Solvers and Pressure-Velocity in CFD: Part 2

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  • Comprehensive exploration of density-based solver methods in CFD, focusing on mathematical foundations and practical implementations.
  • Detailed explanation of fundamental equations including continuity, momentum, and energy equations with their complete derivations.
  • In-depth coverage of time-derivative preconditioning and its importance in handling low Mach number flows.
  • Comparison between AUSM and Roe schemes, including both explicit and implicit formulations.
  • Practical guidelines for implementation in ANSYS Fluent, including time step selection and stability considerations.
  • Advanced numerical techniques for pressure-velocity coupling, with emphasis on matrix formulation and eigenvalue calculations.
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Description

Advanced Guide to Solvers and Pressure-Velocity Coupling in CFD – Part 2

Introduction

Welcome to the fourth session of our Computational Fluid Dynamics series by the MR-CFD team. This comprehensive guide continues our exploration of solver types and pressure-velocity coupling methods, with a specific focus on density-based methods in CFD simulations.

Density-Based vs. Pressure-Based Methods

While pressure-based methods offer both segregated and coupled algorithms with implicit formulations, density-based methods exclusively use coupled approaches. In ANSYS Fluent, density-based solvers provide both implicit and explicit formulation options.

Mathematical Foundation

Continuity Equation

The differential form of the continuity equation uses uppercase V to represent the velocity vector, containing components:

  • U in X direction
  • V in Y direction
  • W in Z direction

Momentum Equations

For x-momentum, we start with the differential equation where:

  • First derivative of (ρU) with respect to (t)
  • Divergence of (ρ velocity vector U)
  • Equal to divergence of (τx i)
  • Minus first derivative of pressure with respect to (x)
  • Plus source term for x momentum

Energy Equation

The differential equation for energy can be written as:

  • First derivative of (ρE) with respect to time
  • Plus divergence of (ρVE)
  • Equal to divergence of K (thermal conductivity)
  • Multiplied by gradient of E

Preconditioning Matrix

The choice of primitive variables Q as dependent variables offers several advantages:

  • Natural choice for incompressible flows
  • Better accuracy for second-order calculations
  • Allows isolation of acoustic wave propagation

Roe Scheme Formulation

The fundamental formulation of the Roe scheme provides a mathematical basis for computing numerical fluxes at cell interfaces. Key considerations include:

  • Conservation equation in differential form
  • Approximation using locally constant matrix
  • Linear mapping requirements

Matrix Formulation and Eigenvalues

The matrix A tilde can be diagonalized as:

A tilde = S × Lambda × S^(-1)

Where:

  • Lambda is a diagonal matrix of eigenvalues: (U-c, U, U, U, U+c)
  • S contains right eigenvectors
  • S^(-1) contains left eigenvectors

Interface Value Calculations

For interface calculations, we define:

  • Lambda negative = Lambda – |Lambda|/2
  • Lambda positive = Lambda + |Lambda|/2

Flux Calculations

The flux F at the interface is calculated using:

F = F_right - S × Lambda_positive × S^(-1) × (Q_right - Q_left)

Or alternatively:

F = F_left + S × Lambda_negative × S^(-1) × (Q_right - Q_left)

AUSM and Roe Scheme Comparison

Feature AUSM Explicit AUSM Implicit Roe Model Explicit Roe Model Implicit
Basic Principle Splits convective and pressure terms Simultaneous equation solving Riemann problem linearization Implicit Riemann solution
Stability CFL dependent More stable CFL dependent More stable

Implementation Guidelines

Explicit Formulation

For explicit calculations:

ΔQ = α(I^(-1)γΔt)R^(i-1)

Implicit Formulation

For implicit calculations:

  • All values taken from next iteration
  • System of equations must be solved simultaneously
  • Higher computational cost per iteration

Practical Considerations

Time Step Selection

Time step calculation:

Δt = 2 × CFL × V / (λ_max × A_F)

Where:

  • CFL = Courant number
  • V = Cell volume
  • λ_max = Maximum local eigenvalue
  • A_F = Face area

Conclusion

This comprehensive guide has covered:

  • Fundamental formulations for density-based solvers
  • Pressure-velocity coupling mechanisms
  • Mathematical derivations and practical implementations
  • Comparison of different numerical schemes

Next Steps

In the next session, we will explore:

  • Discretization methods for property implementation
  • Practical examples and case studies
  • Advanced troubleshooting techniques

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