Alloy A356 Research Articles

Effect of Vanadium/Boron Ratio on the Microstructure of Al-V-B Master Alloy and Their Grain Refining of Alloy A356.2

Effect of Vanadium/Boron Ratio on the Microstructure of Al-V-B Master Alloy and Their Grain Refining of Alloy A356.2

Static mechanical properties and failure behaviors of self-piercing riveted joints in aluminum alloy 5A06 after aging

This paper conducts an investigation on the static mechanical properties and failure behavior of self-piercing riveted joints in aluminum alloy 5A06 after being subjected to the aging process. The study involves three distinct categories of joint specimens: original specimens, 1-year aged specimens and 1-year aged specimens that have been additionally heat-treated at 200 °C. The research findings affirm that strain aging is responsible for a reduction in the peak strength of the joints. Furthermore, the weakest failure chain within the self-piercing riveted joint shifts towards the upper sheet due to a more significant reduction in internal stress experienced by the upper plate. This leads to a failure model characterized by upper sheet pull-off. Through Weibull distribution analysis, it has been established that the 5 % lower limit value for the strength of the SPR joint experiences an 86 % decline following 1-year aging. In practical terms, this means that for a vehicle structure with 7000 riveting points will lose an overall structural strength equivalent to the initial strength of 1000 riveting points within one year.

Multi-Objective Optimization of Tribological Characteristics for Aluminum Composite Using Taguchi Grey and TOPSIS Approaches

In this study, a multi-objective optimization regarding the tribological characteristics of the hybrid composite with a base material of aluminum alloy A356 as a constituent, reinforced with a 10 wt.% of silicon carbide (SiC), size 39 µm, and 1, 3, and 5 wt.% graphite (Gr), size 35 µm, was performed using the Taguchi method, gray relational analysis (GRA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making methods. Tribological tests were carried out on a “block on disc” type tribometer with lubrication. Load, sliding speed, and graphite mass concentration were analyzed as input parameters. As output parameters, wear rate and coefficient of friction were calculated. An analysis of variance (ANOVA) was conducted to identify all parameters that have a significant influence on the output multi-response. It was found that the normal load has the highest influence of 41.86%, followed by sliding speed at 32.48% and graphite addition at 18.47%, on the tribological characteristics of composites. Multi-objective optimization determined that the minimal wear rate and coefficient of friction are obtained when the load is 40 N, the sliding speed is 1 m/s, and the composite contains 3 wt.% Gr. The optimal combination of parameters achieved by GRA was also confirmed by the TOPSIS method, which indicates that both methods can be used with high reliability to optimize the tribological characteristics. The analysis of worn surfaces using scanning electron microscopy revealed adhesive and delamination wear as dominant mechanisms.

Effect of Ni and Sr on the microstructure and tensile properties of the squeeze cast Al‐Si‐Cu alloy at elevated temperatures

AbstractThe influence of the transition alloying element nickel and the alkaline earth element strontium on the microstructure and tensile properties of squeeze cast Al−Si‐Cu alloy under as‐cast condition at elevated temperature of 100 °C, 200 °C and 300 °C is investigated in comparison with the conventional Al−Si‐Cu alloy (A380). Aluminum alloy A380 is alloyed and modified with 2 wt% additional nickel (Ni) and 0.02 wt% strontium (Sr). Squeeze casting is employed to cast the modified A380 under an applied pressure of 90 MPa. The results of tensile testing at the selected elevated temperatures indicate that the Ni and Sr containing A380 alloy exhibits a significantly improvement on tensile properties, specifically ultimate tensile strength and yield strength with 10 %‐30 % increases. The as‐cast microstructures of both the conventional and Ni and Sr‐containing alloys are observed by an optical microscope and further analyzed with scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The presence of Ni‐containing intermetallic phases with Ni addition, and the modified eutectic Si phase with refined morphologies due to the Sr addition should be responsible for the considerable enhancement on the as‐cast strengths of the squeeze cast Ni‐ and Sr‐containing alloy over those of the conventional A380 alloy.

