International Journal of Lightweight Materials and Manufacture最新文献

Large amount of wood dust is created as a byproduct of woodworking activities. Every year, there is an increase in wood dust generation, which severely pollutes the environment. Consequently, it becomes imperative to use wood dust in the production of useful products. A Carbonized Wood-Silicon Dioxide Filled Natural Rubber Composite (CWSDFNRC) was therefore created in this work using a compression molding method. The friction and compression properties of the composites were determined. Modeling of the composite's mechanical and friction characteristics was done using artificially intelligent techniques including Response Surface Methodology (RSM), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The novel material was thermally analyzed using Dynamic Mechanical Analysis (DMA), Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA), and Differential Thermal Analysis (DTA). The effectiveness of RSM, ANN, and ANFIS was demonstrated by relevant error indices. The optimization method revealed the ideal level of fitness at particle size, carbonization temperature, filler content, curing temperature, curing pressure, and curing time of 150 μm, 214 °C, 51 phr, 150 °C, 3 Pa, and 10 min respectively. These fitness conditions gave an optimal value of 17.63 MPa for compressive strength and a friction coefficient of 0.96. The novel material's characteristics contrasted well with those of comparable materials described in the literature, suggesting that it has the potential to be used in the manufacture of outer shoe soles and other elastomeric applications.

Distinct alloys have different chemical and thermal characteristics, making it difficult to weld together. For the purpose of maximizing tensile strength and weld hardness of the joint, the gas metal arc (GMA) welding process for the dissimilar aluminium alloys AA5083-O and AA6061-T6 was modelled and optimized in the current study. A genetic-neural approach was attempted, in which optimal artificial neural network (ANN) was applied to model the process and genetic algorithm (GA) approach was extended to optimize the parameters. The proposed genetic-neural (GA-ANN) approach was also compared to the traditional response surface methodology (RSM). In predicting the reactions of a GMA welded joint made of two different alloys, AA5083-O and AA6061-T6, the suggested optimum ANN model was shown to be more accurate (error 6%). The genetic-neural optimization technique has less inaccuracy (approximately 5% error) than the RSM optimization approach, however the more computational time was required to select GA-ANN parameters.

The ultrasonic spot welding (USW) is used to develop the lap joints of AA 6061-T6 aluminium alloy because it is difficult to spot weld using resistance spot welding (RSW) and laser beam spot welding (LBSW) processes due to its high electrical conductivity, thermal conductivity and light reflectivity respectively. The main objective of this investigation is to optimize the USW parameters specifically welding time (s), amplitude (%) and pressure (bar) for enhancing the tensile shear fracture load (TSFL) bearing capability of AA 6061-T6 aluminium alloy lap joints for automotive applications. The statistical response surface methodology (RSM) was utilized for generating strength prediction models (SPM) and validated using analysis of variance (ANOVA). The RSM is widely used for optimizing the process parameters as it provides greater information such as optimum conditions, direct effect of process parameters and performance prediction from limited number of experiments compared to other optimization techniques. The response surfaces were created using RSM and analyzed. The effect of USW parameters on macrostructure, microstructure and TSFL of USW joints was studied. From the results, it was observed that the USW joints created using the welding amplitude of 100%, welding time of 21 s and welding pressure of 6 bar exhibited greater TSFL capacity of 5.08 kN. The SPM accurately predicted the TSFL of USW joints within 5% error on 95% confidence. Welding pressure disclosed major effect on TSFL of USW joints followed by welding amplitude and time. The greater TSFL of USW joints is imputed to the better coalescence of weld surfaces and refined microstructure.

