Navier-Stokes Equations and PDE Classification Notes

Classification of Partial Differential Equations (PDEs)

  • Navier-Stokes Equations (NSE):

    • Describe motion of fluid substances.
    • Set of nonlinear partial differential equations (PDEs) derived from conservation principles (mass, momentum, energy).

  • Classification of PDEs:

    • Based on characteristics of flow and governing equations.
    • General classification includes Elliptic, Parabolic, and Hyperbolic.
Types of PDEs

  • General Form:
    aφ<em>xx+bφ</em>xy+cφ<em>yy+dφ</em>x+eφy+fφ+g=0a\varphi<em>{xx} + b\varphi</em>{xy} + c\varphi<em>{yy} + d\varphi</em>{x} + e\varphi_{y} + f\varphi + g = 0

  • Classifications:

    • Parabolic: if $b^2 - 4ac = 0$
    • Hyperbolic: if $b^2 - 4ac > 0$
    • Elliptic: if $b^2 - 4ac < 0$
Importance of Classification in CFD
  • Determines behavior of flow or thermal solutions.
  • Numerical methods must be appropriate and stable according to the PDE type.
  • Switching type may occur depending on boundary conditions (e.g., supersonic vs. subsonic conditions).
Flow and Heat Transfer Types
  • Classification by Flow Type:
    • Hyperbolic:
    • Example: Inviscid, compressible flows (shock waves, supersonic flow).
    • Information propagates like a wave.
    • Parabolic:
    • Example: Unsteady flows (boundary-layer flows).
    • Solution driven by initial and boundary conditions.
    • Elliptic:
    • Example: Steady-state incompressible flows (potential flow).
    • Information propagates infinitely in all directions.
Mathematical Definitions of Domains
  • Hyperbolic: Open sets and no diffusion; capable of existing discontinuities.
  • Parabolic: Open sets with diffusion, related to time domain.
  • Elliptic: Closed boundary-value problems.

Model Equations

  • Special cases of full NSE with simpler characteristics. Fundamental for validation of numerical algorithms.
  • Common Model Equations:
    • 1-D Wave Equations (2nd Order):
      ∂2ϕ∂t2=c2∂2ϕ∂x2\frac{\partial^2 \phi}{\partial t^2} = c^2 \frac{\partial^2 \phi}{\partial x^2} (Hyperbolic)
    • 1-D Wave Equations (1st Order):
      ∂ϕ∂t+c∂ϕ∂x=0\frac{\partial \phi}{\partial t} + c \frac{\partial \phi}{\partial x} = 0 (Hyperbolic, Linear)
    • 1-D Unsteady Advection-Diffusion Equation:
      ∂ϕ∂t+U∂ϕ∂x=α∂2ϕ∂x2\frac{\partial \phi}{\partial t} + U \frac{\partial \phi}{\partial x} = \alpha \frac{\partial^2 \phi}{\partial x^2} (Parabolic)
    • Burgers Equation:
      ∂ϕ∂t+ϕ∂ϕ∂x=<br/>ν∂2ϕ∂x2\frac{\partial \phi}{\partial t} + \phi \frac{\partial \phi}{\partial x} = <br />\nu \frac{\partial^2 \phi}{\partial x^2} (Parabolic)

Approximate Equations

  • Approximation of NSE:
    • Allows neglecting certain terms leading to simpler solutions.
  • Examples:
    • 2-D Steady Velocity Potential Equation:
    • (1−M2)(∂2ϕ∂x2+∂2ϕ∂y2)=0(1 - M^2) \left( \frac{\partial^2 \phi}{\partial x^2} + \frac{\partial^2 \phi}{\partial y^2} \right) = 0 (Elliptic, Parabolic, Hyperbolic depending on M)
    • Euler Equations (Inviscid and Non-linear):
    • DV+ρ∇⋅V=0 and DV=−1ρ∇p+fD\mathbf{V} + \rho \nabla \cdot \mathbf{V} = 0 \text{ and } D\mathbf{V} = -\frac{1}{\rho} \nabla p + \mathbf{f} (Elliptic/Subsonic, Hyperbolic/Supersonic)

Turbulence and Reynolds Averaging

  • Reynolds Averaging in NSE leads to turbulent terms requiring modeling.
  • Key process in achieving accurate simulations in fluid dynamics.

Conclusion

  • Understanding the classification of PDEs is fundamental in fluid dynamics and aids in developing stable numerical methods and tailored solution algorithms for specific phenomena. The Navier-Stokes equations, as multifunctional mathematical representations, serve as the backbone in modeling real-world fluid motion and behavior across various applications.