International Journal of Lightweight Materials and Manufacture最新文献

The automotive and aerospace sectors are progressively employing the magnesium (Mg) alloy of the grade AZ31B because of its excellent castability, low density, and high ratio of strength to weight. Nevertheless, the limited ability of AZ31B alloy to withstand corrosion limits their use in several fields of technology. In order to solve this problem, the AZ31B alloy is coated utilizing an AA2024/Al₂O₃ metal matrix composite (MMC) coating that is applied by the cold spray coating (CS) method. The primary goal of this work is the parametric optimization of CS process for maximizing adhesive strength of MMC-coated Mg-alloy substrate. Response surface methodology (RSM) is implemented to find the optimum CS parameters, including feed rate of powder – FRP (g/min), standoff distance of gun – SDG (mm) and processing temperature – TEMP (°C). The regression-based parametric adhesion strength prediction (ASP) model was formulated using the RSM and statistically validated using analysis of variance (ANOVA). Employing 3D surface of responses, the influence of CS parameters on the adhesion strength of an MMC-coating was assessed. The findings revealed that when the MMC-coating was cold sprayed on the Mg-alloy using FRP of 22 g/min, SDG of 12 mm, and TEMP of 520 °C, the maximum adhesion strength of MMC-coating was 70 MPa (actual). Given less than 2% error at 95% confidence, the parametric ASP model correctly predicted the adhesion strength of the MMC-coating. The ANOVA findings showed that FRP (g/min) had significant effect on adhesive strength of MMC-coating followed by SDG (mm) and TEMP (°C). The MMC-coating applied using the RSM optimized CS parameters showed 70.73% superior adhesive strength owing to the lower porosity formation of 2 vol% which offers greater interfacial area. The ASP equation was formulated using the “best fitting line” approach and validated using ANOVA for predicting the adhesive strength (MPa) from the porosity formation (vol%) in the MMC-coating.

The estimation of transition fatigue lifetimes for piston aluminum alloys was carried out using unsupervised machine learning (ML) with the K-means algorithm. For this purpose, an experimental dataset representing standard ISO specimens with piston aluminum alloy material, which was subjected to rotational bending fatigue tests under fully reversed cyclic load conditions, was utilized. Subsequently, the stress and fatigue lifetime data were employed to fit the algorithm of K-means clustering. Then, to enhance the K-means performance, various preprocessing methods and Kernel functions were employed to cluster fatigue lifetime and stress data. Furthermore, following the division of the data into multiple clusters, the middle cluster, which represents fatigue lifetime and stress, was identified as the transition fatigue region, and its center defines the estimated transition fatigue lifetime. Ultimately, the transition fatigue lifetimes were determined using the Coffin–Manson–Basquin equation for piston aluminum alloys and compared to the estimated transition fatigue lifetimes, along with the calculation of relative errors. The obtained results indicated that, among the different models employed in this study, the polynomial Kernel K-means clustering algorithm proved to be the most efficient for clustering data within stress and number of cycles plots (S–N plots). Moreover, employing the K-means algorithm with a polynomial Kernel function and five cluster numbers yielded the most accurate estimation of transition fatigue lifetime for piston aluminum alloys, exhibiting the lowest relative error.

Dimensional distortion and instability in the milling process of aluminum alloy parts can significantly increase production costs and result in defective parts. Therefore, distortion mitigation has long been a central focus of aerospace industry researchers. This article aims to investigate the effect of axial ultrasonic-assisted milling on distortion. In this study, the machining parameters effect in conventional milling (CM) and ultrasonic assisted milling (UAM) were experimentally and statistically investigated on distortion and milling force, and the results were subjected to a comparative analysis. Experiments provided compelling evidence of the technical advantages offered by axial ultrasonic-assisted milling, demonstrating its efficacy in reducing both milling force and distortion when compared to conventional milling. Furthermore, our study established a direct relationship between milling force and distortion. Applying the axial ultrasonic-assisted vibration resulted in a notable 29% reduction in cutting force compared to conventional milling. Additionally, UAM exhibited a reduction in distortion by approximately 21%. These findings have significant implications, particularly in improving the flatness tolerance of the workpiece, thereby yielding components free from waves and warpages.

In this study, the effect of resistance spot welding (RSW) and laser beam spot welding (LBSW) processes on evolution of microstructure, load endurance capabilities, heat affected zone (HAZ) softening, and corrosion resistance of ultra-high-strength (UHSS) steel joints welded in lap joint design is investigated. The UHSS sheets of dual phase 1000 grade (UHSDP1000) having 1.20 mm thickness were joined using the RSW and LBSW parameters optimized by response surface methodology (RSM). The microstructural features of welding regions of RSW and LBSW joints were studied using optical microscopy (OM). The load endurance capabilities of RSW and LBSW joints were assessed using the tensile shear failure load (TSFL) and cross-tensile failure load (CTFL) tests. The ruptured surfaces of TSFL and CTFL tested samples were examined utilizing scanning electron microscopy (SEM). The microhardness distribution of divergent regions of RSW and LBSW joints was evaluated and imputed to the TSFL and CTFL failure of joints. The corrosion resistance of RSW and LBSW joints was analyzed using potentiodynamic corrosion and immersion corrosion tests. The RSW joints showed 183% and 62.79% greater TSFL and CTFL endurance capabilities than LBSW joints. The TSFL and CTFL endurance capabilities of LBSW joints are inferior to RSW joints due to the smaller load bearing area. It causes the stress concentration in FZ and HAZ of LBSW joints. The RSW joints and LBSW joints disclosed TSFL and CTFL failure in button pull out rupture mode with tearing of HAZ. The failure of RSW and LBSW joints in HAZ is due to the softening caused by martensitic tempering and coarsening of grains. The LBSW joints disclosed inferior resistance to corrosion than RSW joints due to the higher martensite content which contributes to greater fraction of favorable pitting sites and decreased corrosion resistance.

