Useful Links
Physics
Fluid Dynamics
Computational Fluid Dynamics (CFD)
Introduction to CFD
Definition and Scope
Historical Development of CFD
Importance in Modern Engineering
Numerical Methods
Finite Difference Method
Basic Concept
Discretization of Derivatives
Stability and Convergence
Finite Volume Method
Control Volume Analysis
Flux Calculations
Conservative Properties
Finite Element Method
Mesh Generation
Basis Functions
Application in Complex Geometries
Comparison of Numerical Methods
Strengths and Weaknesses
Selection Criteria
Turbulence Modeling
Direct Numerical Simulation (DNS)
Characteristics and Limitations
Computational Cost
Large Eddy Simulation (LES)
Filtering and Sub-grid Scales
Applications in High Reynolds Number Flows
Reynolds-Averaged Navier-Stokes (RANS)
Turbulence Closure Models
k-epsilon Model
k-omega Model
Spalart-Allmaras Model
Implementation in Industrial Flows
Hybrid Models
Detached Eddy Simulation (DES)
Delayed Detached Eddy Simulation (DDES)
Grid Generation
Structured Grids
Cartesian Grids
Polar and Cylindrical Grids
Unstructured Grids
Triangular and Tetrahedral Elements
Adaptive Mesh Refinement
Grid Quality and Resolution
Mesh Independence Study
Grid Transformation Techniques
Validation and Verification
Code Verification
Method of Manufactured Solutions
Benchmark Problems
Validation Against Experimental Data
Wind Tunnel Results
Field Measurements
Sensitivity Analysis
Parameter Variation
Impact on Results
Error Sources and Estimation
Numerical Error
Modeling Error
Discretization Error
Post-Processing of CFD Results
Visualization Techniques
Streamlines and Pathlines
Contour and Vector Plots
Data Analysis
Flow Quantities Calculation
Force and Pressure Coefficients
Interpretation of Results
Identifying Flow Patterns
Assessing Design Performance
Software and Computational Resources
Commercial Software Packages
ANSYS Fluent
OpenFOAM
COMSOL
Custom CFD Codes
Development and Application
Integration with In-house Tools
High-Performance Computing (HPC)
Parallel Computing
Cloud-Based Simulations
Challenges and Future Directions
Handling Complex Geometries
Multiscale and Multiphysics Coupling
Uncertainty Quantification
Emerging Applications
Renewable Energy Systems
Biomedical Engineering
Future Trends
Machine Learning in CFD
Real-time Simulation Capabilities
5. Applications in Engineering and Nature
First Page
7. Experimental Fluid Dynamics