All Study Guides Mathematical Fluid Dynamics Unit 3
💨 Mathematical Fluid Dynamics Unit 3 – Conservation Laws in Fluid DynamicsConservation laws in fluid dynamics form the foundation for understanding and modeling fluid behavior. These principles, including mass, momentum, and energy conservation, govern how fluids move and interact with their surroundings.
Mathematical formulations like the continuity equation and Navier-Stokes equations express these laws. These equations, combined with fluid properties and boundary conditions, allow us to analyze and predict fluid flow in various real-world applications, from aerodynamics to meteorology.
Got a Unit Test this week? we crunched the numbers and here's the most likely topics on your next test Key Concepts and Definitions
Conservation laws fundamental principles governing the behavior and evolution of fluid systems
Mass conservation states that mass cannot be created or destroyed within a closed system
Momentum conservation based on Newton's second law of motion (F = m a F = ma F = ma )
Energy conservation derived from the first law of thermodynamics
Includes kinetic, potential, and internal energy components
Continuity equation mathematical expression of mass conservation in fluid dynamics
Navier-Stokes equations set of partial differential equations describing the motion of viscous fluids
Derived from conservation of mass, momentum, and energy principles
Incompressible flow assumes constant fluid density throughout the flow field
Compressible flow accounts for changes in fluid density due to pressure variations
Conservation Principles
Conservation of mass fundamental principle stating that mass is neither created nor destroyed within a system
Mathematically expressed as ∂ ρ ∂ t + ∇ ⋅ ( ρ u ) = 0 \frac{\partial \rho}{\partial t} + \nabla \cdot (\rho \mathbf{u}) = 0 ∂ t ∂ ρ + ∇ ⋅ ( ρ u ) = 0
Conservation of momentum based on Newton's second law of motion (F = m a F = ma F = ma )
Relates forces acting on a fluid element to its acceleration
Conservation of energy derived from the first law of thermodynamics
States that energy cannot be created or destroyed, only converted between different forms
Conservation principles form the foundation for deriving governing equations in fluid dynamics
Applying conservation laws to a control volume leads to integral formulations of the governing equations
Conservation principles hold true for both compressible and incompressible flows
Ensuring conservation of mass, momentum, and energy is crucial for accurate modeling and simulation of fluid systems
Continuity equation mathematical expression of mass conservation in fluid dynamics
Differential form: ∂ ρ ∂ t + ∇ ⋅ ( ρ u ) = 0 \frac{\partial \rho}{\partial t} + \nabla \cdot (\rho \mathbf{u}) = 0 ∂ t ∂ ρ + ∇ ⋅ ( ρ u ) = 0
Integral form: ∂ ∂ t ∫ V ρ d V + ∫ S ρ u ⋅ n d S = 0 \frac{\partial}{\partial t} \int_V \rho dV + \int_S \rho \mathbf{u} \cdot \mathbf{n} dS = 0 ∂ t ∂ ∫ V ρ d V + ∫ S ρ u ⋅ n d S = 0
Momentum equation derived from Newton's second law and conservation of momentum
Differential form: ρ ( ∂ u ∂ t + u ⋅ ∇ u ) = − ∇ p + ∇ ⋅ T + ρ g \rho \left(\frac{\partial \mathbf{u}}{\partial t} + \mathbf{u} \cdot \nabla \mathbf{u}\right) = -\nabla p + \nabla \cdot \mathbf{T} + \rho \mathbf{g} ρ ( ∂ t ∂ u + u ⋅ ∇ u ) = − ∇ p + ∇ ⋅ T + ρ g
Integral form: ∂ ∂ t ∫ V ρ u d V + ∫ S ρ u ( u ⋅ n ) d S = − ∫ S p n d S + ∫ S T ⋅ n d S + ∫ V ρ g d V \frac{\partial}{\partial t} \int_V \rho \mathbf{u} dV + \int_S \rho \mathbf{u}(\mathbf{u} \cdot \mathbf{n}) dS = -\int_S p\mathbf{n} dS + \int_S \mathbf{T} \cdot \mathbf{n} dS + \int_V \rho \mathbf{g} dV ∂ t ∂ ∫ V ρ u d V + ∫ S ρ u ( u ⋅ n ) d S = − ∫ S p n d S + ∫ S T ⋅ n d S + ∫ V ρ g d V
Energy equation derived from the first law of thermodynamics and conservation of energy
Differential form: ρ ( ∂ e ∂ t + u ⋅ ∇ e ) = − p ∇ ⋅ u + ∇ ⋅ ( k ∇ T ) + Φ \rho \left(\frac{\partial e}{\partial t} + \mathbf{u} \cdot \nabla e\right) = -p\nabla \cdot \mathbf{u} + \nabla \cdot (k\nabla T) + \Phi ρ ( ∂ t ∂ e + u ⋅ ∇ e ) = − p ∇ ⋅ u + ∇ ⋅ ( k ∇ T ) + Φ
Integral form: ∂ ∂ t ∫ V ρ e d V + ∫ S ρ e ( u ⋅ n ) d S = − ∫ S p u ⋅ n d S + ∫ S k ∇ T ⋅ n d S + ∫ V Φ d V \frac{\partial}{\partial t} \int_V \rho e dV + \int_S \rho e(\mathbf{u} \cdot \mathbf{n}) dS = -\int_S p\mathbf{u} \cdot \mathbf{n} dS + \int_S k\nabla T \cdot \mathbf{n} dS + \int_V \Phi dV ∂ t ∂ ∫ V ρ e d V + ∫ S ρ e ( u ⋅ n ) d S = − ∫ S p u ⋅ n d S + ∫ S k ∇ T ⋅ n d S + ∫ V Φ d V
Navier-Stokes equations set of partial differential equations describing the motion of viscous fluids
Derived by combining the continuity, momentum, and energy equations
Boundary conditions specify the fluid behavior at the boundaries of the domain
Essential for obtaining unique solutions to the governing equations
Initial conditions define the state of the fluid system at the initial time (t = 0 t = 0 t = 0 )
Fluid Properties and Behavior
Density measure of mass per unit volume (ρ = m / V \rho = m/V ρ = m / V )
Constant for incompressible flows, variable for compressible flows
Viscosity measure of a fluid's resistance to deformation under shear stress
Newtonian fluids have a constant viscosity (water, air)
Non-Newtonian fluids have a viscosity that depends on shear rate (blood, paint)
Compressibility measure of a fluid's ability to change its volume under pressure
Incompressible fluids have a constant density (liquids)