The AA6082-T6 was experimentally studied in the present research with respect to the drilling performance. Drill diameter, cutting speed and feed rate were examined, using a full factorial design. Mathematical modelling of the process was carried out using the Response Surface Methodology (RSM) as well as the Artificial Neural Network (ANN) techniques. The output results in terms of cutting force, torque and surface roughness, revealed high levels of correlation between the experimental and the predicted data. Specifically, the Mean Absolute Percentage Error (MAPE) values using RSM compared to the ones of the experiments, were equal to 2.14%, 3.49% and 6.16% for F_z, M_z and R_a respectively. The equivalent MAPE between the ANN and the experiments were found to be 2.19%, 1.82% and 2.85% accordingly. Moreover, the most significant terms were revealed, being the interaction D × f for the thrust force and the torque with contribution percentages equal to approximately 44% and 42% respectively, and the term D² for the surface roughness with 51%. The evaluation of the machining parameters, identified their significance, enabling the selection of the optimal cutting parameters, which were obtained by the desirability function, taking into account the importance of the generated surface quality and the reduction of cost. The solutions given by this approach, pointed out the Ø9 tool, coupled with V_c = 50 m/min and f = 0.15mm/rev as a well-balanced combination, whereas the Ø9.9 tool used under the same conditions, yielded the best possible surface quality (appr. 0.2 μm).

The effects of salt water exposure at deep ocean depth pressures when coupled with low temperatures on the material characteristics of three unique additively manufactured polymers has been investigated through a detailed experimental approach. The polymers in the study were manufactured utilizing both Vat Photopolymerization and Material Extrusion printing techniques. The Material Extrusion process was utilized to produce material specimens of Stratasys ULTEM 9085 and Markforged Onyx while the Vat Photopolymerization process was used to produce specimens of Accura ClearVue. The ULTEM 9085 and Markforged Onyx are filament based polymers and the ClearVue is a liquid based resin. The specimens were first submerged in a high pressure, salt water bath of 3.5% NaCl solution at 34.5 MPa (5000 lb/in²) for a total exposure time of 60 days to determine the water absorption characteristics. Subsequent to the salt water exposure at high pressure, the specimens were evaluated to determine changes in tension, compression, flexure, and in-plane fracture properties. To determine the effects of water saturation and low temperature coupling, the mechanical testing was performed at temperatures of 20 °C, 0 °C and −20 °C in both dry and saturated conditions. Additionally, non-destructive testing in the form of TeraHertz and FIRT imaging was conducted to analyze the physical material changes through the thickness of the material due to the saline water absorption. To quantify the change in material storage and loss moduli properties, Dynamic Mechanical Analysis (DMA) characterization was performed on each of the AM polymers in dry and saturated states. The DMA testing also quantified changes in the Glass Transition Temperature because of salt water exposure. In summary, The current study investigates the effects of coupled long term/high pressure salt water exposure with low temperatures on the mechanical and material characteristics of three unique AM polymers by: (1) immersing the materials in a salt water solution at 34.5 MPa for 60 days, (2) Conducting post exposure mechanical testing on the materials at 0 °C and −20 °C with comparisons to 20 °C testing on dry specimens, and quantifies changes in material properties through DMA experiments. The results from all testing in the study show that high pressure salt water exposure when coupled with low temperatures has unique effects on each of the materials considered in the study and careful consideration to each parameter must be given based on the material type when components will be employed in marine operations.

The microstructure of a linear friction welded joint of 7050 aluminum alloy was investigated through optical microscopy (OM), scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD). The analysis focused on grain boundary types, microstructure, and mechanical properties of the joint. The results reveal that fine equiaxed crystals are generated in the welded zone through dynamic recrystallization. The average grain size is 6.8 μm, with a volume fraction of large angle grain boundaries reaching 69.5%. The microstructure primarily consists of Cube {001}<100> texture, {111}<110> Brass recrystallization texture, and a small amount of copper {112}<111> deformation texture. The thermo-mechanically affected zone (TMAZ) presents a linear structure with an average grain size of 15.8 μm and a volume fraction of 36.1% at large grain boundary, resulting in a deformed Brass {011}<211> texture and a small amount of {236}<385> as well as {111}<110> Brass recrystallization texture. The welded joint exhibits a tensile strength of 492 MPa and a yield strength of 380 MPa, which represents 94.2% and 78.5% of the base material, respectively. Furthermore, the elongation of the joint is 10.2% and 98% of the base material, respectively. The fracture of the tensile sample is observed in the TMAZ, showing good mechanical properties with a mixed fracture mode with some degrees of ductility and brittleness.