Prediction method for dendritic crystal growth in static molten steel based on parallel computing
A technology of parallel computing and prediction method, applied in the field of metallurgical continuous casting, can solve problems such as waste of computing resources, low efficiency, time-consuming efficiency, etc., and achieve the effects of improving computing efficiency, reducing computing time, and avoiding high costs
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[0063] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.
[0064] In this embodiment, the method for predicting dendrite growth in static molten steel based on parallel computing of the present invention is used to predict the dendrite growth of a low-carbon peritectic steel sample in a steel plant during the production process. like figure 1 Shown, the prediction method of dendrite growth in the standing molten steel based on parallel computing of the present invention, comprises the following steps:
[0065] Step 1: Collect physical property parameters and proportion data of each component of the steel to be studied; the physical property parameters include liquidus slope, melting point temperature, and molar volume.
[0066] In this embodiment, the carbon content of the low-carbon peritectic steel sample is 0.83 at.%, and the pseudo-binary phase diagram of the steel sample is as follows Figure 4 ...
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