本书在简单介绍一般火焰、熔体和气-粒广义流态化系统的流场、温度场、浓度场、电磁场数学模拟原理和方法的基础上，重点介绍了作者及其课题组近十年来按“数学模拟-全息仿真-整体优化”的思路研究有色冶金炉窑仿真和优化的实例，包括铝电解槽、熔炼电炉、贫化电炉、碳阳极焙烧炉、闪速熔炼炉、锅炉以及单端辐射管仿真和优化的过程与结果。

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.

1 Introduction

 1.1 Classification of the Furnaces and Kilns for Nonferrous Metallurgical Engineering (FKNME)

 1.2 The Thermophysical Processes and Thermal Systems of the FKNME.

 1.3 A Review of the Methodologies for Designs and Investigations of FKNME

1.3.1 Methodologies for design and investigation of FKNME

1.3.2 The characteristics of the MHSO method

 1.4 Models and Modeling for the FKNME

1.4.1 Models for the modem FKNME

1.4.2 The modeling process

 References

2 Modeling of the Thermophysical Processes in FKNME

 2.1 Modeling of the Fluid Flow in the FKNME

2.1.l Introduction

2.1.2 The Reynolds-averaging and the Favre-averaging methods

2.1.3 Turbulence models

2.1.4 Low Reynolds number k-e models

2.1.5 Re-Normalization Group (RNG) k-e models

2.1.6 Reynolds stresses model(RSM)

 2.2 The Modeling of the Heat Transfer in FKNME

2.2.1 Characteristics of heat transfer inside furnaces

2.2.2 Zone method

2.2.3 Monte Carlo method

2.2.4 Discrete transfer radiation model

 2.3 The Simulation of Combustion and Concentration Field

2.3.1 Basic equations of fluid dynamics including chemical reactions..

2.3.2 Gaseous combustion models

2.3.3 Droplet and particle combustion models

2.3.4 NOx models

 2.4 Simulation of Magnetic Field

2.4.1 Physical models

2.4.2 Mathematical model of current field

2.4.3 Mathematical models of magnetic field in conductive elements..

2.4.4 Magnetic field models of ferromagnetic elements

2.4.5 Three-dimensional mathematical model of magnetic field

 2.5 Simulation on Melt Flow and Velocity Distribution in Smelting Furnaces

2.5.1 Mathematical model for the melt flow in smelting furnace

2.5.2 Electromagnetic flow

2.5.3 The melt motion resulting from jet-flow

 References

3 Hologram Simulation of the FKNME

 3.1 Concept and Characteristics of Hologram Simulation

 3.2 Mathematical Models of Hologram Simulation

 3.3 Applying Hologram Simulation to Multi-field Coupling

3.3.1 Classification of multi-field coupling

3.3.2 An example of intra-phase three-field coupling

3.3.3 An example of four-field coupling

 3.4 Solutions of Hologram Simulation Models

 References

4 Thermal Engineering Processes Simulation Based on Artificial Intelligence

 4.1 Characteristics of Thermal Engineering Processes in Nonferrous Metallurgical Furnaces

 4.2 Introduction to Artificial Intelligence Methods

4.2.1 Expert system

4.2.2 Fuzzy simulation

4.2.3 Artificial neural network

 4.3 Modeling Based on Intelligent Fuzzy Analysis

4.3.1 Intelligent fuzzy self-adaptive modeling of multi-variable system

4.3.2 Example: fuzzy adaptive decision-making model for nickel matte smelting process in submerged arc furnace

 4.4 Modeling Based on Fuzzy Neural Network Analysis

4.4.1 Fuzzy neural network adaptive modeling methods of multi-variable system

4.4.2 Example: fuzzy neural network adaptive decision-making model for production process in slag cleaning furnace

 References

5 Hologram Simulation of Aluminum Reduction Cells

 5.1 Introduction

 5.2 Computation and Analysis of the Electric Field and Magnetic Field..

5.2.1 Computation model of electric current in the bus bar

5.2.2 Computational model of electric current in the anode

5.2.3 Computation and analysis of electric field in the melt

5.2.4 Computation and analysis of electric field in the cathode

5.2.5 Computation and analysis of the magnetic field

 5.3 Computation and Analysis of the Melt Flow Field

5.3.1 Electromagnetic force in the melt

5.3.2 Analysis of the molten aluminum movement

5.3.3 Analysis of the electrolyte movement

5.3.4 Computation of the melt velocity field

 5.4 Analysis of Thermal Field in Aluminum Reduction Cells

5.4.1 Control equations and boundary conditions

5.4.2 Calculation methods

 5.5 Dynamic Simulation for Aluminum Reduction Cells

5.5.1 Factors influencing operation conditions and principle of the dynamic simulation

5.5.2 Models and algorithm

5.5.3 Technical scheme of the dynamic simulation and function of the software system

