Study on Numerical Simulation of Mold Filling and Heat Transfer in Die Casting Process

A 3-D mathematical model considering turbulence phenomena has been established based on a computational fluid dynamics technique, so called 3-D SOLA-VOF (Solution Algorithm-Volume of Fluid), to simulate the fluid flow of mold filling process of die casting. In addition, the mathematical model for simulating the heat transfer in die casting process has also been established. The computation program has been developed by the authors with the finite difference method (FDM) recently. As verification, the mold filling process of a S-shaped die casting has been simulated and the simulation results coincide with that of the benchmark test. Finally, as a practical application, the gating design of a motorcycle component was modified by the mold filling simulation and the dies design of another motorcycle component was optimized by the heat transfer simulation. All the optimized designs were verified by the production practice.

Synergistic effects of composition and heat treatment on microstructure and properties of vacuum die cast Al-Si-Mg-Mn alloys

The purpose of this study was to prepare high-quality Al-Si-Mg-Mn alloy with a good combination of strength and ductility employing the vacuum-assisted high-pressure die cast process. An orthogonal study of heat treatments was conducted to design an optimized T6 heat treatment process for both Al-10%Si-0.3%Mg-Mn and Al-11%Si-0.6%Mg-Mn alloys. The results demonstrate that no obvious blisters and warpage were observed in these two alloys with solid solution treatment. After the optimal T6 heat treatment of 530°C×3 h + 165°C×6 h, Al-11%Si-0.6%Mg-Mn alloy has better mechanical properties, of which tensile strength, yield strength and elongation reached 377.3 MPa, 307.8 MPa and 9%, respectively. The improvement of mechanical properties can be attributed to the high density of needle-like β″(Mg_5Si_6) precipitation after aging treatment and the fine and spherical eutectic Si particles uniformly distributed in the α-Al matrix.

Microstructure,mechanical properties and first-principle analysis of vacuum die-cast Mg-7Al alloy with Sn addition

The influences of Sn element and heat treat-ment on the microstructure and mechanical properties of Mg-7Al alloy prepared by vacuum die cast(VDC)were studied.The results indicate thatα-Mg dendrite and Mg_(17)Al_(12) are refined and new Mg_(2)Sn phase is formed in Mg-7Al alloy with 2 wt%Sn addition.The ultimate tensile strength(σ_(b))of Mg-7Al alloy increases from 205 to 258 MPa(i.e.,a 25%increase).The mechanical properties of Mg-7Al-2Sn(AT72)alloy are further improved through heat treatment because of the dense microstructures processed by VDC.In particular,the mechanical properties of AT72 alloy are greatly improved after solution treatment at 400℃for 20 h due to solution strengthening of Al and Sn elements and precipitation strengthening of Mg_(2)Sn phases.The precipitation strengthening effect of particle Mg_(2)Sn phases is more apparent due to the decomposition of Mg_(17)Al_(12) phases.In addition,from the view of microscopic theory,the effect of Sn on mechanical properties of Mg-7Al alloy was discussed by first-principle calculation.

Grain Size Distribution and Interfacial Heat Transfer Coefficient during Solidification of Magnesium Alloys Using High Pressure Die Casting Process

The objective of this study is to predict grain size and heat transfer coefficient at the metal-die interface during high pressure die casting process and solidification of the magnesium alloy AM60. Multiple runs of the commercial casting simulation package, ProCASTTM, were used to model the mold filling and solidification events employing a range of interfacial heat transfer coefficient values. The simulation results were used to estimate the centerline cooling curve at various locations through the casting. The centerline cooling curves, together with the die temperature and the thermodynamic properties of the alloy, were then used as inputs to compute the solution to the Stefan problem of a moving phase boundary, thereby providing the through-thickness cooling curves at each chosen location of the casting, Finally, the local cooling rate was used to calculate the resulting grain size via previously established relationships. The effects of die temperature, filling time and heat transfer coefficient on the grain structure in skin region and core region were quantitatively characterized. It was observed that the grain size of skin region strongly depends on above three factors whereas the grain size of core region shows dependence on the interracial heat transfer coefficient and thickness of the samples. The grain size distribution from surface to center was estimated from the relationship between grain size and the predicted cooling rate. The prediction of grain size matches well with experimental results. A comparison of the predicted and experimentally determined grain size profiles enables the determination of the apparent interracial heat transfer coefficient for different locations.

Effects of Mg Enhancement and Heat Treatment on Microstructures and Tensile Properties of Al2Ca-Added ADC12 Die Casting Alloys

The effects of Mg enhancement and heat treatment on the microstructures and tensile properties of Al_2Ca-added ADC12 die casting alloys were investigated. 0.3% and 0.5% Mg in the form of a master alloy including a trace amount of Al_2Ca were added to conventional ADC12（383 and AlSi10Cu2Fe） alloy with an initial Mg-content of 0.3% to increase the Mg content to 0.6% and 0.8%, respectively. To avoid heat treatmentinduced surface blisters, shortened solution treatment for 15 min at 490 ℃ and artificial aging for 6 h at 150 ℃ was undertaken. The results show that a 10% improvement in the shape factor of eutectic Si particles was achieved for Al_2Ca-added ADC12 with 0.8% Mg compared to the conventional ADC12 in the as-aged condition. Al_2Ca-added ADC12 with 0.8% Mg exhibited a yield strength of 289 MPa, a tensile strength of 407 MPa, and an elongation of 4.22%.

Modeling effects of alloying elements and heat treatment parameters on mechanical properties of hot die steel with back-propagation artificial neural network

Materials data deep-excavation is very important in materials genome exploration.In order to carry out materials data deep-excavation in hot die steels and obtain the relationships among alloying elements,heat treatment parameters and materials properties,a 11×12×12×4 back-propagation（BP）artificial neural network（ANN）was set up.Alloying element contents,quenching and tempering temperatures were selected as input;hardness,tensile and yield strength were set as output parameters.The ANN shows a high fitting precision.The effects of alloying elements and heat treatment parameters on the properties of hot die steel were studied using this model.The results indicate that high temperature hardness increases with increasing alloying element content of C,Si,Mo,W,Ni,V and Cr to a maximum value and decreases with further increase in alloying element content.The ANN also predicts that the high temperature hardness will decrease with increasing quenching temperature,and possess an optimal value with increasing tempering temperature.This model provides a new tool for novel hot die steel design.