Simulation on the Performance of Ceramic-Lined Steel Pipe Prepared by SHS Process Based on Artificial Neural Network

Y. Zhu, Yuxi Ge, F. Huang, Hongjun Ni
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Abstract

In order to study the relationship between reaction recipe and the performance of ceramic-lined steel pipe prepared by SHS process, 21 groups data obtained in the experiment were used. the different reaction recipes were taken as input data. Besides, the crushing strength and the density of ceramic layer were taken as output data. the BP neural network model was established to simulate the performance of ceramic lined composite steel pipe under different reaction recipes. Simulation results show that: the use of BP neural network simulation of ceramic lined composite tube crushing strength and the density of the steel pipe ceramic layer maximum error of 2.6742% and 4.8445%.It meets the needs in the engineering.
基于神经网络的SHS法制备陶瓷内衬钢管性能仿真研究
为了研究SHS法制备陶瓷内衬钢管的反应配方与性能之间的关系,采用了21组实验数据。以不同的反应配方作为输入数据。并以破碎强度和陶瓷层密度作为输出数据。建立BP神经网络模型,模拟不同反应配方下陶瓷内衬复合钢管的性能。仿真结果表明:利用BP神经网络模拟陶瓷内衬复合管的破碎强度和钢管陶瓷层密度的最大误差分别为2.6742%和4.8445%。满足工程上的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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