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Determination of temperature difference in squeeze casting hot work tool steel

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Abstract

The effects of process parameters on temperature difference (ΔTRECS) of the squeeze casting part were studied by employing artificial neural network (ANN) and Procast software when cooling up to recrystallization temperature, such as interface heat transfer coefficient of metal/cavity die (h1), applied pressure (Ap), interface heat transfer coefficient of metal/male die (h2), die pre-heat temperature (Dt) and pouring temperature (Pt). An ANN model on the relationship between the processing parameters and ΔTRECS was constructed. The test results on performance of the trained network show that the ANN model can predict ΔTRECS with reasonable accuracy. Employing the ANN model the following conclusions could be made from this work: as far as the influence of process parameters on ΔTRECS are concerned, the most important and the secondary parameter are Dt and Ap. H1 and Ap increase within a certain range, ΔTRECS are found to increase. When Ap and h1 are above their respective critical point, the ΔTRECS decreased rapidly. Pt, h2 and Dp increase within a certain range, ΔTRECS are found to decrease.

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Acknowledgment

The work was supported by the Science Fund of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body (30815004).

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Correspondence to Rong Ji Wang.

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Wang, R.J., Zeng, J. & ZHOU, Dw. Determination of temperature difference in squeeze casting hot work tool steel. Int J Mater Form 5, 317–324 (2012). https://doi.org/10.1007/s12289-011-1061-8

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  • DOI: https://doi.org/10.1007/s12289-011-1061-8

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