Simulation and Optimization of Furnaces and Kilns for Nonferrous Metallurgical Engineering

by Mei, Chi; Zhou, Jiemin; Peng, Xiaoqi; Zhou, Naijun; Zhou, Ping

• ISBN13: 9783642002472
• ISBN10: 3642002471
• Format: Hardcover
• Copyright: 2010-12-23
• Publisher: Springer Nature

Summary

Simulation and Optimization of Furnaces and Kilns for Nonferrous Metallurgical Engineering is based on advanced theories and research methods for fluid flow, mass and heat transfer, and fuel combustion. It introduces a hologram simulation and optimization methods for fluid field, temperature field, concentration field, and electro-magnetic field in various kinds of furnaces and kilns. Practical examples and a detailed introduction to methods for simulation and optimization of complex systems are included as well. These new methods have brought significant economic benefits to the industries involved. The book is intended for researchers and technical experts in metallurgical engineering, materials engineering, power and thermal energy engineering, chemical engineering, and mechanical engineering.Chi Mei, Jie-min Zhou, Xiao-qi Peng, Nai-jun Zhou and Ping Zhou are all professors at School of Energy Science and Engineering, Central South University, Changsha, Hunan Province, China.

Author Biography

Chi Mei, Jiemin Zhou, Xiaoqi Peng, Naijun Zhou and Ping Zhou are all professors at School of Energy Science and Engineering, Central South University, Changsha, Hunan Province, China.