Despite the wide growth of additive manufacturing, it is still very expensive to mass produce 3D-printed parts. The costs can be minimized if the quantity of material required to produce a part can be substantially reduced by introducing hollow cavities into the structure, without compromising its properties. This study investigates the effect of the degree of hollowness and different internal cavity structures on the mechanical properties of 3D-printed materials. Test specimens were prepared with four polymeric materials (i.e., acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), carbon fiber-reinforced (CFR) ABS, and CFR PLA) using the fused deposition modeling 3D printing technique. Internal hollow cavities were introduced to the specimens during printing and the specimens were prepared with three different cavity structures (i.e., hexagonal honeycomb, circular drills, and squares), and the degree of hollowness was varied from 0% to 30% in 10% increments. Tensile and flexural properties of the 3D-printed specimens were evaluated and analyzed. The mechanical properties of all specimens were found to decrease with increasing hollowness levels, regardless of the type of material or the internal cavity structure. The hexagonal honeycomb structure showed the best tensile properties out of the three internal cavity structures, while the flexural properties were not significantly affected by the internal cavity structure. The material type had a significant impact on the mechanical properties with PLA exhibiting better tensile and flexural properties than ABS, while their carbon fire reinforced counterparts showed enhanced mechanical properties than pure ABS and PLA.

Magnesium and its alloys remain perilous in the framework of light weighting and advanced devices structure such as rockets and satellites. However, the utilization of Magnesium (Mg) is increasing every year, revealing growing demands in manufacturing industries. Manufacturing of Mg components is challenging because of their HCP crystal structure and limited ductility. In this context, additive manufacturing (AM) provides the flexibility to manufacture complex shape components with excellent dimensional stability. It also provides a new possibility for utilizing novel component structures that increase the applications for Mg alloy. This review herein pursues to holistically explore the additive manufacturing of Mg alloy with a synopsis of processes used and microstructure, mechanical properties, corrosion behaviour and postprocessing of AMed Mg alloy. The challenges and future scope of AMed Mg alloys are critically explored.

Materials properties are highly dependent on the processing parameters and technique used during sintering. The effect of Spark Plasma sintering process parameters (pressure and temperature) on the hardness and relative density of Ni–20Cr–5ZrO₂ composite was investigated. Response Surface Methodology (RSM) from the design of experiment (DOE) technique was successfully employed for the experimental design, and statistical analysis was conducted on the obtained experimental results. The microstructural analysis of the sintered composite showed the presence of solid solution phases of Ni and Cr, which were confirmed by the XRD results as (Cr,Ni) alongside unreacted ZrO₂ particles at sintering temperatures of 950 °C and 1000 °C. The validity of the model developed with the impact of each variable and their corresponding interaction on the responses was performed using analysis of variance (ANOVA). The relative density and hardness were the two responses considered. The actual values (experiment data) and expected values (simulated data) were subjected to statistical analysis, to develop a predictive model that synchronizes density and hardness as distinct process parameters, with material hardness and relative density serving as the responses of the specified experiment. For the responses, quantitative models were created, and 10 experimental runs were processed to ascertain the desirability of the responses. The SPS processing parameters considered the most desirable were 1000 °C sintering temperature and 50 MPa pressure. The hardness property obtained under this condition is 433.23 HV with a relative density of 98.15%.

The high entropy alloys (HEAs) are relatively a new class of materials that have attracted significant attention of engineering sector in recent years due to their extensive mechanical properties, high strength to weight ratio, thermal stability and resistance to corrosion and oxidation. HEAs are characterized by their unique composition that is typically composed of five or more elements in equal or somewhat substantial proportions. This leads to the evolution of highly complex microstructure that makes it challenging to weld. To fulfil the key requirements of the design and manufacturing, these HEAs must be capable of being welded in a satisfactory manner. The joining of similar and dissimilar combinations of HEAs and other engineering materials system have been proved to be feasible which further expands their structural applications in aerospace, nuclear and defence sector. Additionally, the fillers of HEAs disclosed greater potential in suppressing the evolution of detrimental intermetallics and enhancing the mechanical properties of joints. So, in this study, a comprehensive review on the current state of research in fusion welding of HEAs particularly Al_xCoCrFeNi and CoCrFeMnNi is provided to address the weldability of HEAs under the diversity of composition, initial working condition, welding processes, operating parameters, configuration of joint and operating conditions. The latest challenges, progress and future perspectives in fusion welding of HEAs are reviewed critically with a particular focus on microstructure and mechanical properties of joints. The effect of fusion welding processes such as gas tungsten arc welding (GTAW), gas metal arc welding (GMAW), electron beam welding (EBW) and laser beam welding (LBW) on microstructural characteristics, mechanical properties and corrosion behaviour of HEAs joints is reviewed and discussed. The effect of post weld heat treatment and HEAs fillers on the mechanical properties and microstructural evolution of welded joints is also discussed. Further, an insight into the potential application of HEAs in advanced engineering applications is provided. The current review article aims to provide an overview of challenges, opportunities, current state of research and main directions in fusion welding of Al_xCoCrFeNi and CoCrFeMnNi HEAs and to highlight their potential as high-performance material in a range of applications.