Compressible fluids have a variable density (gases)
Turbulence chaotic and irregular motion characterized by rapid fluctuations in velocity and pressure
Occurs at high Reynolds numbers (R e = ρ U L μ Re = \frac{\rho UL}{\mu} R e = μ ρ UL )
Requires additional modeling techniques (turbulence models)
Boundary layers thin regions near solid surfaces where viscous effects are significant
Characterized by steep velocity gradients and shear stresses
Separation occurs when the boundary layer detaches from the surface due to adverse pressure gradients
Leads to recirculation zones and increased drag
Vorticity measure of the local rotation in a fluid (ω = ∇ × u \boldsymbol{\omega} = \nabla \times \mathbf{u} ω = ∇ × u )
Plays a crucial role in the formation and evolution of turbulent structures
Applications in Real-World Systems
Aerodynamics study of air flow around vehicles (aircraft, cars)
Focuses on lift, drag, and stability
Hydrodynamics study of water flow in pipes, channels, and open bodies of water
Includes hydraulic systems, river engineering, and coastal processes
Meteorology study of atmospheric flows and weather patterns
Involves modeling of wind, temperature, and moisture fields
Biomedical engineering study of blood flow in the cardiovascular system
Includes modeling of heart valves, arteries, and capillaries
Environmental engineering study of pollutant transport in air, water, and soil
Involves modeling of dispersion, advection, and reaction processes
Turbomachinery design and analysis of rotating machinery (turbines, compressors)
Focuses on efficiency, performance, and flow stability
Combustion modeling of chemical reactions and heat release in engines and furnaces
Involves coupling of fluid dynamics with chemical kinetics and thermodynamics
Problem-Solving Techniques
Analytical methods exact solutions to simplified versions of the governing equations
Useful for gaining physical insight and validating numerical methods
Numerical methods approximate solutions to the full governing equations
Finite difference methods discretize the domain into a structured grid
Finite volume methods discretize the domain into control volumes
Finite element methods discretize the domain into unstructured elements
Computational fluid dynamics (CFD) simulation of fluid flows using numerical methods
Requires discretization of the domain, boundary conditions, and initial conditions
Involves solving large systems of algebraic equations
Turbulence modeling techniques for approximating the effects of turbulence
Reynolds-averaged Navier-Stokes (RANS) models time-averaged equations with turbulence closure models
Large eddy simulation (LES) resolves large-scale turbulent structures and models small-scale structures
Direct numerical simulation (DNS) resolves all scales of turbulence without modeling
Verification process of ensuring that the numerical solution is accurate and converges to the exact solution
Involves grid refinement studies and comparison with analytical solutions
Validation process of ensuring that the numerical solution agrees with experimental data or real-world observations
Requires careful design of experiments and uncertainty quantification
Limitations and Assumptions
Continuum assumption treats fluids as continuous media rather than discrete particles
Breaks down at small scales (nanofluids) or low densities (rarefied gases)
Newtonian fluid assumption assumes a linear relationship between shear stress and strain rate
Not valid for non-Newtonian fluids (polymers, suspensions)
Incompressible flow assumption assumes constant density throughout the flow field
Not valid for high-speed flows or flows with large pressure variations
Steady flow assumption assumes no time dependence in the flow variables
Not valid for unsteady or transient flows
Laminar flow assumption assumes smooth and ordered flow without turbulence
Not valid for high Reynolds number flows or flows with instabilities
No-slip boundary condition assumes zero velocity at solid surfaces
Not valid for rarefied gases or flows with slip at the wall
Boussinesq approximation assumes small density variations only affect buoyancy terms
Not valid for flows with large temperature or concentration gradients
Advanced Topics and Extensions
Multiphase flows involve the interaction of multiple fluid phases (gas-liquid, solid-liquid)
Requires additional conservation equations and interface tracking methods
Non-Newtonian fluid mechanics study of fluids with complex rheological properties
Involves constitutive equations relating stress and strain rate
Turbulent reacting flows involve the interaction of turbulence and chemical reactions
Requires modeling of turbulence-chemistry interaction and scalar transport
Magnetohydrodynamics (MHD) study of electrically conducting fluids in the presence of magnetic fields
Involves coupling of fluid dynamics with Maxwell's equations
Micro- and nanoscale flows involve fluid behavior at small scales
Requires consideration of non-continuum effects and surface interactions
High-performance computing (HPC) techniques for large-scale CFD simulations
Involves parallel computing, domain decomposition, and scalable algorithms
Uncertainty quantification (UQ) methods for assessing the impact of input uncertainties on simulation results
Includes sensitivity analysis, polynomial chaos expansions, and Bayesian inference