 5.6 Model of Current Efficiency of Aluminum Reduction Cells

5.6.1 Factors influencing current efficiency and its measurements

5.6.2 Models of the current efficiency

 References

6 Simulation and Optimization of Electric Smelting Furnace

 6.1 Introduction

 6.2 Sintering Process Model of Self-baking Electrode in Electric Smelting Furnace

6.2.1 Electric and thermal analytical model of the electrode

6.2.2 Simulation software

6.2.3 Analysis of the computational result and the baking process

6.2.4 Optimization of self-baking electrode configuration and operation regime

 6.3 Modeling of Bath Flow in Electric Smelting Furnace

6.3.1 Mathematical model for velocity field of bath

6.3.2 The forces acting on molten slag

6.3.3 Solution algorithms and characters

 6.4 Heat Transfer in the Molten Pool and Temperature Field Model of the Electric Smelting Furnace

6.4.1 Mathematical model of the temperature field in the molten pool

6.4.2 Simulation software

6.4.3 Calculation results and verification

6.4.4 Evaluation and optimization of the furnace design and operation

 References

7 Coupling Simulation of Four-fleld in Flame Furnace

 7.1 Introduction

 7.2 Simulation and Optimization of Combustion Chamber of Tower-Type Zinc Distillation Furnace

7.2.1 Physical model

7.2.2 Mathematical model

7.2.3 Boundary conditions

7.2.4 Simulation of the combustion chamber prior to structure optimization

7.2.5 Structure simulation and optimization of combustion chamber

 7.3 Four-field Coupling Simulation and Intensification of Smelting in Reaction Shaft of Flash Furnace

7.3.1 Mechanism of flash smelting process--particle fluctuating collision model

7.3.2 Physical model

7.3.3 Mathematical model----coupling computation of particle and gas phases

7.3.4 Simulation results and discussion

7.3.5 Enhancement of smelting intensity in flash furnace

 References

8 Modeling of Dilute and Dense Phase in Generalized Fluidization

 8.1 Introduction

 8.2 Particle Size Distribution Models

8.2.1 Normal distribution model

8.2.2 Logarithmic probability distribution model

8.2.3 Weibull probability distribution function

8.2.4 R-R distribution function (Rosin-Rammler distribution)

8.2.5 Nukiyawa-Tanasawa distribution function

 8.3 Dilute Phase Models

8.3.1 Non-slip model

8.3.2 Small slip model

8.3.3 Multi-fluid model (or two-fluid model)

8.3.4 Particle group trajectory model

8.3.5 Solution of the particle group trajectory model

 8.4 Mathematical Models for Dense Phase

8.4.1 Two-phase simple bubble model

8.4.2 Bubbling bed model

8.4.3 Bubble assemblage model (BAM)

8.4.4 Bubble assemblage model for gas-solid reactions

8.4.5 Solid reaction rate model in dense phase

 References

9 Multiple Modeling of the Single-ended Radiant Tubes

 9.1 IntroductiOn

9.1.1 The SER tubes and the investigation of SER tubes

9.1.2 The overall modeling strategy

 9.2 3D Cold State Simulation of the SER Tube

 9.3 2D Modeling of the SER Tube

9.3.1 Selecting the turbulence model

9.3.2 Selecting the combustion model

9.3.3 Results and analysis of the 2D simulation

 9.4 One-dimensional Modeling of the SER Tube

 References

10 Multi-objective Systematic Optimization of FKNME

 10.1 Introduction

10.1.1 A historic review

10.1.2 The three principles for the FKNME systematic optimization

 10.2 Objectives of the FKNME Systematic Optimization

10.2.1 Unit output functions

10.2.2 Quality control functions

10.2.3 Control function of service lifetime

10.2.4 Functions of energy consumption

10.2.5 Control functions of air pollution emissions

 10.3 The General Methods of the Multi-purpose Synthetic Optimization

10.3.1 Optimization methods of artificial intelligence

10.3.2 Consistent target approach

10.3.3 The main target approach

10.3.4 The coordination curve approach

10.3.5 The partition layer solving approach

10.3.6 Fuzzy optimization of the multi targets

 10.4 Technical Carriers of Furnace Integral Optimization

10.4.1 Optimum design CAD

10.4.2 Intelligent decision support system for furnace operation optimization

10.4.3 Online optimization system

10.4.4 Integrated system for monitoring, control and management

 References

Index