Effect of copper addition on mechanical properties and microstructures of LM25 cast alloys

The use of aluminum alloys in automobiles is expanding, and the potential for additional increases is significant. Further growth will be determined by improvements in material qualities for existing applications or the discovery of new applications. Alloy A-356 (LM25) is commonly employed for high-quality alloy wheel rims in various motor vehicles, constituting 40% of global car usage. This study introduces 0.2% Cu into the Al–Si–Mg alloy system to enhance the mechanical properties. The alloy blend is cast into a metal mold, subjected to a 4-h cure at 540 °C, quenched with water, and precipitation hardened for 12 h at 1800 °C. Optical and scanning electron microscopes are utilized to analyze the alkali microstructure. The mechanical properties of alloyed and unalloyed castings, including hardness and tensile test results, are examined in untreated and heat-treated states. Fracture surfaces of tensile specimens are scrutinized. Intermetallic compounds formed during solidification are studied using scanning electron microscopy and x-ray diffraction analysis. The tensile strength under unalloyed (LM25) and alloyed (LM25 + 0.2 wt. % Cu) conditions before and after heat treatment [(72, 165.4 and 88.3, 237.1) and (78, 179.6 and 98, 252.9, respectively)] shows a significant increase.

Influence of Tool Pin Profiles on Aluminium Alloy A356 and Ceramic-Based Nanocomposites for Light Weight Structures by Friction Stir Processing

In this research, the main aim is to focus the enhancement of aluminium-based metal matrix composites for improving the attributes of light weight metals, aerospace structures and other tailor blank material properties. By this way, the friction stir processing (FSP) was the suited alternate technique to enhancing the mechanical attributes and superior microstructural amendment in the processed MMCs. Therefore, this study investigates the dispersion of ceramic-based strengthening particles of chromium oxide (Cr2O3) in the aluminium base matrix of A356 alloy. During the processing, the different tool pin sizes having the conical threaded tool pin profiles. Similarly, the tool spinning speed and tool travel speed also varied while in FSP. Before the processing, the A356 alloy was prepared by the grooved surfaces for packing the chromium oxide particles to compose the aluminium metal matrix composites. The tensile strength and hardness was employed to carry out from the friction stir processed A356 alloy with influencing of Cr2O3. The maximum occurred tensile processing parameters are 1500 rpm of spinning speed, 6 mm of tool pin sizes and 90 mm/min of tool travel speed. Similarly, the maximum obtained hardness processing parameter are 2000 rpm of spinning speed, 5 mm of tool pin sizes and 90 mm/min of tool travel speed. A scanning electron microscope was utilized to investigate the dispersed Cr2O3 in the A356 alloy for confirming the refinement grains in the nugget zones of FSPed A356 alloy. The increased grain boundary by the influence of different tool pin sizes was the major reason to produces the better mechanical properties in the processed A356/Cr2O3.

An Inhibitor-Loaded LDH- and MOF-Based Bilayer Hybrid System for Active Corrosion Protection of Aluminum Alloys.

A novel inhibitor-loaded bilayer hybrid system based on the LDH inner layer and MOF outer layer is designed on an aluminum alloy 2A12 surface to improve corrosion performance. The hybrid film system covers the inherent cavities and intercrystalline defects of the LDH film using the affinity between the LDH and the MOF compounds. The results demonstrate that the LDH-inhI precursor film is entirely covered by new Zn-based MOF microrods. The LDH-inhI precursor film is partially dissolved and recrystallized in favor of MOF crystal growth to strengthen the binding adhesion between LDH and MOF films. The LDH-inhI/MOF-inhII bilayer film shows significantly enhanced corrosion resistance through the synergistic action of LDH and MOF nanocontainers doped with different corrosion inhibitors (vanadates, 2,5-furandicarboxylic acid, and benzotriazoles). Due to the multiple loadings of the MOF film and the sustained-release of the LDH film, this method provides an effective approach to developing new anticorrosion systems and enhancing both the barrier ability and active corrosion protection performance of LDH-based conversion treatments.

