect on the damage behavior and load of the composite structure was determined. As a result of the experiments and analyses, it was seen that the maximum contact force of the specimens under the bending load decreased by 29.8 % by increasing the number of holes on the specimen surface from 1 to 3. The maximum contact force was determined to increase by 18.52 % due to repairing the three-hole specimens with a patch.

7075-T651 Al alloy sheets were welded by friction stir spot welding (FSSW) method without and with tap water. Conducting FSSW with water reduced the weld microstructure grain size and the hook defect formation at the weld, resulting in an increase in the hardness and tensile strength of the weld. The joint made with water showed an average tensile load of 4237 N, whereas the joint made without water exhibited 3690 N. Using water enhanced the strength of the joint, but slightly decreased its ductility. The hardness of the joint made with water presented slightly higher, probably due to the formation of smaller grains in its microstructure as a result of the water leading to a decrease in the welding process temperature. In both joints, the highest hardness measurements in the stir zones (SZs) and the lowest ones in the heat-affected zone (HAZ) and thermo-mechanically affected zone (TMAZ) were found as the SZs had a finer-grained microstructure. Furthermore, the application of water noticeably, though not completely, inhibited the occurrence of the hook defect in the joint and also reduced the sizes of HAZ and TMAZ. According to the weld fracture surface analysis, both joints failed in a ductile manner.

Powder metallurgy and selective laser melting (SLM) methods are widely used in producing metal parts. Adding reinforcements can improve the mechanical and physical properties of the parts. This study uses the powder metallurgy method before SLM to investigate the effect of copper reinforcement (0, 0.5, 1, 2, and 5 wt.%) on 316L and MS1 (maraging steel) material. The study started by thermochemical investigating the effects of copper addition on the phases during cooling. According to the thermochemical analysis, experimental sintering processes were carried out with the addition of copper in suitable mixing ratios. The findings show that 316L material is more convenient to the sinter than MS1 due to alloy ratios and powder sizes. Adding up to 2 wt.% copper to 316L results in a 36 wt.% reduction in linear shrinkage and improved mechanical and physical stability. The most satisfactory results were obtained by sintering the samples at 1200 °C for 1 h. This study shows that future research should focus on producing copper-reinforced 316L metal powders using SLM methods and parameter optimization and developing hybrid manufacturing methods that combine SLM with powder metallurgy.

The present study aimed to develop a recyclable composite material based on a natural product, namely banana fiber, instead of synthetic reinforcement elements such as glass fiber or carbon fiber in thermoplastic matrix composites employed in many aspects of daily life. Polyoxymethylene (POM) thermoplastic was used as the matrix material. 3 %, 6 %, and 9 % by weight short natural banana fiber was used as reinforcement. Furthermore, the study improved the mechanical and thermal properties of the composite material with chemical improvements based on alkali treatment of banana fiber. Banana fiber and POM was initially mixed mechanically and then extruded at temperatures between 170 and 190 °C to obtain a homogeneous mixture. The mixture obtained by extrusion was initially cooled in the cooling pool and then passed through the crusher to obtain granules. These granules were pressed in plastic injection molds to obtain standard test samples. The ratio of reinforcement material and the variations in mechanical and thermal properties of the composites induced by the alkali treatment are presented in figures and tables. Furthermore, the changes in cross-sectional material images were examined with electron microscopy scans. The tensile and flexural strength of the material improved with alkali treatment.