Ultra-large aluminum shape casting:Opportunities and challenges

Ultra-large aluminum shape castings have been increasingly used in automotive vehicles,particularly in electric vehicles for light-weighting and vehicle manufacturing cost reduction.As most of them are structural components subject to both quasi-static,dynamic and cyclic loading,the quality and quantifiable performance of the ultra-large aluminum shape castings is critical to their success in both design and manufacturing.This paper briefly reviews some application examples of ultra-large aluminum castings in automotive industry and outlines their advantages and benefits.Factors affecting quality,microstructure and mechanical properties of ultra-large aluminum castings are evaluated and discussed as aluminum shape casting processing is very complex and often involves many competing mechanisms,multi-physics phenomena,and potentially large uncertainties that significantly influence the casting quality and performance.Metallurgical analysis and mechanical property assessment of an ultra-large aluminum shape casting are presented.Challenges are highlighted and suggestions are made for robust design and manufacturing of ultra-large aluminum castings.

Development of viscosity model for aluminum alloys using BP neural network

Viscosity is one of the important thermophysical properties of liquid aluminum alloys,which influences the characteristics of mold filling and solidification and thus the quality of castings.In this study,315 sets of experimental viscosity data collected from the literatures were used to develop the viscosity prediction model.Back-propagation(BP)neural network method was adopted,with the melt temperature and mass contents of Al,Si,Fe,Cu,Mn,Mg and Zn solutes as the model input,and the viscosity value as the model output.To improve the model accuracy,the influence of different training algorithms and the number of hidden neurons was studied.The initial weight and bias values were also optimized using genetic algorithm,which considerably improve the model accuracy.The average relative error between the predicted and experimental data is less than 5%,confirming that the optimal model has high prediction accuracy and reliability.The predictions by our model for temperature-and solute content-dependent viscosity of pure Al and binary Al alloys are in very good agreement with the experimental results in the literature,indicating that the developed model has a good prediction accuracy.

Effect of Ce on castability,mechanical properties and electric conductivity of commercial purity aluminum

Effects of Ce addition on microstructure, castability （fluidity and hot tearing sensitivity）, mechanical properties and electric conductivity of commercial purity aluminum （CP-AI） were investigated through microstructure observation and performance tests. Results show that adding Ce in a CP-AI can considerably refine the grains, and has an important influence on the amount, crystallographic forms, and distribution of secondary phases. Addition of Ce also has a large impact on the fluidity and hot tearing sensitivity （HTS） of the CP-AI. With the addition of Ce from 0.1wt.% to 0.5wt.%, the fluidity of CP-AI is first increased remarkably and then decreased, and the HTS has an opposite response. The best castability of the studied alloys appears to be at 0.2wt.%-0.3wt.% Ce addition. The remarkable improvement in castability is attributed to the considerable refinement of grain structure. Ce addition can also lead to a significant rise in electric conductivity. The maximum conductivity of the as-cast CP-Al is 59.7% IACS with an addition of 0.2wt.%Ce. The T7 heat treatment can further improves the conductivity to 60.7% IACS. The Ce-induced evolution of the secondary phases is believed to be the mechanism for it.

Microstructure and mechanical properties of lost foam cast 356 alloys

Microstructure and mechanical properties of lost foam cast aluminum alloys have been investigated in both primary A356(0.13% Fe) and secondary 356(0.47%). As expected, secondary 356 shows much higher content of Fe-rich intermetallic phases, and in particular the porosity in comparison with primary A356. The average area percent and size(length) of Fe-rich intermetallics change from about 0.5% and 6 μm in A356 to 2% and 25 μm in 356 alloy. The average area percent and maximum size of porosity also increase from about 0.4% and 420 μm to 1.4% and 600 μm, respectively. As a result, tensile ductility decreases about 60% and ultimate tensile strength declines about 8%. Lower fatigue strength was also experienced in the secondary 356 alloy. Low cycle fatigue(LCF) strength decreased from 187 MPa in A356 to 159 MPa in 356 and high cycle fatigue(HCF) strength also declined slightly from 68 MPa to 64 MPa.

Quantitative microstructure and fatigue life of B319 casting alloys

In this study, the microstructure of B319 casting alloys and effects of five different casting conditions on microstructure were studied. Multi-scale microstructure was quantified in terms of secondary dendrite arm spacing （SDAS）, and Si particle size and aspect ratio. The effects of SDAS, Si aspect ratio and size on fatigue life were analyzed. The results indicate that the size and aspect ratio of Si particles are a function of SDAS which is dependent on cooling rate during solidification. The fatigue life decreases with SDAS increasing as SDAS is smaller than 30 pm while it increases with SDAS increasing as SDAS is larger than 60 ~tm. In addition, the fatigue life decreases with Si aspect ratio and size increasing at the same SDAS. Moreover, SDAS and Si particles have also influence on fatigue fracture, such as the area of cracks propagation region and the roughness of fatigue fracture. The cracks propagation area is smaller, and the fatigue fracture is similar to tensile fracture with larger SDAS. Besides, the longitudinal section of fatigue fracture is rougher with large SDAS and elongated Si particles.