Page History

• Nonlinear solver:
  • Newton
• Linear solver:
  • Proconditioner: Block Jacobi
  • Side: Left
• Serial results:
  • Residual norm converges to 4.3571·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Preconditioner: Block Jacobi
  • Side: Right
• Results:
  • Residual norm converges to 4.3532·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Preconditioner: Incomplete LU (0)
  • Reordering type: Minimum discarded fill
  • Side: Left
• Serial results:
  • Residual norm converges to 4.3566·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts
• Parallel results:
  • Residual norm converges to 4.3501·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Preconditioner:Threshold-based Incomplete LU (ILUT)
  • Reordering type: Minimum discarded fill
  • Side: Right
  • Drop threshold: 10^-3
• Serial results:
  • Residual norm converges to 4.3538·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts
• Parallel results:
  • Residual norm converges to 4.3539·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Incomplete LU (0) (left) preconditioner
    • Reordering type: Minimum discarded fill
    • Side: Right
  • P = 0 linear multigrid for coarse correction
• Serial results:
  • Residual norm converges to 3.8091·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts
• Parallel results:
  • Residual norm converges to 4.3501·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Preconditioner: Incomplete LU (ILU)
  • Parallel preconditioner: Additive Schwarz Method (ASM)
  • Side: Right
  • Reordering type: Minimum discarded fill
  • Outer GMRES iterations: 2
  • Inner GMRES iterations: 20
• Parallel results (without multigrid):
  • Residual norm converges to 4.3736·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts
• Parallel results (with multigrid):
  • Residual norm converges to 3.8106·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Preconditioner: Threshold-based Incomplete LU
  • Side: Right
  • Reordering type: Minimum discarded fill
• Serial results:
  • Residual norm converges to 4.3559·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts
• Parallel results:
  • Residual norm converges to 4.3506·10^-13 after 5 iterations
  • Drag coefficient: C_D = .5318 counts
  • Lift coefficient: C_L = .9638 counts

• Nonlinear solver:
  • Lean Jacobi
• Linear solver:
  • Preconditioner: None
• Serial results:
  • Residual norm converges to 4.7345·10^-4 after 200 iterations
  • Drag coefficient: C_D = .5098 counts
  • Lift coefficient: C_L = .9478 counts
• Parallel results:
  • Residual norm converges to 4.7345·10^-4 after 200 iterations
  • Drag coefficient: C_D = .5098 counts
  • Lift coefficient: C_L = .9478 counts

• Nonlinear solver:
  • Newton
• Linear solver:
  • Preconditioner: Threshold-based Incomplete LU
  • Side: Left
  • Reordering type: Minimum discarded fill
• Serial results:
  • Residual norm converges to 5.6482·10^-14 after 38 iterations
  • Drag coefficient: C_D = .5319 counts
  • Lift coefficient: C_L = .9653 counts

Listed below are the tolerances for the relevant data compared in the history files:

• Number of degrees of freedom on adapted meshes: 1
• Error indicator: 10^-12
• Error estimate: 10^-12
• Drag: 10^-12

For the primal solution, please refer to the Newton-ILU case above (with Nonlinear solver iterations limited to 50)

• Adjoint parameters:
  • Adjoint output: Drag
  • Patch Reconstruction H1: False
  • Hessian Scalar Type: -1
    (Mach number for Hessian evaluation)
  • Nonlinear Smoother: Newton (solved to 10^-6)
  • Adjoint Smoother residual converged to 10^-6
  • Primal truth surrogate not fully converged
  • Adjoint truth fully converged
• Adaptation parameters:
  • Output Adapted: Drag
  • Anisotropy method: Hessian
  • Curved re-meshing method: Boundary-curved
  • Number of adaptation iterations: 2
  • hp adaptation space
  • Adaptation algorithm: Fixed-Fraction marking
    • 30% refining and 20% coarsening fractions
    • Target degree-of-freedom increase factor: 1.0 (constant DOF)
  • Forward sensitivities are computed
    (i.e. dC_D/dα with a tangent linearization)
• Serial results:
  • Initial mesh:
    • DOF = 990
    • Error estimate = 3.9138·10^-4
    • Drag = 5.3180·10^-4
  • First adaptation:
    • DOF = 1008
    • Error estimate = 1.9066·10^-4
    • Drag = 2.6942·10^-4
  • Second adaptation:
    • DOF = 1026
    • Error estimate = 1.3617·10^-4
    • Drag = 2.0600·10^-4

• Almost all parameters are identical to the boundary-curved adaptation test. The only differing parameters are:
  • Target degree-of-freedom increase factor: 1.25
  • Curved re-meshing type: Elasticity
• Serial results:
  • Initial mesh:
    • DOF = 990
    • Error estimate = 3.9138·10^-4
    • Drag = 5.3180·10^-4
  • First adaptation:
    • DOF = 1008
    • Error estimate = 1.8590·10^-4
    • Drag = 2.6109·10^-4
  • Second adaptation:
    • DOF = 1278
    • Error estimate = 8.5377·10^-5
    • Drag = 1.3336·10^-4