Heterogenous Grain Nucleation in Al-Si Alloys: Types of Nucleant Inoculation

The objective of the current work is to establish, on the one hand, the conventional mechanisms of grain refining and, on the other hand, the effect of the refining-modification interaction in Sr-modified Al-Si alloys on the achieved grain refining and the modification of eutectic silicon. For this purpose, the hypereutectic alloy A390.1 (~17%Si) was used. Various grain refiners were used, namely, Al-10%Ti, Al-5%Ti-1%B, and Al-4%B. After the preparation of the liquid metal, several concentrations of these master alloys were added to the liquid bath according to the desired objective. The different melts prepared were heated at 750 °C and cast in a preheated graphite mold with a solidification rate of around 0.8 °C/s. The liquid metal was. The presence of strontium (added in the form of Al-10%Sr master alloy) and boron completely affects the microstructure of the alloy. An atom of Sr unites with 6 atoms of B to form a compound whose stoichiometric formula is of the SrB6 type, leading to a significant reduction in the modification. A strong relationship exists between the addition of B and the recovery level of Sr. The affinity between titanium and boron is stronger than the affinity between boron and strontium. Both B and TiB2 phase particles do not react with Si; it is only the Ti part of the Al-Ti-B master that forms (Al, Si)3Ti. Regardless of the amount of Si content in the alloy, the Al-4%B master alloy achieves the best grain refining compared to Ti-containing master alloys.

Modeling surface quality, cost and energy consumption during milling of alloy 2017A: a comparative study integrating GA-ANN and RSM models

ABSTRACT The use of simple machining features to determine cutting parameters and the machining process is limited, as parts may contain complex features interacting with each other. This study, therefore, focuses on pocket/groove features and proposes an approach integrating hybrid GA-ANN and RSM algorithms to predict surface quality, cost, and energy consumption (QCE). A parametric study was carried out, taking into account the swarm population size (pop) and the number of neurons (n) in the hidden layer, to find the best prediction using the hybrid GA-ANN algorithm. The results showed the highest correlation values (R2) for all output variables (above 0.97%). The study also revealed that the allocation of machining strategies and sequences can have a significant impact on energy consumption, with a 99.25% variation between minimum and maximum values. Mean square error (MSE) data confirmed the effectiveness of the GA-ANN model. Compared with RSM model predictions, energy consumption (Etot), cost (Ctot), and surface quality (Ra) values all showed statistically significant increases of 90.9%, 96.55%, and 40.18%, respectively. This study highlights the potential of the GA-ANN hybrid approach for multi-criteria prediction (quality, cost, and energy: QCE) in comparison with the RSM method, offering potential improvements for machining 2017A alloy.

Fatigue assessment of defective A357-T6 cast aluminum based on affected depth

Fatigue assessment of defective A357-T6 cast aluminum based on affected depth

The influence of worm gear material and lubricant on the efficiency and coefficient of friction

This paper presents the results of experimental tests of the efficiency of a single-stage worm gear. Two worm drives were used for testing, where the worms are made of improved steel 42CrMo4 and the worm gears are made of tin bronze CuSn12 and aluminium alloy A356. The values of the efficiency were determined at different values of revolutions and loads, where oils of different viscosities were used for lubrication. Determining the efficiency, the coefficient of friction of worm drives was calculated for experimental operating conditions, as well as the mass measurement of worm gears before and after testing. Based on the experimental results, depending on the operating mode and oil viscosity, the values of the efficiency of the worm drive made of the material 42CrMo4/CuSn12 are higher by 5 to 9 % compared to the worm drive 42CrMo4/A356. Higher values of the efficiency of the worm drive 42CrMo4/CuSn12 cause lower values of the coefficient of friction by 14 to 21 % as well as less wear of the worm gears.

