In order to achieve high cycle time in die casting process, high measurements accuracy of die cooling by lubricant spray is important. Therefore, a die lubricant spray experiment has been implemented with a heated die block.
  Temperature distribution near the die block surface has been measured by thermocouples, and distribution of lubricant/block head transfer coefficient in spray spot has been calculated based on the experiment. With the experiment, spray cooling models for casting CAE have been proposed. The models consist of one spray model and two spray models in which spray guns lubricant applied at the same time. Using the proposed models, lubricant spray simulation was carried out. The content of the experiment was that the simulated temperature curves were compared with actually measured temperature curves. As a result, the simulated curves agreed well with actually measured temperature curves.

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  The effects of C on continuous cooling transformation behavior and heat treatment characteristics were studied by using three types of flake graphite cast iron containing 2.6mass%C to 3.6%C. Austenitizing was done at 1223 K-900 s and 1323 K-900 s respectively. All of the ferrite, pearlite and martensite transformation regions were observed in the CCT diagrams of these three cast irons and at both austenitizing temperatures. On the other hand, cementite and bainite transformation regions were not seen. Effects of C on continuous cooling transformation behavior were slight, due to little change in C content in the matrix of each cast iron. The start of pearlite transformation temperature was higher than that of ferrite in each CCT diagram for the three cast irons and two austenitizing temperatures. The hardenability curves for the three cast irons decreased with increasing C content or increasing austenitizing temperature. Carbon did not affect the hardenability of flake cast iron. The effects of C on continuous cooling transformation behavior and heat treatment characteristics of low alloyed flake graphite cast iron were found to resemble those of spheroidal graphite cast iron.

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  The thermal expansion coefficient of 35mass%Ni austenite cast iron is 3.0×10^-6/K to 4.0×10^-6/K and becomes larger in three times than that of Inver alloy. Therefore, we first discuss the influence of carbon content on the thermal expansion coefficient using the carburized samples, and then, the effect of Ni segregation using the cast samples with different graphite morphology. In addition, the influence of the cooling rate, namely nickel segregation distance, on the thermal expansion coefficient is investigated by changing the thickness of the cast samples.
  As the result, the influence of carbon on the thermal expansion coefficient is not so significant. Spheroidal graphite iron is not suitable for annealing due to the large segregation distance. In addition, the thermal expansion coefficient of thin cast sample decreases faster than that of the thick one by annealing. The thermal expansion coefficient of 35mass%Ni austenite cast iron can be decreased to 2.0×10^-6/K, by fully annealing to decrease in the Ni segregation, regardless of the addition of Co.

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  Mold-filling simulation has been used in foundries for the prediction of casting defects. However, the optimization of gating designs or casting conditions for decreasing the casting defects is one of the most difficult and important problems. In the present study, we proposed an evaluation formula to quantitatively evaluate the casting defects caused by cold shut, which causes reduced casting quality. We confirmed the propriety of the criterion by applying it to a practical casting problem. Through the comparison of numerical results and experimental data, it was found that we can qualitatively estimate the feasibility of cold shut occurrence by using the proposed evaluation formula in mold-filling simulation.
  Furthermore, we attempted the multi-objective optimization of injection speed to decrease casting defects induced by cold shut and air inclusion. As the objective function for optimization, we used the proposed criterion and the volume rate of air inclusion entrapped in cavities, and a genetic algorithm was adopted to consider the high nonlinearity of the hydrodynamic behavior of molten metal. Optimization was carried out by the integration of an optimization tool into a casting simulation program, and we succeeded in achieving a pareto set within five days by using a multi-processor machine.

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