吉林大学学报(工学版) ›› 2001, Vol. ›› Issue (4): 27-32.

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Application of Genetic Algorithm to Composition Optimum in Multicomponent Cu-base Filler Meter

QIU Xiao-ming1, ZHANG Li2, REN Lu-quan2, LI Jian-qiao 2   

  1. 1. College of Material Science & Engineering, Jilin University, Changchun 130025, China;
    2. Key Lab of Terrain-Machinery Bionics Engineering, Education Minist, Jilin University, Changchun 130025, China
  • Received:2001-02-12 Online:2001-10-25

Abstract: The wettability and shearing strength for CuZn filler meters brazing white east iron are lower than those of CuZn filler meters brazing steel. The erosion of white cast iron over-dissolving into filler meters is the main cause of the reduction of the wettability and shearing strength. By means of the quadratic regression composition design process, the regression equations between wettability, mechanical property and elements are established. The influence of the elements on the wettability and shearing strength is also analysed. The multiparameters optimization and solution for the wettability and shearing strength on the multicomponent Cu-base filler meter are studied by Genetic Algorithm. The study has proved that the optimal contents and properties used for brazing white cast iron can be obtained by Genetic Algorithm.

Key words: genetic algorithm, Cu-base filler meter, optimization

CLC Number: 

  • TG425
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