2018
DOI: 10.1051/matecconf/201817806012
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Prediction of thermal field dynamics of mould in casting using artificial neural networks

Abstract: Manufacturing a large number of cast parts made of aluminium alloy led to an increased interest in developing and applying new control techniques of the casting process. Anyway, the difficulty in estimating some important process parameters only allowed the use of some approaches which are limited to a few geometric models. Many researchers made great efforts to find the best method for monitoring and measuring thermal field dynamics of the cast and mould during solidification and cooling of the melt alloy. Ac… Show more

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Cited by 5 publications
(2 citation statements)
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“…Typically, programs are built on finite element or finite element methods [9][10][11][12][13][14]. However, these methods require the precise setting of boundary conditions, one of which is again the surface temperature of the casting.…”
Section: The History Of the Development Of Methods For Calculating Th...mentioning
confidence: 99%
“…Typically, programs are built on finite element or finite element methods [9][10][11][12][13][14]. However, these methods require the precise setting of boundary conditions, one of which is again the surface temperature of the casting.…”
Section: The History Of the Development Of Methods For Calculating Th...mentioning
confidence: 99%
“…Almost all researchers agree on the importance of the comprehensive assessment of the thermal felds of the "casting-mold" system [30]. Tis is also relevant from the point of view of the creation and widespread use of new environmentally friendly materials for foundry molds, such as orthophosphates and pyrophosphates of silicon and zirconium [31], meta-phosphates and pyrophosphates of sodium [32], as well as binders synthesized from various aluminum-containing compounds [33], thermophysical properties of which difer from previously known ones.…”
Section: Introductionmentioning
confidence: 99%