APPLICATION OF TEMPERATURE FIELD SIMULATION AND ARTIFICIAL NEURAL NETWORK FOR DESIGN OF NONQUENCHED PREHARDENED STEELS FOR LARGE MOLDS FOR PLASTICS

作者：Luo, Yi^*; Wu, Xiao-chun

来源：Metal Science and Heat Treatment, 2012, 54(7-8): 360-367.

DOI：10.1007/s11041-012-9513-4

• prehardened steel for large molds for casting plastics
• nonquenched steels
• simulation of temperature fields
• artificial neural network
• design of chemical composition

Translated from Metallovedenie i Termicheskaya Obrabotka Metallov, No. 7, pp. 38 - 45, July, 2012. The suggested model for designing nonquenched prehardened steels for large molds for plastics combines simulation of temperature fields and computation of hardness on the basis of an artificial neural network (ANN). The temperature field is simulated for round steel preforms from 400 to 700 mm in diameter and up to 10 tons in mass. The ANN is introduced into the design model for analyzing and simulating the relation between the chemical composition and the hardness of alloyed steels cooled at a rate of 0.5, 0.3, 0.05, and 0.03 K/sec. The suggested model is used to develop two chemical compositions for preforms from prehardened steels for casting plastics. The preforms have been tested in production of commercial articles.

• 出版日期2012-11
• 单位上海大学