This book aims at providing a computational framework of radiative heat transfer in participating media. The book mainly helps engineers and researchers develop their own codes for radiative transfer analysis, starting from simple benchmark problems and extending further to industry scale problems. The computations related to radiative heat transfer are very relevant in iron and steel manufacturing industries, rocket exhaust designing, fire resistance testing, and atmospheric and solar applications. The methods to accurately treat the non-gray nature of the participating gases such as H2O, CO2, and CO are discussed along with considering particle radiation. The solver development based on these methods and its application to a variety of industry problems and different kind of geometries is a significant attraction in the book. The last section of the book deals with the use of artificial neural networks and genetic algorithm-based optimization technique for solving practical problems of process parameter optimization in industry. This book is a comprehensive package taking the readers from the basics of radiative heat transfer in participating media to equip them with their own solvers and help to apply to industry problems.
Author(s): Rahul Yadav, C. Balaji, S. P. Venkateshan
Publisher: Springer
Year: 2022
Language: English
Pages: 200
City: Cham
Preface
Contents
About the Authors
1 Introduction
1.1 Thermal Radiation
1.2 Importance of Radiative Heat Transfer
1.3 Radiative Heat Transfer in Participating Medium
1.4 Radiative Transfer Equation
1.5 Properties of a Participating Medium
1.6 Organization of the Book
2 Important Literatures on Radiative Heat Transfer
2.1 Introduction
2.2 Background
2.3 Studies on Development of RTE Solver
2.4 Studies on Development of Band Models
2.5 Studies on Inclusion of Particle Radiation
2.6 Application-Based Studies
2.7 Relevance, Scope, and Challenges
3 Mathematical Formulation
3.1 Introduction
3.2 Solution Methods for RTE
3.2.1 Traditional Discrete Ordinates Method
3.2.2 Finite Volume Method
3.3 Estimation of Gas Properties
3.3.1 Full Spectrum Band Models
3.3.2 The SLW Model
3.3.3 Functional form of the ALBDF
3.3.4 Formulation for Non-isothermal, Non-homogeneous Media
3.3.5 SLW-Gray Approximation
3.4 Estimation of Particle Properties
3.4.1 Scattering by a Single Particle
3.4.2 Scattering by a Group of Particles
3.4.3 Treatment of the Phase Function and Anisotropic Scattering
3.4.4 Calculation of Particle Properties in Conjunction with Band Models
3.5 Modeling of Radiative Equilibrium
3.6 Closure
4 Radiative Heat Transfer in Cylindrical Geometries
4.1 Introduction
4.2 Development of the FVM-SLW Method for a Cylindrical Geometry
4.3 Solution Procedure
4.4 Validation of the FVM-SLW Method for the Cylindrical Geometry
4.4.1 Validation with Experimental Results
4.4.2 Validation for a Non-Gray Gas-Particle Mixture
4.4.3 Validation for Anisotropic Scattering
4.4.4 Decision on the Number of Gray Gases
4.5 Application to an Industrial Scale Delft Furnace
4.5.1 Effect of Gas Concentration
4.5.2 Effect of Particle Concentration
4.6 Application to a Rocket Plume Base Heating Problem
4.6.1 Effect of Gas Concentration
4.6.2 Effect of Particle Concentration
4.7 Conclusions
4.8 Closure
5 Radiative Heat Transfer in Conical Geometries
5.1 Introduction
5.2 FVM-SLW Formulations for Body-Fitted Conical Geometries
5.3 Validation
5.3.1 Validation with Absorbing Emitting and Scattering Medium
5.4 Application to a Conical Diffuser
5.4.1 Decision on the Minimum Number of Gray Gases
5.4.2 Effect of Gas Concentration
5.4.3 Effect of Particle Concentration
5.4.4 Effect of Cone Angle
5.4.5 Effect of Anisotropic Scattering
5.4.6 Effect of Wall Emission
5.5 Conclusions
5.6 Closure
6 Radiative Heat Transfer in Three-Dimensional Geometries
6.1 Introduction
6.2 Formulations for a Three-Dimensional Rectangular Geometry
6.3 Validation
6.3.1 Validation for a Three-Dimensional Furnace with Measured Temperatures
6.3.2 Validation for a Mixture of Non-gray Gases
6.3.3 Validation with Experimental Results
6.4 Application to a Section of a Reheating Furnace
6.4.1 Effect of Particles and Anisotropic Scattering
6.4.2 Effect of Gas Concentration
6.4.3 Effect of Roof Temperature
6.5 Conclusions
6.6 Closure
7 AI-Based Solution to Practical Radiant Heating Problems
7.1 Introduction
7.2 Need for a Fast Forward Prediction Model
7.3 Artificial Neural Networks
7.4 Development of ANN for a Two-Dimensional Rectangular Geometry
7.5 Comparison of ANN with RTE
7.6 Application of the Network to the Inverse Problem
7.6.1 Optimum Configurations for the Design Case
7.6.2 Validation of Optima Using Forward Model Calculations
7.7 Development of ANN for a Three-Dimensional Rectangular Geometry
7.8 Comparison of ANN Prediction with RTE Solution
7.9 Application of the Network to the Inverse Problem
7.9.1 Genetic Algorithm (GA)
7.9.2 Optimal Configuration for Design Case
7.9.3 Validation of Optima with Forward Model Calculations
7.10 Validation of Optima with Exhaustive Search
7.11 Conclusions
7.12 Closure
8 Conclusions and Future Perspective
8.1 Conclusions
8.2 Overview of the Framework of A Generic RHT Solver
8.3 A Grand Overview of the Present Study
8.4 Suggestions for Future Work
8.5 Closure
A Formulation of Mie Scattering Theory
Appendix B Radiative Properties of Soot Based on Temperature and Type of Fuel
Appendix C MATLAB Codes
Index
