Computational Fluid Flow and Heat Transfer: Advances, Design, Control, and Applications

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Aim and scope
Preface
Acknowledgments
List of contributors
About the editors
Chapter 1: Introduction to mathematical and computational methods
1.1 Introduction
1.2 Advanced computational tools for fluid flow analysis
1.2.1 Governing equations and numerical methods
1.2.2 Turbulence modeling
1.2.3 Multiphase flow simulations
1.2.4 High-performance computing and parallel processing
1.2.5 Validation and verification
1.2.6 Convection and radiation modeling
1.2.7 Phase change and boiling
1.2.8 Multiphysics coupling
1.2.9 High-performance computing and parallel processing
1.2.10 Visualization and post-processing
1.3 CFD software application in different Industries
1.4 Steps involved in CFD simulation
1.5 Comparison of MATLAB code results with the CFD results
1.5.1 Computational solution using Matlab
1.6 Computational solution using ANSYS
1.7 Benefits and limitations of CFD
1.8 Future trends and challenges
1.9 Conclusion
References
Chapter 2: IoT-enabled monitoring for natural convection solar dryers
2.1 Introduction
2.1.1 Novelty
2.2 Materials and methods
2.2.1 Experimental setup
2.2.2 Performance analysis
2.3 Uncertainty analysis
2.4 Proposed IoT system design
2.4.1 Solar dryer setup
2.4.2 Sensors
2.4.3 Analog to digital converter
2.4.4 NodeMcu processor
2.4.5 Cloud storage
2.4.5.1 Adafruit
2.5 Investigating the IoT-based data transfer model accuracy and error with experimental data sets
2.6 Results and discussion
2.6.1 Solar dryer part
2.6.2 Internet of Things aspect
2.7 Conclusions
Nomenclature
Abbreviation
References
Chapter 3: Natural convection study in cylindrical annulus through OpenFOAM
3.1 Introduction
3.2 Problem setup and mathematical formulation
3.2.1 Problem setup
3.2.2 Mathematical formulations
3.2.3 Important quantities in natural convection heat transfers
3.2.3.1 Stream function
3.2.3.2 Vorticity
3.2.3.3 Enstrophy
3.2.3.4 Local Nusselt numbers
3.3 Numerical solver and validation
3.4 Results and discussion
3.5 Conclusion
References
Chapter 4: MHD forced convection in Casson hybrid nanofluids with Soret and Dufour effects
4.1 Introduction
4.2 Mathematical formulation of the flow geometry
4.3 Solution methodology
4.4 Mathematical computation of finite difference scheme
4.5 Result and discussions
4.6 Conclusions
Appendix
Nomenclature
Greek Symbols
References
Chapter 5: Boundary layer flow in aerospace applications
5.1 Introduction
5.2 Fundamentals of boundary layer flow
5.2.1 Concept of boundary layer
5.2.2 Boundary layer thickness
5.2.3 Velocity profiles and flow characteristics
5.2.4 Boundary layer separation
5.3 Mathematical modelling of boundary layer flow
5.3.1 Navier-Stokes equations and simplifications
5.3.1.1 Simplifications of the Navier-Stokes equations
5.3.2 Boundary layer equations
5.3.3 Boundary conditions
5.3.4 Numerical methods for solving boundary layer equations
5.4 Aerodynamic characteristics of boundary layer flow
5.4.1 Boundary layer thickness and growth
5.4.1.1 Boundary layer thickness (δ)
5.4.2 Skin friction and drag in boundary layer flow
5.4.3 Boundary layer control techniques
5.5 Boundary layer flow over aerospace components
5.5.1 Boundary layer flow over aerofoils
5.5.2 Boundary layer flow over wings
5.5.3 Boundary layer flow over control surfaces
5.6 Factors affecting boundary layer flow
5.6.1 Reynolds number and its influence
5.6.1.1 Influence on aerodynamic design
5.6.2 Surface roughness effects
5.6.3 Temperature effects
5.6.4 Compressibility effects
5.7 Design strategies for boundary layer flow control
5.7.1 Passive flow control techniques
5.7.2 Active flow control techniques
5.7.3 Optimizing boundary layer flow control systems
5.8 Future directions and research in boundary layer flow
References
Chapter 6: Sensitivity analysis for aerospace engineering applications
6.1 Introduction
6.2 Computational modelling
6.3 Global sensitivity analysis
6.3.1 Sampling methods for the sensitivity analysis
6.3.2 RBF-based metamodelling
6.3.3 Sensitivity indices by Sobol’s method
6.4 Mesh refinement analysis and validation
6.5 Results and discussion
6.6 Concluding remarks
Acknowledgements
References
Chapter 7: Design optimization and sensitivity analysis in aerospace engineering
7.1 Introduction
7.2 Sensitivity analysis in wind tunnel testing and experimental techniques
7.3 Sensitivity analysis in aerospace engineering
7.3.1 Definition and importance of sensitivity analysis
7.4 Role in design optimization
7.5 Uncertainty quantification and risk assessment
7.6 System-level analysis and decision-making
7.7 Current methodologies and limitations
7.8 Parametric sensitivity analysis
7.9 Gradient-based sensitivity analysis
7.10 Global sensitivity analysis
7.11 Challenges in traditional approaches
7.12 Future trends in sensitivity analysis
7.13 Integration of machine learning and AI
7.14 Data-driven sensitivity analysis techniques
7.15 Hybrid approaches: Physics-based and data-driven
7.16 Advancements in sensitivity analysis algorithms
