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Development and Application of Prediction Model for End-point Manganese Content in Converter Based on Data from Sub-lance Zhang Bo1,a, Xue Zheng-liang1; Liu Ke1, Xiao Wen-bin2 1Hubei Wuhan Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of Education, Wuhan University of Science and Technology, 430081, China; 2Hubei Wuhan Wuhan Iron and Steel Group Corp; 430083, China atale-2002@163.com Keywords: End-point of Converter; Sub-lance; Prediction of Manganese Content; Multiple Linear Regression; BP Neural Network Abstract: Base on smelting data from converter sub-lance in a factory, the prediction models for end manganese content in converter were established by Multiple Linear Regression (MLR) and BP Neural Network (BP-NN) respectively.
Material conditions: weight of molten iron, temperature of molten iron, weight of scrap steel, carbon content of molten iron, manganese content of molten iron, silicon content of molten iron and phosphorus content of molten iron.
3 Multiple Linear Regression (MLR) model 3.1 structure of MLR model MLP prediction model for end manganese content in converter was established on basis of conditions of materials, blowing and dynamic control, whose general formulae is as follows.
Author: ZHANG Bo, Doctoral candidates; Tel: +86-13971092849; Email:tale-2002@163.com References [1] LIU Kun, LIU Liu．End Point Phosphorus and Manganese Content Control Model Based on Sublance Technique and Optimization of Dephosphorization Process[J]．Iron and Steel, 2008,43(7): 32-36 [2] XU Hui, Li Xu．Prediction model of phosphorus content in molten steel based on BP neural network [J]．Journal of Anshan University of Science and Technology, 2007,30(2): 128-131 [3] XUE zheng-liang, WU Li-jia．Research on factors affecting residual manganese content and its yield in the end-point hot metal of converter [J]．Steelmaking, 2011,27(6): 40~43 [4] XU Na, ZHAO Bu-hui．Development of a Prediction Model for BOF End Manganese Content [J]．Journal of Jiangsu University of Science and Technology, 2001(22): 47-51 [5] Michitaka, K, Hiroshi Y, Tooru Y, et al.

According to different sub-positions and different number of chlorine atoms, 209 similar chemical compositions, this could be used to industrial raw material and main components of herbicide.
Materials and Methods The detection method for PCBs.
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Brooks and Corey model is developed based on Corey’s model combined with modified Burdine’s model. in BC model as in Table 1 is the pore size distribution index whose value depends on type of material.
According to [10], for heterogeneous material and for homogeneous material.
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In the model shown in Figure 1, the parameters of substrate as follows :E=200GPa, Poisson's ratio =0.29 [9], The material parameters of the TiN coating [10] are as follows: elastic modulus E=590GPa, Poisson's ratio =0.21; The following [9] diamond material parameters: elastic modulus 1140GPa, Poisson's ratio is 0.007, the hardness is 80 GPa, alternative analytical rigid body in the simulation.
The Hertzian contact cracks show that single material contact crack first appears in the contact surface, and then, the crack will extend to the contact body.
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A Numerical Model for Evaluating the Casting Complex Degree Shiping Wu 1, a, Qin Xu 1,b, Xiang Xue 1,c and Guangran Wu2,d 1School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China 2Shoudu Space Machinery Company, Beijing 100076, China aspwu@hit.edu.cn, bxuqin_hit@163.com, cxxue@hit.edu.cn, dsmart_78@163.com Keywords: Castings; Tissues; Complexity Degree; Quantitative Description; Surface Modulus.
ACKNOLEDGEMENT The authors would like to thank the National Natural Science Foundation of China (Grant No. 50775050) and the State Key Laboratory of Solidification Processing in NWPU (200702).
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Decrease in grain size decreases the micro hardness value of processed materials. 3.
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Khoury, Effect of fire on concrete and concrete structures, Progress in Structural Engineering and Materials. 2 (4) (2000) 429-447
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Beke 1,b 1 University of Debrecen, Department of Solid State Physics, H-4010 Debrecen P.O.Box2, Hungary 2 University of Debrecen, Medical and Health Science Centre, Institute of Dental Science, Department of Prosthetic Dentistry, H-4012 Debrecen Nagyerdei krt. 98, Hungary a ldaroczi@tigris.klte.hu, bdbeke@delfin.klte.hu,chegedus@jaguar.unideb,hu, d kokenyesi@jaguar.unideb.hu Keywords: Diffusion bonding, metal ceramic bonding, solid-state reaction, dental materials Abstract.
Wide scale of materials was investigated by cross-sectional TEM (CTEM) technique and microdiffraction methods.
When ceramic is present on the surface the cavities are filled up with the material of the porcelain's glassy phase by grain-boundary diffusion through the oxide layer.
Ni-Cr material after heat treatment without ceramic 0 2 4 6 8 10 C Mo Ni Al Na Cu Ni Co Cu Si Ni K K Cr Cr I(a.u.)
Beke, Journal of Dental Research 81/5, (2002) p334

Experiments Raw material and properties.Gas atomized 316L stainless steel powder provided by Zhong-wu material Co., Ltd., China was used in the experiments.
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Acknowledgements This work was financially supported by the Tangshan Science and Technology Bureau project(12140201A-2 ).
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