Analyzing the Fluid Flow in Continuous Casting through Evolutionary Neural Nets and Multi-Objective Genetic Algorithms

被引：27

作者：

Govindan, Deepak ^{[2
]}

Chakraborty, Suman ^{[2
]}

Chakraborti, Nirupam ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Met & Mat Engn, Kharagpur 721302, W Bengal, India

[2] Indian Inst Technol, Dept Mech Engn, Kharagpur 721302, W Bengal, India

来源：

STEEL RESEARCH INTERNATIONAL | 2010年 / 81卷 / 03期

关键词：

Genetic Algorithms; Continuous Casting; Evolutionary Neural Networks; Evolutionary Computation; Predator-Prey Genetic Algorithm; Multi-objective optimization; BLAST-FURNACE DATA; MATERIALS SCIENCE; STEEL BILLETS; HEAT-TRANSFER; OPTIMIZATION; DESIGN; KNOWLEDGE; NETWORKS; SPRAY; MOLD;

D O I：

10.1002/srin.200900128

中图分类号：

TF [冶金工业];

学科分类号：

0806 ;

摘要：

The flow fields computed for a typical continuous caster are analysed using the basic concepts of Pareto-optimality in the context of multi-objective optimization. The data generated by the flow solver FLUENT (TM) are trained through Evolutionary Neural Networks that emerged through a Pareto-tradeoff between the complexity of the network and its accuracy of training. A number of objectives constructed this way are subjected to optimization using a Multi-objective Predator-Prey Genetic Algorithm. The procedure is repeated using the software mode-FRONTIER (TM) and the results are compared and analysed.

引用

页码：197 / 203

页数：7

共 25 条

[1] Identification and Optimization of AB2 Phases Using Principal Component Analysis, Evolutionary Neural Nets, and Multiobjective Genetic Algorithms [J].

Agarwal, Akash ;

Pettersson, Frank ;

Singh, Arunima ;

Kong, Chang Sun ;

Saxen, Henrik ;

Rajan, Krishna ;

Iwata, Shuichi ;

Chakraborti, Nirupam .

MATERIALS AND MANUFACTURING PROCESSES, 2009, 24 (03) :274-281

[2] A Genetic Algorithm-Assisted Inverse Convective Heat Transfer Model for Tailoring Weld Geometry [J].

Bag, S. ;

De, A. ;

DebRoy, T. .

MATERIALS AND MANUFACTURING PROCESSES, 2009, 24 (03) :384-397

[3] Analyzing Fe-Zn system using molecular dynamics, evolutionary neural nets and multi-objective genetic algorithms [J].

Bhattacharya, Baidurya ;

Kumar, G. R. Dinesh ;

Agarwal, Akash ;

Erkoc, Sakir ;

Singh, Arunima ;

Chakraborti, Nirupam .

COMPUTATIONAL MATERIALS SCIENCE, 2009, 46 (04) :821-827

[4]

Bolender T, 2009, STAHL EISEN, V129, P22

[5] EMPOWERMENT WITH KNOWLEDGE - TOWARD THE INTELLIGENT MOLD FOR THE CONTINUOUS-CASTING OF STEEL BILLETS [J].

BRIMACOMBE, JK .

METALLURGICAL TRANSACTIONS B-PROCESS METALLURGY, 1993, 24 (06) :917-935

[6]

BRIMACOMBE JK, 1974, CIM BULL, V67, P46

[7] Genetic algorithms in materials design and processing [J].

Chakraborti, N .

INTERNATIONAL MATERIALS REVIEWS, 2004, 49 (3-4) :246-260

[8] Optimisation of continuous casting process using genetic algorithms: studies of spray and radiation cooling regions [J].

Chakraborti, N ;

Gupta, RSP ;

Tiwari, TK .

IRONMAKING & STEELMAKING, 2003, 30 (04) :273-278

[9] A heat transfer study of the continuous caster mold using a finite volume approach coupled with genetic algorithms [J].

Chakraborti, N ;

Kumar, KS ;

Roy, GG .

JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 2003, 12 (04) :430-435

[10] Fluid flow in hydrocyclones optimized through multi-objective genetic algorithms [J].

Chakraborti, N. ;

Shekhar, A. ;

Singhal, A. ;

Chakraborty, S. ;

Chowdhury, S. ;

Sripriya, R. .

INVERSE PROBLEMS IN SCIENCE AND ENGINEERING, 2008, 16 (08) :1023-1046

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