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The present study looks into the effect of WEDM process parameters on the material removal rate (MRR) and surface roughness (SR) responses when machining hybrid composites (Al-Si12/boron carbide/fly ash) using the Taguchi technique. Fly ash and boron carbide (B4C) particles were used for reinforcement (3%, 6%, and 9% by weight), and aluminium alloy (Al-Si12) was used as a matrix material. ANOVA was used to find out the importance of machining factors that affect the quality features of the WEDM process, as well as the relative role of input parameters in determining the WEDM process’ responses. The greatest impact on the response is finalised by the signal-to-noise (S/N) ratio response analysis. However, as a last step, a confirmation experiment with the best combination was carried out to predict and validate the accuracy of the observed values. As the pulse on time and reinforcement increases, MRR also increases. As the gap voltage, wire feed, and pulse off time decrease, it increases. SR is increased by increasing the gap voltage, pulse on time, and pulse off time, wire feed, and reinforcement. The maximum MRR of 38.01 mm3/min and the minimum SR of 3.24 μm were obtained using optimal machining conditions.

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A review of multiwalled carbon nanotubes as solar thermic fluids and their thermophysical properties is done in this article. The basic fluids were ethylene glycol and water in ratios of 100 : 0, 90 : 10, and 80 : 20. To investigate how surface modification impacts thermophysical properties, three base fluids were combined with surfactant-assisted MWCNTs and oxidized MWCNTs in weight fractions of 0.125, 0.25, and 0.5 percent, respectively. It takes two months to check whether the dispersion stays constant. Thermal conductivity and viscosity measurement were done using heated discs and Anton Paar viscometers. Using oxidized MWCNTs to disperse, the base fluids increased thermal conductivity by 15% to 24%. Surfactant-assisted MWCNTs in nanofluids perform worse than oxidized MWCNTs. The dynamic viscosity of nanofluids is higher than that of basic fluids between 50 and 70°C. During a mathematical computation, all of the MWCNT weight fractions and ethylene glycol volume percentages are included. The correlation may be a good fit for the experimental data within limits. The characteristics are forecasted using feed-forward backpropagation. In this research, buried layer neurons and factors are examined.