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Table of Contents

  • 1. Quick Start
    • 1.1. Introduction to Flow360
    • 1.2. ONERA M6 Wing with WebUI
    • 1.3. ONERA M6 Wing with Python API
    • 1.4. Automated Meshing with WebUI
    • 1.5. Automated Meshing with Python API
    • 1.6. NREL S809 Airfoil
    • 1.7. XV-15 Rotor
  • 2. Capabilities
    • 2.1. Overview
    • 2.2. Feature Compatibility Matrix
    • 2.3. Propeller Models and Sliding Interfaces
    • 2.4. User Defined Dynamics
  • 3. Preprocessing
    • 3.1. Engineering Sketch Pad
    • 3.2. Automated Meshing
  • 4. Solver Configuration
  • 5. Python API Reference
  • 6. Case Studies
    • 6.1. NACA 0012 Low Speed Airfoil
    • 6.2. 2D NACA 4412 Airfoil Trailing Edge Separation
    • 6.3. 2D Backward Facing Step
    • 6.4. Transition Modeling
    • 6.5. High Lift Common Research Model (HL-CRM)
    • 6.6. Drag Prediction of Common Research Model
    • 6.7. ONERA M6 Wing
    • 6.8. XV-15 Rotor Blade Analysis using the Blade Element Disk Method
    • 6.9. DTU 10MW Wind Turbine
  • 7. Tutorials
    • 7.1. Geometry Modeling and Preparation for Automated Meshing: An Example of the ONERA M6 Wing
    • 7.2. Non-Dimensionalization and Integrated Loads Post-Processing in Flow360
    • 7.3. RANS CFD on 2D High-Lift System Configuration Using the Flow360 Python Client
    • 7.4. Blade Element Theory using the XV-15 rotor
    • 7.5. Time-accurate RANS CFD on a propeller using a sliding interface: the XV-15 rotor geometry
  • 8. Knowledge Base
    • 8.1. Preprocessing
      • 8.1.1. Meshing Recommendations
      • 8.1.2. Nondimensional Inputs
      • 8.1.3. BET Translators
      • 8.1.4. SectionalPolars Best Practices.
    • 8.2. Simulation
      • 8.2.1. timeStepping
      • 8.2.2. BETDisks
      • 8.2.3. navierStokesSolver
      • 8.2.4. turbulenceModelSolver
      • 8.2.5. slidingInterfaces
    • 8.3. Postprocessing
    • 8.4. Fixing Divergence Issues
    • 8.5. Frequently Asked Questions
  • 9. Publications
    • 9.1. Webinar
    • 9.2. Papers
  • 10. Release Notes
Theme by the Executable Book Project
  • .rst
Contents
  • 8.2.3.1. relativeTolerance
  • 8.2.3.2. kappaMUSCL
  • 8.2.3.3. orderOfAccuracy
  • 8.2.3.4. Limiters
  • 8.2.3.5. linearIterations
  • 8.2.3.6. updateJacobianFrequency

navierStokesSolver

Contents

  • 8.2.3.1. relativeTolerance
  • 8.2.3.2. kappaMUSCL
  • 8.2.3.3. orderOfAccuracy
  • 8.2.3.4. Limiters
  • 8.2.3.5. linearIterations
  • 8.2.3.6. updateJacobianFrequency

8.2.3. navierStokesSolver#

8.2.3.1. relativeTolerance#

When running unsteady cases, the relativeTolerance is typically set to 1e-2 or 1e-3. Once the nonlinear residuals drop by 2 or 3 orders of magnitude, the solver will continue to the next physical step. The relativeTolerance is ignored for steady cases.

8.2.3.2. kappaMUSCL#

The default value of -1 leads to a second-order upwind scheme, which is the most stable. A value of 0.33 leads to a blended upwind/central scheme, which is recommended for low subsonic flows to reduce dissipation.

8.2.3.3. orderOfAccuracy#

The orderOfAccuracy determines whether the solver will use 1st or 2nd order spatial discretization. The 1st order solver is faster, cheaper and most importantly, it is more dissipative, making it less likely to diverge. However, such numerical dissipation may also significantly impact the accuracy of the solution.

When initializing the flow field for unsteady cases with rotating components, such as simulating a rotor enclosed in a sliding interface, the user typically needs to run the 1st-order solver for around 1 or 2 revolutions. Once the flow field has been initialized, the user can fork the first-order case and switch orderOfAccuracy from 1 to 2 for the child cases.

While adjusting the orderOfAccuracy for the navierStokesSolver, the turbulenceModelSolver should also be adjusted.

The recommended timeStepping is slightly different for the 1st and 2nd order cases. For more details, see Rotational Angle per Step, maxPseudoSteps and CFL

8.2.3.4. Limiters#

If the case is transonic or supersonic, the user should set limitVelocity and limitPressureDensity as TRUE in the Navier Stokes solver parameters section of their input file.

8.2.3.5. linearIterations#

linearIterations controls the number of linear iterations in each pseudo-step. Typically, linearIterations is set to 25~35 for the NS solver. The user might need to increase it to 50-55 for challenging cases to improve convergence.

8.2.3.6. updateJacobianFrequency#

The default value for updateJacobianFrequency is 4, which means that the Jacobian for evaluating the NS equation is updated every 4 pseudo-steps. For some challenging cases, reducing updateJacobianFrequency from 4 to 1 may help, however, this may slow the NS solver by up to approximately 30%.

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8.2.2. BETDisks

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8.2.4. turbulenceModelSolver

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