Electrical Conductivity Calculation of Molten Multicomponent Slag by Neural Network Analysis

Yusuke HARAGUCHI; Masashi NAKAMOTO; Masanori SUZUKI; Kiyoshi FUJI-TA; Toshihiro TANAKA

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Electrical Conductivity Calculation of Molten Multicomponent Slag by Neural Network Analysis

机译：神经网络分析计算熔渣多组分电导率

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Only a few models for estimating electrical conductivity of molten slag have been developed, which are limited to systems with certain types of components. In this study, a new method for estimating the electrical conductivity of molten slag through neural network calculations is proposed and is compared with previous estimation approaches. The present estimation approach can reproduce the electrical conductivity of molten slag composed of SiO_2, CaO, MgO, MnO, Al_2O_3, FeO, Fe_2O_3, and Na_2O to an uncertainty of 30%. We found that the neural network calculation is applicable to various kinds of molten slag over wider mole fraction and temperature ranges than conventional models.

机译：仅开发了几种估计熔渣电导率的模型，这些模型仅限于具有某些类型组件的系统。在这项研究中，提出了一种通过神经网络计算估算熔渣电导率的新方法，并将其与以前的估算方法进行了比较。该估计方法可以将由SiO_2，CaO，MgO，MnO，Al_2O_3，FeO，Fe_2O_3和Na_2O组成的熔渣的电导率再现到30％的不确定度。我们发现，与传统模型相比，神经网络计算适用于在更大的摩尔分数和温度范围内的各种熔渣。

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来源
《ISIJ international》 |2018年第6期|1007-1012|共6页
作者
Yusuke HARAGUCHI; Masashi NAKAMOTO; Masanori SUZUKI; Kiyoshi FUJI-TA; Toshihiro TANAKA;
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作者单位

Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan;

Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan;

Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan;

Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan;

Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
原文格式 PDF
正文语种 eng
中图分类
关键词
electrical conductivity; multicomponent molten slag; neural network computation; estimation;

机译：电导率多组分熔渣神经网络计算;估算;

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专利

1. Electrical Conductivity Calculation of Molten Multicomponent Slag by Neural Network Analysis [J] . Yusuke Haraguchi, Masashi Nakamoto, Masanori Suzuki, ISIJ international . 2018,第6期

机译：基于神经网络的多组分熔渣电导率计算。
2. Estimation Model for Electrical Conductivity of Molten CaF2-Al2O3-CaO Slags Based on Optical Basicity [J] . Birol Burak, Polat Gokhan, Saridede Muhlis Nezihi JOM . 2015,第2期

机译：基于光学碱度的CaF2-Al2O3-CaO熔渣电导率估算模型
3. (S004_1)Viscosity and electrical conductivity estimations of metallurgical molten slags [J] . Guo-Hua Zhang, Kuo-Chih Chou 材料とプロセス: 日本鉄鋼協会講演論文集 . 2013,第2期

机译：（S004_1）冶金熔渣的粘度和电导率估算
4. Application of CVCC technique for measuring electrical conductivity of metallurgical slags and molten salts [C] . Piotr Palimaka, Stanistaw Pietrzyk, Tomasz Sak International Conference on Non-Ferrous Metals . 2016

机译：CVCC技术在冶金炉渣和熔盐的测量电导率下的应用
5. High-pressure experimental investigations of the melting systematics of compositionally variable peridotites and the electrical conductivity of partially-molten peridotite. [D] . Schwab, Brandon Edward. 2000

机译：高压实验研究组成可变橄榄岩的熔融体系和部分熔融橄榄岩的电导率。
6. Prediction of Electrical Conductivity of Fiber-Reinforced Cement-Based Composites by Deep Neural Networks [O] . Dongdong Yuan, Wei Jiang, Zheng Tong, 2019

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7. Effect of V₂O₅, Cr₂O₃, P₂O₅ or TiO₂ on the Electrical Conductivity of Molten CaO (43)-SiO₂(43)-Al₂O₃(14) Slag. (Research on the molten slag refyning- IX) [O] . Makoto KATO, Susumu MINOWA 1966

机译：V _{2 O _{5 ，Cr _{2 O _{3 ，p _{2 o _{5 或tiO _{2 在熔融CaO（43）-sio _{2 （43）-al _{2 O _{3 （14）渣。（熔渣Refyning-IX的研究）}}}}}}}}}}
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Electrical Conductivity Calculation of Molten Multicomponent Slag by Neural Network Analysis

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