International Journal of Lightweight Materials and Manufacture最新文献

Leak proof tube-to-tube sheet joints are mandatory for the optimal operation and longevity of the shell and tube heat exchanger. Tube-to-tube sheet joints play a crucial role as fluid barriers, ensuring effective separation between the tube and shell side fluids within shell and tube heat exchangers. Non-conventional friction stir welding, known for imparting less residual stresses, is not commercially used for the fabrication of tube-to-tube sheet joints due to complex joint configuration and geometrical limitations. An extensive study on friction stir welding considering the geometrical parameters of tube-to-tube sheet arrangement is highly demanded. This research examined the mutual influence of radial clearance ranging from 0 mm to 0.5 mm and tube projection lying from 1 mm to 2 mm in friction stir welding of tube to tube sheet configuration on the pull-out strength, extension and, hardness at the stirring and fusion zones. Optimum radial clearance and tube projection for achieving high mechanical weld properties was estimated using multi-objective integrated Taguchi-PCA-GRA optimization. The result proves that the friction stir welded joint is capable of achieving joint strength close to the tungsten inert gas welded joint. The optimum parameters are 2 mm for tube projection and 0 mm for radial clearance to achieve maximum strength and weld penetration, while minimizing hardness at both stir zone and fusion zone. The findings of this research proved the adaptability of friction stir welding for the fabrication of tube-to-tube sheet joints with the right choice of tube projection and radial clearance.

Wire arc additive manufacturing (WAAM) has increasingly been recognized as a cost-effective method for fabricating intricate metallic parts, especially from nickel-based superalloys. This review covers key aspects of WAAM, including its versatile heat sources (GTAW, GMAW, CMT, and PAW) with unique advantages and limitations for customization. Design for Additive Manufacturing (DfAM) principles are highlighted, enabling intricate geometries and addressing support structures, distortion control, and orientation.

Several nickel-based superalloys (e.g., Inconel 718, Inconel 625, Inconel 617, Hastelloy C276, Hastelloy X, Haynes 282) are rigorously evaluated for WAAM suitability due to their high-temperatureature strength, corrosion resistance, and mechanical properties. The review analyzes process parameters like arc current, wire feed rate, and deposition path. It explores defect detection and prevention strategies and emphasizes post-processing methods (heat treatment, rolling, hot isostatic pressing) in enhancing microstructural characteristics and mechanical properties.

Microstructural characterization techniques (optical microscopy and XRD) provide insights into grain structure, phase composition, and defect presence. In conclusion, this review underscores the paramount suitability of WAAM for producing defect-free and complex structures in nickel-based superalloys. Ongoing research and advancements in WAAM will undoubtedly improve its competitiveness and unlock its full potential in the field of additive manufacturing.

Expanding the use of 6xx aluminum alloy series in various industries is challenging due to the need for cost-effective welding processes and optimal settings to ensure high-quality joints. The present research focused on the comparison of joint performance of the pipes and plates using tungsten inert gas (TIG) and friction stir welding (FSW) The AA6082 alloy material is used for pipes and plates used in the study. Various techniques were utilized, including hardness and tensile tests, and microstructural examinations. Using a scanning electron microscope (SEM), the surface fracture of the specimens that failed under tensile tension was also examined. The present research also included the economic impact on the welding processes used. Results demonstrated that the weld obtained using FSW was defects free whereas, internal flaws were seen in TIG welded samples. The hardness value increased over the base material (BM) for the FSW and TIG by 31–35% and 46-40%, respectively. The FSW joint was welded at a maximum UTS of 3 mm/min and a rotational speed of 3000 rpm. FSW can create the AA60682 flange joints more efficiently and effectively than fusion welding procedures like TIG processes in pipeline applications. For AA6082 flange joints, overall total cost comparisons between FSW and TIG were also made.

The main task of this work is the optimization of the manufacturing process of Al-alloy lattice cellular structures with rhombic cell, obtained with lost-PLA technique. It is an easy, environment sustainable and economical technique (both for infrastructure and operating costs) for the manufacturing of Al porous structure based on the 3D printing of PLA and replication process alternative to that based on expensive metal 3D printers. Plaster processing, PLA burnout and AA 6082 alloy casting conditions and parameters have been suitably tuned in order to get final samples with geometry and surface finishing conditions identical to the starting ones made in PLA. A good replication process has been implemented with a high repeatability rate and accurate surface finishing, comparable with that of the PLA printed objects. Morphological analysis on PLA and Al 6082 was conducted as well microstructural analysis and Vickers microhardness tests on Al alloy samples in the as-cast conditions. Metallography reveals the presence of AlFeSi and AlFeMnSi intermetallic phases at the cell boundaries and some coarse precipitates Mg₂Si in the AA 6082 alloy. Microstructures and HV measured values are aligned with literature data for this alloy in the same (as-cast) conditions.

The fabrication of dissimilar metal joints, particularly between AA 6061 aluminum alloy (Al) and AZ31B magnesium alloy (Mg), poses significant technical challenges due to their distinct metallurgical characteristics and the inherent difficulties associated with welding such materials. These challenges include the propensity for intermetallic compound formation, thermal cracking, and differences in thermal and mechanical properties between the two alloys. Cold Metal Transfer (CMT) welding, known for its low heat input and controlled metal transfer, offers a potential solution to these issues. However, optimizing the process parameters to ensure strong, defect-free joints requires a systematic approach. This study aims to optimize CMT welding parameters using parametric mathematical modeling (PMM) to produce high-strength Al and Mg dissimilar joints and to study the effects of CMT parameters on tensile strength (TS) and weld metal hardness (WMH), as well as the microstructural features of AA 6061 aluminum alloy/AZ31B magnesium alloy (Al/Mg) dissimilar joints. Al/Mg dissimilar butt joints were produced by the CMT process using ER4043 as filler wire. CMT, a low-heat input welding technique, was used to mitigate issues such as intermetallic compounds (IMCs), wider heat-affected zone (HAZ), and distortion. The CMT parameters, particularly wire feed speed (WFS), welding speed (WS), and arc length correction (ALC), were optimized using response surface methodology (RSM) to maximize the TS and WMH of the Al/Mg dissimilar joints. Polynomial regression was employed to create PMMs that integrated these CMT parameters to forecast the TS and WMH of the joints. An analysis of variance (ANOVA) was applied to assess the feasibility of the PMMs. The results indicated that the Al/Mg dissimilar joints, produced using a WFS of 4700 mm/min, a WS of 280 mm/min, and an ALC of 10%, exhibited higher TS and WMH values of 33 MPa and 95.8 HV, respectively. The PMMs provided precise forecasts for the TS and WMH of the Al/Mg joints with an error rate of less than 1% and a confidence level of 97%.

This research dealt with fabrication of suitable lightweight composite panel samples from sawdust for building applications. Raw and alkali-treated sawdust particles were utilized at varying weight proportions (0 %, 25 %, 50 %, 75 %, and 100 %) to develop the samples with topbond as binder. From the results of heat transfer and strength properties tests, the raw sawdust improved thermal insulation efficiency while the treated sawdust enhanced the strength of the samples. For each loading level of sawdust, 100 % screwability and nailability were achieved. The findings suggest that, if used as ceiling panels in buildings, the samples would outperform conventional ceilings like plywood, asbestos, plaster of Paris, and KalsiCeil in mitigating global warming effects, reducing dead loads, and promoting sustainable and cost-effective housing development. This underscores the potential of these samples to address key priorities in construction and environmental sustainability.

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.