Numerous studies have investigated the advantages of using composite laminates made of both metals and fibers, which include being able to sustain heavier loads, having better resistance to impacts, and being more durable, while also being lightweight. In this particular study, we utilized the hand lay-up method to create composite laminates consisting of three layers of aluminum alloy and 60 layers of fiber. We tested three different types of aluminum alloy (Al-2024, Al-5052, and Al-7075) and two types of fiber (kevlar and carbon), which were divided into three categories: kevlar fibers, TiC nanoparticle-impregnated kevlar fibers and carbon fibers. We then combined each type of fiber with each type of aluminum alloy to make nine distinct composite laminates. To determine the mechanical properties of the laminates, we used a rule-of-mixture formula. Our research revealed that kevlar fibers had a more significant impact on increasing the yield strength and ultimate tensile strength of the composite laminates than carbon fibers. However, carbon fibers have a greater effect on the modulus of elasticity of the composite. Among all types of aluminum, Al-2024 provides the highest mechanical properties for composite laminates. However, impregnating kevlar fibers with TiC nanoparticles did not enhance the anti-ballistic performance of composite laminates. Consequently, composite laminate that consists of Al-2024 and carbon fibers exhibits the best mechanical properties and anti-ballistic performance, making them the ideal choice for anti-ballistic applications.

This study focuses on the development of a large-dimensional 3D printer and its challenges in general. The major fused deposition modeling (FDM) printers focus on printing small-scale parts due to their challenges in printing large-scale objects using thermoplastic polymer filaments. A novel large-dimensional multi-extrusion FDM printer is developed at the workshop and printed several large-dimensional objects to emphasize its prospects in developing large-scale products. The printer has a print bed with a dimension of 900 mm × 1100 mm × 770 mm with respect to the length–width–height (L–W–H), respectively. There are many challenges to successfully printing large-dimensional objects using FDM technology. The experimental design elaborates on the challenges experienced during printing various large-dimensional objects. In addition, the paper focuses on the qualitative analysis of the optimal process parameters in section 4.5. Based on the experimental results, the key challenges are found to be uneven bed temperature, bending of print bed due to thermal effect, surface unsticks due to lack of adhesive force, surrounding temperature, and irregular filament feed. Experimental results also validate the key design specifications and their impact on enhancing large-scale 3D printing. The developed printer is capable of printing large-scale objects with five different thermoplastic materials using five individual extruders simultaneously. It adds a new dimension of flexible automation in additive manufacturing (AM).

The inhomogeneity of joints during superplastic deformation greatly limits the application of laser beam welding/superplastic forming (LBW/SPF). In order to adjust the deformation uniformity of the joint, Yb₂O₃ with different mass fractions was added to the laser welded joint of TC4 titanium alloy, and the effect of Yb₂O₃ on the superplastic deformation behavior of the laser welded joint of TC4 titanium alloy was studied. The results showed that the addition of Yb₂O₃ can effectively refine β grains. At Yb₂O₃ content of 6 wt%, the refinement effect of Yb₂O₃ on the weld grains is the most obvious. At this time, the peak flow stress of the longitudinal weld sample reaches a minimum value of 25.6 MPa, and the superplasticity of the joint is significantly improved. The elongation of the transverse welded sample reached 29% of that of the base metal and the joint deformation uniformity was significantly improved. The prior β grain of weld broke during superplastic deformation, and the acicular martensite structure in the weld was gradually transformed into a lamellar structure. After the addition of Yb₂O₃, the lamellar structure inside the weld becomes short and disordered, which promotes occurrence of superplastic deformation.