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In this study, a novel method, Tubular Channel Angular Pressing-Extrusion (TCAPE), is introduced for manufacturing ultrafine microtubes. This method, integrating Tubular Channel Angular Pressing (TCAP) and microtube extrusion (MTE) processes, reduces the number of stages in the fabrication of ultrafine microtubes while achieving favorable mechanical properties. In the TCAPE process, the tube undergoes Severe Plastic Deformation (SPD) in the shaping region and is subsequently shaped into the desired geometric dimensions through the extrusion process at the end. To investigate the effect of the number of SPD passes on the microstructure and mechanical properties of the produced microtubes, one-pass and two-pass SPD were applied. Metallography, XRD testing, tensile testing, and hardness measurement were employed for analysis. For a one-pass SPD, the sample was processed only through the TCAPE process (TCAP + MTE), while for a two-pass SPD, the sample underwent the TCAP process first and then underwent TCAPE for the second processing step (2TCAP + MTE). Tensile test results indicate an increase in Ultimate Tensile Strength (UTS) from the initial value of 73 MPa–103.1 MPa and 148 MPa, and elongation altered from the initial value of 10 to 7.1 and 17.5 after two-pass SPD. Metallography results show a reduction in grain size from the initial value of 160 μm to 15 μm and 3 μm after two-pass SPD. The TCAPE process, due to applying higher strain (1.955) compared to the TCAP process (1.64), exhibits better performance in refining the microstructure and improving mechanical properties. The hardness and ultimate strength of the TCAPE-processed sample are 13.33% and 13.5% higher than those of the TCAP-processed sample, respectively.

In this study, the Cyclic Contraction-Expansion Extrusion (CCEE) process, a novel severe plastic deformation (SPD) technique, is applied to the AZ91 magnesium alloy to enhance its mechanical properties through microstructural refinement. The CCEE method combines cyclic expansion extrusion (CEE) and cyclic extrusion compression (CEC), integrating their advantages while overcoming drawbacks. The CCEE process is capable of inducing substantial plastic strain (3.38) within a single processing cycle, eliminating the need for secondary punches or a synchronized backpressure system. The process is conducted at a temperature of 300 °C, resulting in a bimodal microstructure through the dynamic recrystallization (DRX) mechanism. This microstructure consists of refined equiaxed α-Mg grains with an average size of 2.8 μm, surrounded by a network of newly nucleated α-Mg grains and Mg17Al12 particles with an average size of 500 nm in the two-pass processed sample. Results obtained from the tensile test technique indicate a significant enhancement in the ultimate tensile strength (UTS) of the AZ91 alloy, increasing from 139 MPa to 276 MPa and 290 MPa, and a notable improvement in elongation, increasing from 4% to 8% and 12% after two passes of the CCEE process. Macro-texture X-Ray diffraction (XRD) measurements reveal the formation of a pyramidal deformation texture in the one-pass sample, contributing to the UTS improvement. This texture weakens during the second pass, leading to an increase in elongation. Furthermore, microhardness measurements show an increase from HV 62 to HV 85 after the first pass of the CCEE and HV 73 after the second pass.

In the present study, the effects of rare earth element Y, texture intensity, and grain size on the tension-compression mechanical behavior of extruded Mg-XY(X = 0–3, wt pct) rods were investigated using improved phenomenological crystal plasticity. To this end, finite element modeling of a three-dimensional representative volume element (3D-RVE) was employed to consider the effects of microstructural parameters. Subsequently, the computational modeling approach was validated with the experimental data to assess the reliability of predictions of the responses of a polycrystalline aggregate. Afterward, the validated computational modeling was employed to predict the mechanical behaviors of extruded Mg-XY (X = 0–3, wt pct) by considering the role of slip/twinning activities during deformation. The results showed that the Y addition significantly improved the yield strength, ultimate strength, and ductility. Examination of the deformation modes activities indicated that the basal slip activity of extruded Mg-XY (X = 1–3, wt pct) is higher than that of extruded pure Mg due to the formation of non-basal texture components, which hindered the twinning activation. Increasing the Y content further reduced the suppression of tensile twinning activity. Therefore, the weak tension–compression yield asymmetry of extruded Mg-XY (X = 1–3, wt pct) was mainly attributed to the reduced tensile twinning activity. The simulated stress-strain curves illustrated that texture weakening, and grain refining improved the mechanical behavior and reduced tension-compression yield asymmetry.

In this paper, the propagation of ultrasonic guided wave in the isotropic single-layer and multi-layer plate with the assumption that layers are fully connected to each other and top and bottom surfaces of plate are free stress, are investigated and the dispersion curves, including diagrams of frequency spectrum, phase velocity and group velocity for single-layer and multi-layer can be extracted. The next, using the obtained dispersion curves how to excitation a specific mode at a probe frequency for single-layer plate and multi-layer plate using the phased array technique to be paid and graphs of emission angle versus frequency for single-layer plate and multi-layer plate are plotted and results are compared with each other.

Noise is one of the most common workplace hazardous agents that can cause permanent hearing damage. Workers in many industries are usually exposed to noise levels with high risks of hearing loss. Accordingly this research aims to study the noise exposure and haring status of registered locksmiths who are exposed to harmful effects caused by several factors, such as key making machines loud noises. This study has been carried out in 33 key workplaces in Tehran capital city of Iran. In order to eliminate the effects of background noise, two different measurements were carried out in the same field conditions by taking in and out of key making machines .The overall sound level and octave band of noise analysis of the key making machine, during the process of Right and Left Shift Gears by considering the background noise level during off time of the machine was determined using ISO 9612 standard method. Hearing threshold of locksmiths is also determined using the NIOSH standard method. Based on results, average of right and left groove keys scraping processes and background noise levels were 92.9, 96.2 and 66.5dBA respectively. The mean noise exposure time of locksmiths was 0.2 h/day. So, the amount of the workers noise equivalent level was found to be 77.63 dBA which is lower than the ACGIH threshold limit values. The results of audiometric tests also showed no significant hearing loss among locksmiths, something can be explained by their low noise exposure levels. It is suggested to assess hearing response of the workers by other methods like ABR.

Optimization of continuous synthesis of high purity carbon nanotubes (CNTs) using chemical vapour deposition (CVD) method was studied experimentally and theoretically. Iron pentacarbonyl (Fe(CO)5), acetylene (C2H2) and Ar were used as the catalyst source, carbon source and carrier gas respectively. The synthesis temperature and flow rates of Ar and acetylene were optimized to produce CNTs at a large scale. A flow rate of 30-120 sccm of acetylene and 500-3000 sccm of Ar at temperatures between 650-950 °C were examined. Using the fundamental trial and error method it was found that the maximum yield of pure CNTs can be produced at 750 °C with flow rates of 40-45 sccm of acetylene and 1500 sccm of Ar. In theoretical part, an artificial neural network (ANN) and the Bees Algorithm (BA) were used to model and optimize the CNTs production, based on the experimental data. The Bees Algorithm used the ANN as the fitness function and the optimum variables found as 60 sccm for acetylene, 555 sccm for argon and 759 °C for temperature. The computational results have relatively good agreement with the experimental results.