7.17 Application in emerging aerospace areas
7.18 Sensitivity analysis in electric propulsion systems
7.19 UAV design and operation optimization
7.20 Sensitivity analysis in space exploration missions
7.21 Role in sustainable aerospace technologies
7.22 Challenges and considerations
7.22.1 High-dimensional parameter spaces
7.22.2 Dealing with complex and nonlinear relationships
7.22.3 Computational costs and efficiency
7.22.4 Uncertainty quantification and robustness analysis
7.22.5 Ethical considerations in sensitivity analysis
7.23 Conclusion and future outlook
References
Chapter 8: Modeling of flows through porous media
8.1 Basics of flow through porous media
8.1.1 Porosity
8.1.2 Darcy’s law and permeability
8.1.3 Pore size and pore size distribution
8.1.4 Specific surface
8.1.5 Hydraulic conductivity
8.1.5.1 Constant head method for hydraulic conductivity prediction
8.1.5.2 Falling head method for hydraulic conductivity prediction
8.2 Fundamentals of capillarity in porous media
8.2.1 Laplace’s equation
8.2.2 Surface wettability and contact angle
8.2.3 Capillary pressure and capillary rise
8.3 Modeling of flow in porous medium
8.3.1 Assumptions and limitations for porous media modeling
8.3.2 Momentum equations for porous media
8.3.3 Darcy’s Law in porous media
8.3.4 Inertial losses in porous media
8.3.5 Energy equation in porous media
8.3.6 Porous media modeling based on physical velocity for single and multiphase systems
8.3.6.1 Single-phase porous media modeling
8.3.6.2 Multiphase porous media modeling
8.3.6.2.1 The continuity equation
8.3.6.2.2 The momentum equation
8.3.6.2.3 The energy equation
8.4 Example case study focused on drying of cotton in pneumatic conveyer belt
8.4.1 Motivation for cotton drying study
8.4.2 Background of research work relevant to cotton drying
8.4.3 Drying of porous material in a conveyer belt system
8.4.3.1 Meshing of the geometry of system
8.4.4 Numerical methods
8.4.4.1 Modeling assumptions and critical equations
8.4.4.2 Boundary conditions for simulations
8.4.5 Cotton moisture calculation
8.4.6 Heat transfer and evaporation (moisture removal) model
8.4.6.1 Heat transfer model
8.4.6.2 Evaporation model
8.4.7 Cotton drying CFD simulations
8.4.8 Results and discussion
8.4.8.1 Mesh independency test
8.4.8.2 Characteristic properties of the conveying system
8.4.8.3 Effect of relative air speed on cotton drying
8.4.8.4 Comparison of moisture loss during cotton drying
8.4.9 Conclusion from the case study
8.5 Learning from this chapter
Acknowledgment
References
Chapter 9: Numerical analysis of turbulent flow in tubes with longitudinal fin using Al 2 O 3 -water nanofluids
9.1 Introduction
9.1.1 Physical model
9.1.2 Governing equations and boundary conditions
9.1.3 Boundary conditions
9.1.4 Grid independence
9.1.5 Model validation
9.1.6 Data reduction
9.1.7 Thermophysical property of nanofluid
9.2 Results and discussions
9.2.1 Effects of solid volume fraction
9.2.2 Comparison of tubes
9.3 Conclusions
References
Chapter 10: Gravity-modulated thermal instability in Oldroyd-B nanofluids
10.1 Introduction
10.2 Mathematical statement of the problem
10.2.1 Equation of continuity
10.2.2 Equation of momentum-balance
10.2.3 Equation of heat balance
10.2.4 Equation of nanoparticle volume fraction
10.3 Basic solution
10.4 Perturbation solution
10.5 Types of modulation
10.6 Stability analysis
10.6.1 Linear stability
10.6.1.1 Normal mode technique
10.6.2 Nonlinear analysis
10.7 Heat transport and nanoparticle concentration
10.8 Results and discussion
10.8.1 Linear stability analysis
10.8.2 Nonlinear stability analysis
10.9 Effect of gravity modulation
10.10 Numerical uncertainty analysis
10.11 Conclusions
Acknowledgment
Nomenclature
Latin Symbols
Greek Symbols
Subscripts and Superscripts
Operators
References
Chapter 11: Thermal instability in Hele-Shaw Cell with variable forces for Rivlin-Ericksen Nanofluid
11.1 Introduction: Background and driving forces
11.2 Problem formulations
11.3 Governing equations
11.4 Boundary conditions
11.5 Primary state
11.6 Perturbation state
11.7 Linear stability exploration
11.8 Weakly nonlinear stability exploration
11.9 Heat and mass transfer
11.10 Results and discussion
11.10.1 Stationary convection
11.10.2 Heat and mass transfer
11.11 Conclusions
Nomenclature
Operator
Nondimensional parameters
References
Chapter 12: MHD flow of a micropolar hybrid nanofluid between two parallel disks
12.1 Introduction
12.2 Mathematical formulation
12.3 Methodology of DTM
12.4 Application of DTM
12.5 Results and discussion
12.6 Conclusions
References
Chapter 13: Modeling Rayleigh-Taylor instability in nanofluid layers
13.1 Introduction
13.2 Modeling
13.3 Stability analysis
13.3.1 Basic state
13.3.2 Perturbed state
13.3.3 Interfacial and boundary conditions
13.4 Dispersion relationship
13.5 Nondimensional form
13.6 Results and discussion
13.7 Conclusions
References
Chapter 14: Shock wave effects on hydrodynamic instability in elliptical bubbles
14.1 Introduction
14.2 Problem setup
14.3 Numerical procedure
14.4 Numerical results and discussion
14.5 Conclusion
References
Index