Table of Contents

Introduction	p. 1
Classification of the Furnaces and Kilns for Nonferrous Metallurgical Engineering (FKNME)	p. 1
The Thermophysical Processes and Thermal Systems of the FKNME	p. 2
A Review of the Methodologies for Designs and Investigations of FKNME	p. 4
Methodologies for design and investigation of FKNME	p. 4
The characteristics of the MHSO method	p. 5
Models and Modeling for the FKNME	p. 7
Models for the modern FKNME	p. 7
The modeling process	p. 7
References	p. 9
Modeling of the Thermophysical Processes in FKNME	p. 11
Modeling of the Fluid Flow in the FKNME	p. 11
Introduction	p. 11
The Reynolds-averaging and the Favre-averaging methods	p. 13
Turbulence models	p. 15
Low Reynolds number k-¿ models	p. 21
Re-Normalization Group (RNG) K-¿ models	p. 25
Reynolds stresses model(RSM)	p. 26
The Modeling of the Heat Transfer in FKNME	p. 27
Characteristics of heat transfer inside furnaces	p. 27
Zone method	p. 29
Monte Carlo method	p. 33
Discrete transfer radiation model	p. 35
The Simulation of Combustion and Concentration Field	p. 38
Basic equations of fluid dynamics including chemical reactions	p. 38
Gaseous combustion models	p. 42
Droplet and particle combustion models	p. 48
NOx models	p. 54
Simulation of Magnetic Field	p. 60
Physical models	p. 60
Mathematical model of current field	p. 61
Mathematical models of magnetic field in conductive elements	p. 62
Magnetic field models of ferromagnetic elements	p. 66
Three-dimensional mathematical model of magnetic field	p. 69
Simulation on Melt Flow and Velocity Distribution in Smelting Furnaces	p. 69
Mathematical model for the melt flow in smelting furnace	p. 70
Electromagnetic flow	p. 71
The melt motion resulting from jet-flow	p. 75
References	p. 80
Hologram Simulation of the FKNME	p. 87
Concept and Characteristics of Hologram Simulation	p. 87
Mathematical Models of Hologram Simulation	p. 89
Applying Hologram Simulation to Multi-field Coupling	p. 92
Classification of multi-field coupling	p. 92
An example of intra phase three-field coupling	p. 93
An example of four-field coupling	p. 94
Solutions of Hologram Simulation Models	p. 97
References	p. 98
Thermal Engineering Processes Simulation Based on Artificial Intelligence	p. 101
Characteristics of Thermal Engineering Processes in Nonferrous Metallurgical Furnaces	p. 101
Introduction to Artificial Intelligence Methods	p. 102
Expert system	p. 103
Fuzzy simulation	p. 104
Artificial neural network	p. 106
Modeling Based on Intelligent Fuzzy Analysis	p. 107
Intelligent fuzzy self-adaptive modeling of multi-variable system	p. 108
Example: fuzzy adaptive decision-making model for nickel matte smelting process in submerged arc furnace	p. 111
Modeling Based on Fuzzy Neural Network Analysis	p. 116
Fuzzy neural network adaptive modeling methods of multi-variable system	p. 117
Example: fuzzy neural network adaptive decision-making model for production process in slag cleaning furnace	p. 120
References	p. 123
Hologram Simulation of Aluminum Reduction Cells	p. 127
Introduction	p. 127
Computation and Analysis of the Electric Field and Magnetic Field	p. 131
Computation model of electric current in the bus bar	p. 132
Computational model of electric current in the anode	p. 133
Computation and analysis of electric field in the melt	p. 134
Computation and analysis of electric field in the cathode	p. 138
Computation and analysis of the magnetic field	p. 140
Computation and Analysis of the Melt Flow Field	p. 146
Electromagnetic force in the melt	p. 147
Analysis of the molten aluminum movement	p. 148
Analysis of the electrolyte movement	p. 149
Computation of the melt velocity field	p. 150
Analysis of Thermal Field Aluminum Reduction Cells	p. 152
Control equations and boundary conditions	p. 153
Calculation methods	p. 156
Dynamic Simulation for Aluminum Reduction Cells	p. 158
Factors influencing operation conditions and principle of the dynamic simulation	p. 159
Models and algorithm	p. 160
Technical scheme of the dynamic simulation and function of the software system	p. 161
Model of Current Efficiency of Aluminum Reduction Cells	p. 163
Factors influencing current efficiency and its measurements	p. 164
Models of the current efficiency	p. 166
References	p. 169
Simulation and Optimization of Electric Smelting Furnace	p. 175
Introduction	p. 175
Sintering Process Model of Self-baking Electrode in Electric Smelting Furnace	p. 176
Electric and thermal analytical model of the electrode	p. 178
Simulation software	p. 182
Analysis of the computational result and the baking process	p. 183
Optimization of self-baking electrode configuration and operation regime	p. 190
Modeling of Bath Flow in Electric Smelting Furnace	p. 192
Mathematical model for velocity field of bath	p. 193
The forces acting on molten slag	p. 194
Solution algorithms and characters	p. 196
Heat Transfer in the Molten Pool and Temperature Field Model of the Electric Smelting Furnace	p. 198
Mathematical model of the temperature field in the molten pool	p. 199
Simulation software	p. 203
Calculation results and verification	p. 203
Evaluation and optimization of the furnace design and operation	p. 208
References	p. 210
Coupling Simulation of Four-field in Flame Furnace	p. 213
Introduction	p. 213
Simulation and Optimization of Combustion Chamber of Tower-Type Zinc Distillation Furnace	p. 215
Physical model	p. 216
Mathematical model	p. 217
Boundary conditions	p. 217
Simulation of the combustion chamber prior to structure optimization	p. 218
Structure simulation and optimization of combustion chamber	p. 220
Four-field Coupling Simulation and Intensification of Smelting in Reaction Shaft of Flash Furnace	p. 221
Mechanism of flash smelting process-particle fluctuating collision model	p. 223
Physical model	p. 224
Mathematical model-coupling computation of particle and gas phases	p. 225
Simulation results and discussion	p. 227
Enhancement of smelting intensity in flash furnace	p. 229
References	p. 232
Modeling of Dilute and Dense Phase in Generalized Fluidization	p. 235
Introduction	p. 235
Particle Size Distribution Models	p. 238
Normal distribution model	p. 239
Logarithmic probability distribution model	p. 240
Weibull probability distribution function	p. 241
R-R distribution function (Rosin-Rammler distribution)	p. 241
Nukiyawa-Tanasawa distribution function	p. 242
Dilute Phase Models	p. 244
Non-slip model	p. 245
Small slip model	p. 247
Multi-fluid model (or two-fluid model)	p. 248
Particle group trajectory model	p. 251
Solution of the particle group trajectory model	p. 256
Mathematical Models for Dense Phase	p. 257
Two-phase simple bubble model	p. 258
Bubbling bed model	p. 259
Bubble assemblage model (BAM)	p. 261
Bubble assemblage model for gas-solid reactions	p. 265
Solid reaction rate model in dense phase	p. 267
References	p. 272
Multiple Modeling of the Single-ended Radiant Tubes	p. 275
Introduction	p. 275
The SER tubes and the investigation of SER tubes	p. 276
The overall modeling strategy	p. 278
3D Cold State Simulation of the SER Tube	p. 279
2D Modeling of the SER Tube	p. 283
Selecting the turbulence model	p. 283
Selecting the combustion model	p. 286
Results and analysis of the 2D simulation	p. 289
One-dimensional Modeling of the SER Tube	p. 291
References	p. 295
Multi-objective Systematic Optimization of FKNME	p. 297
Introduction	p. 297
A historic review	p. 297
The three principles for the FKNME systematic optimization	p. 298
Objectives of the FKNME Systematic Optimization	p. 299
Unit output functions	p. 300
Quality control functions	p. 305
Control function of service lifetime	p. 306
Functions of energy consumption	p. 308
Control functions of air pollution emissions	p. 309
The General Methods of the Multi-purpose Synthetic Optimization	p. 309
Optimization methods of artificial intelligence	p. 309
Consistent target approach	p. 312
The main target approach	p. 314
The coordination curve approach	p. 315
The partition layer solving approach	p. 315
Fuzzy optimization of the multi targets	p. 316
Technical Carriers of Furnace Integral Optimization	p. 318
Optimum design CAD	p. 319
Intelligent decision support system for furnace operation optimization	p. 320
Online optimization system	p. 327
Integrated system for monitoring, control and management	p. 330
References	p. 334
Index	p. 337
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