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The improved wear and corrosion resistance of gray cast iron (GCI) with enhanced mechanical properties is a proven stepping stone towards the longevity of its versatile industrial applications. In this article, we have tailored the microstructural properties of GCI by alloying it with titanium (Ti) and tungsten (W) additives, which resulted in improved mechanical, wear, and corrosion resistance. The results also show the nucleation of the B-, D-, and E-type graphite flakes with the A-type graphite flake in the alloyed GCI microstructure. Additionally, the alloyed microstructure demonstrated that the ratio of the pearlite volume percentage to the ferrite volume percentage was improved from 67/33 to 87/13, whereas a reduction in the maximum graphite length and average grain size from 356 ± 31 µm to 297 ± 16 µm and 378 ± 18 µm to 349 ± 19 µm was detected. Consequently, it improved the mechanical properties and wear and corrosion resistance of alloyed GCI. A significant improvement in Brinell hardness, yield strength, and tensile strength of the modified microstructure from 213 ± 7 BHN to 272 ± 8 BHN, 260 ± 3 MPa to 310 ± 2 MPa, and 346 ± 12 MPa to 375 ± 7 MPa was achieved, respectively. The substantial reduction in the wear rate of alloyed GCI from 8.49 × 10−3 mm3/N.m to 1.59 × 10−3 mm3/N.m resulted in the upgradation of the surface roughness quality from 297.625 nm to 192.553 nm. Due to the increase in the corrosion potential from −0.5832 V to −0.4813 V, the impedance of the alloyed GCI was increased from 1545 Ohm·cm2 to 2290 Ohm·cm2. On the basis of the achieved experimental results, it is suggested that the reliability of alloyed GCI based on experimentally validated microstructural compositions can be ensured during the operation of plants and components in a severe wear and corrosive environment. It can be predicted that the proposed alloyed GCI components are capable of preventing the premature failure of high-tech components susceptible to a wear and corrosion environment. [ABSTRACT FROM AUTHOR]

Sheet metals such as titanium alloys, steel alloys, and aluminum alloys are significant materials due to their importance among everyday life products as well as high-strength applications in aircraft, ships, automobiles, construction, military, and marine purposes. Recently, laser cutting is one of the best and fastest non-conventional methods to cut sheet metals, so it is necessary to understand how laser cutting parameters affect cutting quality. A comprehensive review was presented to investigate how laser cutting parameters affect the cut surface and kerf quality and which parameters affect cutting quality the most. An overview of the advantages of laser cutting when compared to other methods of machining was presented. In addition, a description of the laser cutting method and the different sources of laser were presented with clearing the range of thicknesses of the cut material for each source and their advantages. Also, a description of the properties and the applications of the studied materials were discussed. The performance parameters ofcutting were illustrated in detail by graphs and equations. The research analysis and discussion were discussed in such organized details by tables and graphs which show the full classification of the studied papers. It was found that the best conditions to obtain low surface roughness, small HAZ width, small kerf width, and small kerf angle are using low laser power, high cutting speed, medium gas pressure, high standoff distance, medium pulse frequency, medium pulse width, small nozzle diameter, small thickness, and nitrogen as an assist gas. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced random vector functional link network (RVFL) algorithm was employed to predict kerf quality indices during CO2 laser cutting of polymethylmethacrylate (PMMA) sheets. In the proposed model, the equilibrium optimizer (EO) is used to augment the prediction capability of RVFL via selecting the optimal values of RVFL parameters. The predicting model includes four input variables: gas pressure, sheet thickness, laser power, and cutting speed, and five kerf quality indices: rough zone ratio, widths of up and down heat affected zones, maximum surface roughness, and kerf taper angle. The experiments were designed using Taguchi L18 orthogonal array. The kerf surface contains three main zones: rough, transient, and smooth zones. The results of conventional RVFL as well as modified RVFL-EO algorithms were compared with experimental ones. Seven statistical criteria were used to assess the performance of the proposed algorithms. The results indicate that the RVFL-EO model has the predicting ability to estimate the laser-cutting characteristics of PMMA sheet. [ABSTRACT FROM AUTHOR]

To accelerate the large-scale cellular automaton (CA) simulation for grain growth, a parallel CA model for grain growth was developed. The model was implemented based on the compute unified device architecture (CUDA) parallel computing platform. The model was verified by the grain growth of a single crystal and the columnar-to-equiaxed transition (CET) of an Al-7wt% Si specimen of uniform undercooling with a constant cooling rate. The grid independence of the model was verified. The grain growth of a plate-like casting of nickel-based superalloy during directional solidification process was simulated and the obtained results of grain density at each section with different heights were compared with the experimental data. The CET transition of directional solidified Al-7wt% Si cylindrical ingot was simulated. The grain texture and cooling curves were in good agreement with experimental results from the literature. Finally, high parallel performance of the CA model was obtained and evaluated. [ABSTRACT FROM AUTHOR]