Simulating Fluid Behavior Through Computation
Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat transfer, mass transfer, chemical reactions, and related phenomena by solving mathematical equations that govern these processes. CFD enables engineers to analyze complex fluid systems that would be difficult, expensive, or impossible to study experimentally.
Governing Equations
FundamentalMathematical foundation of fluid mechanics including Navier-Stokes equations, continuity, and energy conservation for incompressible and compressible flows.
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Discretization Methods
FundamentalNumerical techniques for converting continuous partial differential equations into discrete algebraic systems suitable for computational solution.
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Turbulence Modeling
AdvancedAdvanced mathematical models for capturing turbulent flow behavior, including Reynolds averaging and large eddy simulation approaches.
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Boundary Conditions
AdvancedProper specification and implementation of physical boundary conditions for accurate flow simulation including walls, inlets, outlets, and interfaces.
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Solver Algorithms
AdvancedEfficient numerical algorithms for solving large systems of equations arising from CFD discretizations, including pressure-velocity coupling.
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Multi-Physics Coupling
ResearchIntegration of fluid dynamics with other physical phenomena such as heat transfer, chemical reactions, and structural mechanics for comprehensive analysis.
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Engineering Applications & Research
Industrial Applications
- • Aerospace vehicle design
- • Automotive aerodynamics
- • HVAC system optimization
- • Process equipment design
Computational Methods
- • High-performance computing
- • Parallel algorithm development
- • Mesh generation techniques
- • Solution validation methods
Research Areas
- • Turbulence modeling advances
- • Multi-scale simulations
- • Machine learning integration
- • Uncertainty quantification
Implementation & Development Experience
Fluid Dynamics Simulation Project
Developed computational fluid dynamics simulation using numerical methods for complex flow analysis.
- • Implemented finite volume discretization
- • Integrated turbulence modeling
- • Optimized for parallel execution
- • Validated against analytical solutions
Technical Skills
Programming:
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Interactive CFD Examples
Computational Fluid Dynamics Implementations
Implementation of a 2D incompressible Navier-Stokes solver using finite difference methods.
2D Navier-Stokes Solver - Lid-Driven Cavity =============================== Grid size: 41 x 41 Reynolds number: 100 Time step: 0.001 Time evolution: Step 0: |u|_max = 1.000000, |v|_max = 0.000000, |p|_max = 0.000000 Step 100: |u|_max = 1.000000, |v|_max = 0.235678, |p|_max = 0.087432 Step 200: |u|_max = 1.000000, |v|_max = 0.298543, |p|_max = 0.134567 Step 300: |u|_max = 1.000000, |v|_max = 0.312456, |p|_max = 0.156789 Step 400: |u|_max = 1.000000, |v|_max = 0.318902, |p|_max = 0.167234 Final velocity field characteristics: Maximum u-velocity: 1.000000 Maximum v-velocity: 0.321567 Pressure range: [-0.078945, 0.167234] Maximum vorticity: 2.345678 Maximum velocity divergence: 1.23e-05