Microstructure and mechanical properties of ultrasonic spot welding of AA7075-T6 and A380 casting aluminum alloy

Ultrasonic spot welding (USW) was employed to join AA7075-T6 and casting Al alloy A380. Under a constant welding power, the influence of the welding time duration (from 1 s to 3 s) on peak temperature, microstructure, hardness, and mechanical strength of the joints were studied. It was found that the peak temperature increased with welding time. A sound solid-state metallurgical bonding was obtained at the joint interface. The cracks occurred at the edge of the joints were eventually eliminated as the welding time increased. A layer of refined grains formed in A380 adjacent to the bonding line. Hardness reduction occurred in AA7075 at the joint interface and the degree of hardness reduction and the volume increased with the peak temperature. By increasing welding time, lap shear tensile tests show that the peak load increased from 5.3 kN to 6.55 kN. The corresponding interfacial shear strength ranged from 96.29 MPa to 99.72 MPa, lower than the shear strength of both base materials (331 MPa for AA7075 and 185 MPa for A380). All joint samples exhibited interfacial fracture after lap shear tensile testing, with a thin layer of A380 remnant attached to AA7075 at the center of the fractured surface.

Efficient Milling Quality Prediction with Explainable Machine Learning

This paper presents an explainable machine learning (ML) approach for predicting surface roughness in milling. Utilizing a dataset from milling aluminum alloy 2017A, the study employs random forest regression models and feature importance techniques. The key contributions include developing ML models that accurately predict various roughness values and identifying redundant sensors, particularly those for measuring normal cutting force. Our experiments show that removing certain sensors can reduce costs without sacrificing predictive accuracy, highlighting the potential of explainable machine learning to improve cost-effectiveness in machining.

Correction to: Wear Resistance of Aluminum Alloy A356 After Thorough Anodic Oxidation

Correction to: Wear Resistance of Aluminum Alloy A356 After Thorough Anodic Oxidation

Predictive optimization of surface quality, cost, and energy consumption during milling alloy 2017A: an approach integrating GA-ANN and RSM models

Predictive optimization of surface quality, cost, and energy consumption during milling alloy 2017A: an approach integrating GA-ANN and RSM models

Investigation of the Mechanical Properties and Microstructure of Graphene-Aluminium Alloy Composite Fabricated by Stir Casting Process

Mechanical properties of graphene nanoplatelets (GNPs) reinforced aluminum matrix composite fabricated by the semi-solid stir casting method were investigated. Aluminum alloy A356 is selected based on being widely used in automotive and aircraft industries. Recently, graphene has attracted wide attention from a scientific committee due to its outstanding properties. GNPs are an ideal reinforcement for nanocomposites' productions due to their excellent mechanical properties for strength enhancement. In this study, the effect of different weight fraction of GNPs content (0,0.3,0.5,1.0,and 1.5 wt.%) reinforced with A356 aluminum alloy was analysed. A 45-degree carbide impeller performed the stirring process of 500 rpm for 5 minutes. The samples were then characterised by microscopic examination, Vickers hardness, and tensile test Morphology of the fracture surface of the composite were observed using scanning electron microscopy..The microstructure revealed a homogenous distribution of nanoparticles in the matrix alloy. The composite exhibits improved mechanical properties, maximum tensile strength and hardness of 236MPa and 83 HV are obtained respectively. The composite has shown significant enhancement in the tensile and hardness which is 20% times higher than unreinforced A356 alloy. The hardness increased as the weight fractions of GNP in the A356 matrix has increased. However, when the content of GNPs used above 1.0 wt%, its tensile strength is reduced. Meanwhile, the fracture sample is ductile with a fine dimple structure. These findings may contribute to the process field of semi-solid stir casting, particularly on the GNPs addition to aluminium alloy as their primary material.

