シャ　キンカ   Jinhua She   佘　錦華    所属   工学部 機械工学科    職種   教授
言語種別	英語
発行・発表の年月	2018/01
形態種別	学術論文
査読	査読あり
標題	Optimization of coke ratio for the second proportioning phase in a sintering process base on a model of temperature field of material layer
執筆形態	共著
掲載誌名	Neurocomputing
掲載区分	国外
出版社・発行元	Elsevier
巻・号・頁	275,pp.10-18
担当範囲	All
著者・共著者	Min Wu, Junjie Ma, Jie Hu, Xin Chen, Weihua Cao, and Jinhua She
概要	Coke ratio for a sintering process is often determined by experience because models of calculating a coke ratio are very complicated, and are hard to be used in practice. This paper presents a three-step optimization method to find a coke ratio that meets the requirements for commercial operations. First, a back-propagation neural network (BPNN) for temperature field of the material layer (TFML) is built to calculate a mass of sinter cake of a sintering process. Then, the energy flow in a sintering process is analyzed, and a theoretical value of the coke ratio is calculated. Finally, the optimization problem for the second portioning phase is formulated that takes into consideration of the conventional constraints, such as material balance, chemical composition, required quality, etc., and a coke ratio constraint based on the theoretical value. This benefits the reduction of CO2 for the sintering process. Numerical verification has shown the validity of the method.
外部リンクURL	https://www.sciencedirect.com/science/article/pii/S0925231217308056#