Method for casting grain structure numerical value prediction

A numerical prediction and organization technology, applied in complex mathematical operations, electrical digital data processing, special data processing applications, etc., can solve problems such as large amount of calculation and long calculation time

Inactive Publication Date: 2016-06-15
HARBIN UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention aims to solve the problems of long calculation time an

Method used

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  • Method for casting grain structure numerical value prediction
  • Method for casting grain structure numerical value prediction
  • Method for casting grain structure numerical value prediction

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specific Embodiment approach 1

[0043] A method for numerical prediction of casting grain structure, characterized in that it comprises:

[0044] Step 1. Solve the KGT (Kurz-Giovanole-Trivedi) model of dendrite growth kinetics to obtain the dendrite tip radius-dendrite tip growth rate change curve;

[0045] The KGT model is a nonlinear model, which is solved by an iterative algorithm. The specific process is as follows:

[0046] Step 1 (1), set the change range of the melt supercooling degree, increase from 0°C to 10°C, increase 0.1°C each time, the melt supercooling degree changes 100 times, for the ti-th calculation, the melt supercooling degree is defined as ΔT all [ti], 1≤ti≤100;

[0047] Step 1 (2), when the melt subcooling degree is ΔT all When [ti], set the total number of iterative calculations to NI; set an iterative calculation to ni, and 1≤ni≤NI;

[0048] When performing the iterative calculation of the nith time, the iterative solution order of the equations in the KGT model is:

[0049] ...

specific Embodiment approach 2

[0070] The specific process of step five described in this embodiment is as follows:

[0071] Step five (1), calculate the energy conservation equation:

[0072] h s =c pL T

[0073] h l =c pL T+ΔH

[0074] [H]=f s h s +(1-f s )h l

[0075] ∂ [ H ] ∂ t + ▿ · ( f l U l h l ) = λ l ▿ · ( ▿ T )

[0076] where: h s and h l Respectively solid phase and liquid phase enthalpy (J / kg), c pL is the specific heat of liquid (J / kgK), λ l is the liquid thermal conductivity (W / m K), ΔH is the latent heat of crystallization (J / kg), f s ...

specific Embodiment approach 3

[0092] The specific process of step five (four) described in the present embodiment is as follows:

[0093] search computation grid(i, j) chan＝0 Left, right, top, and bottom four grids, respectively (i-1, j) chan＝0 , (i+1,j) chan＝0 , (i, j+1) chan＝0 and (i,j-1) chan＝0 , examine f s value;

[0094] if 0 s [i,j]s [i+1, j]=0, the label is (i, j) chan＝0 It is at the front of solidification, and the solidification direction is from left to right. flag[i,j]=1;

[0095] if 0 s [i,j]s [i-1, j]=0, the label is (i, j) chan＝0 At the front of solidification, the solidification direction is from right to left, flag[i,j]=1;

[0096] if 0 s [i,j]s [i, j+1]=0, the label is (i, j) chan＝0 It is at the front of solidification, and the solidification direction is from bottom to top. flag[i,j]=1;

[0097] if 0 s [i,j]s [i, j-1]=0, the label is (i, j) chan＝0 It is at the front of solidification, and the solidification direction is from top to bottom. flag[i,j]=1;

[0098...

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Abstract

The invention provides a method for casting grain structure numerical prediction, and relates to a prediction method of a casting grain structure. The method aims at solving the problems that in existing grain structure numerical prediction, the calculation time is long and the calculation amount is large. The method includes the steps of calculating a dendritic crystal growth kinetics KGT model first, obtaining the dendritic crystal tip radius-dendritic crystal tip growth speed change curve, conducting macro-scale mesh generation on a casting system, only calculating an energy conservation equation for a computational grid (i,j)chan=/0 to obtain temperature field distribution, calculating a momentum conservation equation for a computational grid (i,j)chan=0 to obtain the metal liquid flowing speed in the computational grid, judging whether the computational grid (i,j)chan=0 is located on the solidification front or not, calculating the solidification front temperature gradient and the solidification front movement speed corresponding to the grid if yes, and outputting distribution of a grain growth morphology identification grain in a casting till solidification ends. The method is suitable for casting grain structure numerical prediction.

Description

technical field [0001] The invention relates to a method for predicting the grain structure of a casting. Background technique [0002] The pros and cons of casting mechanical properties and the length of service life mainly depend on the grain structure formed during the solidification process of castings. Castings with different performances require different grain structures. For example, casting blades require the solidified grain structure to be completely columnar grain growth, the purpose is to reduce the possibility of blade creep under high temperature working conditions; automobile engines, automobile hubs, automobile engines Castings such as covers require that the solidified grain structure is completely equiaxed grain growth, the purpose is to increase the strength of the casting, improve the filling performance, and finally reduce the possibility of hot tearing of the casting during use. In order to ensure that the casting has uniform mechanical properties, ac...

Claims

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Application Information

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IPC IPC(8): B22D27/04G06F17/50G06F17/11
CPCB22D27/04G06F17/11G06F30/367
Inventor 刘东戎杨洋王坦郭二军
Owner HARBIN UNIV OF SCI & TECH
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