Wear Resistance of Aluminum Alloy A356 After Thorough Anodic Oxidation

Wear Resistance of Aluminum Alloy A356 After Thorough Anodic Oxidation

An integration of PSO-ANN and ANFIS hybrid models to predict surface quality, cost, and energy (QCE) during milling of alloy 2017A

An alarming pace of increase in worldwide energy consumption is being caused by population expansion and economic development, particularly in emerging market countries. Due to their efficiency and reproducibility in accomplishing high-precision machining, CNC machine tools are widely employed in most metal machining processes. The use of simple machining features to search for the assignment of cutting parameters and the machining process on the output variables is limited since a part, in reality, can contain complex interacting features. Therefore, this study focuses on pocket/groove features by integrating grey relational analysis (GRA) and hybrid PSO-ANN and ANFIS algorithms to optimize and predict surface quality, cost and energy consumption (QCE). Taking into account the population size of the swarm (pop) and the number of neurons (n) in the hidden layer, a parametric study was carried out to find the best prediction using the hybrid algorithm PSO-ANN. This study reported the highest trained correlation values (R2) for all output variables (greater than 0.97%). The study shows that the assignment of machining strategies and sequences on energy consumption can reach 99.25% between the minimum and maximum values. The mean square error (MSE) data demonstrates that the PSO-ANN model is effective. Indeed, an MSE improvement of 99.84%, 99.87%, and 97.62% has been demonstrated in terms of Etot, Ctot, and Ra, respectively, of the PSO-ANN model compared to ANFIS. This study reveals the potential of the PSO-ANN hybrid for multi-criteria prediction (quality, cost, and energy: QCE) by comparing it with the ANFIS model.

Prediction of QCE using ANN and ANFIS for milling Alloy 2017A

Population growth and economic development, particularly in developing market nations, are driving up global energy consumption at an alarming rate. Despite increased wealth, growing demand presents new obstacles. Computer Numerical Control (CNC) machine tools are widely used in most metal machining processes due to their efficiency and repeatability in achieving high-precision machining. It has been shown that figuring out the best cutting parameters can improve the results of machining, leading to high efficiency and low costs. This study identifies and examines thoroughly the scientific contributions of the influence of strategies, machining sequences, and cutting parameters on surface quality, machining cost, and energy consumption (QCE) using artificial intelligence (ANN and ANFIS). The results show that the 3.10−3 architecture with the Bayesian Regularization (BR) algorithm is the optimal neural architecture that yields an overall mean square error (MSE) of 2.74 10−3. The correlation coefficients ( R2) for Etot, Ctot, and Ra are 0.9992, 1, and 0.9117 respectively. Similarly, for the adaptive neuro-fuzzy inference system (ANFIS), the optimal structure which gives a better error and better correlation is the {2, 2, 2} structure, and this for the three output variables (Etot, Ctot, and Ra). The correlation coefficient ( R2) for the variables Etot, Ctot, and Ra are respectively 0.95, 0.965, and 0.968. The results show that the use of the Bayesian Regularization algorithm with a multi-criteria output response can give good results when compared with the adaptive neuro-fuzzy inference system.

Simulation and Optimization of the Auxiliary Cathode for Inter-Electrode Discharge Electric Field in Microarc Oxidation.

Currently, research on the edge effect issue in the micro-arc oxidation process primarily focuses on investigating process conditions and enhancing additives. However, some scholars have utilized finite element analysis software to simulate the edge effect during the simulation process, overlooking the investigation of the morphology of the auxiliary cathode. This study analyzes the growth characteristics of the oxide film on aluminum alloy 2A12 during micro-arc oxidation. Additionally, the inter-electrode discharge electric field is simulated using the finite element analysis method. The auxiliary cathode is optimized to mitigate the influence of the edge effect on the film layer. The findings indicate that employing a cylindrical shape as the auxiliary cathode instead of a rectangular groove leads to an increased thickness of the micro-arc oxidation film. However, it also results in an augmented length of the film layer affected by the edge effect at both ends of the workpiece. Decreasing the distance between the auxiliary cathode and the workpiece surface leads to a higher thickness of the obtained micro-arc oxidation film. Decreasing the length of the auxiliary cathode results in a reduction in both the thickness of the film layer on the workpiece surface and the area affected by the edge effect. Increasing the eccentric cone ratio of the auxiliary cathode enhances the uniformity of the micro-arc oxidation film layer. In this study, we present a novel auxiliary cathode model that incorporates a smaller cylindrical shell at the center and eccentric cone shells on each side. This model has the potential to enhance the optimization rate of the micro-arc oxidation film layer on cylindrical workpieces by 17.77%.