摘要
The bonding of solid steel plate to liquid al uminum was studied using rapid solidification. The relationship models of interf acial shear strength and thickness of interfacial layer of bonding plate vs bond ing parameters (such as preheat temperature of steel plate, temperature of alumi num liquid and bonding time) were respectively established by artificial neural networks perfectly.The bonding parameters for the largest interfacial shear stre ngth were optimized with genetic algorithm successfully. They are 226℃ for preh eating temperature of steel plate, 723℃ for temperature of aluminum liquid and 15.8s for bonding time, and the largest interfacial shear strength of bonding pl ate is 71.6 MPa . Under these conditions, the corresponding reasonable thickne ss of interfacial layer (10.8μm) is gotten using the relationship model establi shed by artificial neural networks.
The bonding of solid steel plate to liquid al uminum was studied using rapid solidification. The relationship models of interf acial shear strength and thickness of interfacial layer of bonding plate vs bond ing parameters (such as preheat temperature of steel plate, temperature of alumi num liquid and bonding time) were respectively established by artificial neural networks perfectly.The bonding parameters for the largest interfacial shear stre ngth were optimized with genetic algorithm successfully. They are 226℃ for preh eating temperature of steel plate, 723℃ for temperature of aluminum liquid and 15.8s for bonding time, and the largest interfacial shear strength of bonding pl ate is 71.6 MPa . Under these conditions, the corresponding reasonable thickne ss of interfacial layer (10.8μm) is gotten using the relationship model establi shed by artificial neural networks.
基金
Funded by the National Natural Science Foundation of China(No.50274047 and 50304001)
the Foundation of Ministry of Edu cation of China
and the Foundation of Bejing Jiaotong University
