A Method for Analyzing Interdiffusion Coefficient of Multicomponent Melts
A technology of interdiffusion coefficient and analysis method, applied in the field of global optimization algorithm, can solve problems such as poor versatility, error, and low data quality and accuracy
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example 1
[0054] Example 1: Through formula (2), we can pre-select a set of optimization parameters a and the corresponding isothermal diffusion time t to obtain the corresponding diffusion component spectrum. Then, the algorithm of the present invention is used to analyze these preset component spectra to obtain the corresponding optimal solution, and the reliability of the algorithm is judged by comparing the optimal solution with the preset value.
[0055] Table 1 gives our preset optimization parameter a, figure 1 The discrete points in represent the diffusion component spectrum generated by these preset optimization parameters, and the composition of the selected diffusion couple is: A 75 B 8 C 17 -A 65 B 12 C 23 , the corresponding mean composition is A 70 B 10 C 20 , isothermal diffusion time t = 1600s, the number of selected experimental points N = 50.
[0056] Utilize the present invention to carry out the step of solving example 1 and comprise:
[0057] Step 1. Use t...
example 2
[0103] Example 2: In order to be closer to the real diffusion process, we added a random error in the range of ±1 (at.%) to the diffusion component spectrum generated by the preset optimization parameters, and the resulting diffusion component spectrum Such as figure 2 The discrete points in are shown. According to the obtained component spectrum, the objective function can also be constructed according to formula (1).
[0104] The calculation steps of Example 2 are exactly the same as those of Example 1, the difference is only in the following two points:
[0105] (1), according to figure 2 For the diffusion concentration data shown, the value ranges of the 9 genes in this example are: [10.0±5.0,20.0±5.0,0.0±100.0,0.0±100.0,0.0±100.0,0.0±100.0,10 (0±2.0) ,10 (0±2.0) ,25.0±5.0,];
[0106] (2), the value of the error control parameter η of L-M algorithm is taken as 10 in this example -4 , ie η=10 -4 ;
[0107] The global optimal solution obtained by this algorithm is ...
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