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Abstract

A comprehensive understanding of melt quality is of paramount importance for the control and prediction of actual casting characteristics. Among many phenomenon that occur during the solidification of castings, there are four that control structure and consequently mechanical properties: chemical composition, liquid metal treatment, cooling rate and temperature gradient. The cooling rate and alloy composition are most important among them. This paper investigates the effect of the major alloying elements (silicon and copper) of AlSi-Cu alloys on the size of secondary dendrite arm spacing. It has been shown that both alloying elements have reasonable influence on the refinement of this solidification parameter
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Abstract

The quality of the squeeze castings is significantly affected by secondary dendrite arm spacing, which is influenced by squeeze cast input parameters. The relationships of secondary dendrite arm spacing with the input parameters, namely time delay, pressure duration, squeeze pressure, pouring and die temperatures are complex in nature. The present research work focuses on the development of input-output relationships using fuzzy logic approach. In fuzzy logic approach, squeeze cast process variables are expressed as a function of input parameters and secondary dendrite arm spacing is expressed as an output parameter. It is important to note that two fuzzy logic based approaches have been developed for the said problem. The first approach deals with the manually constructed mamdani based fuzzy system and the second approach deals with automatic evolution of the Takagi and Sugeno’s fuzzy system. It is important to note that the performance of the developed models is tested for both linear and non-linear type membership functions. In addition the developed models were compared with the ten test cases which are different from those of training data. The developed fuzzy systems eliminates the need of a number of trials in selection of most influential squeeze cast process parameters. This will reduce time and cost of trial experimentations. The results showed that, all the developed models can be effectively used for making prediction. Further, the present research work will help foundrymen to select parameters in squeeze casting to obtain the desired quality casting without much of time and resource consuming.
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