Error transport equation boundary conditions for the Euler and Navier-Stokes equations

Discretization error is usually the largest and most difficult numerical error source to estimate for computational fluid dynamics, and boundary conditions often contribute a significant source of error. Boundary conditions are described with a governing equation to prescribe particular behavior at the boundary of a computational domain. Boundary condition implementations are considered sufficient when discretized with the same order of accuracy as the primary governing equations; however, careless implementations of boundary conditions can result in significantly larger numerical error. Investigations into different numerical implementations of Dirichlet and Neumann boundary conditions for Burgers' equation show a significant impact on the accuracy of Richardson extrapolation and error transport equation discretization error estimates. The development of boundary conditions for Burgers' equation shows significant improvements in discretization error estimates in general and a significant improvement in truncation error estimation. The latter of which is key to accurate residual-based discretization error estimation. This research investigates scheme consistent and scheme inconsistent implementations of inflow and outflow boundary conditions up to fourth order accurate and a formulation for a slip wall boundary condition for truncation error estimation are developed for the Navier-Stokes and Euler equations. The scheme consistent implementation resulted in much smoother truncation error near the boundaries and more accurate discretization error estimates.

[1]  I. Babuska,et al.  A‐posteriori error estimates for the finite element method , 1978 .

[2]  B. Leer,et al.  Flux-vector splitting for the Euler equations , 1997 .

[3]  Tom I-P. Shih,et al.  A discrete transport equation for error estimation in CFD , 2002 .

[4]  Peter A. Cavallo,et al.  Viscous Error Transport Equation for Error Quantification of Turbulent Flows , 2008 .

[5]  E. Fehlberg,et al.  Low-order classical Runge-Kutta formulas with stepsize control and their application to some heat transfer problems , 1969 .

[6]  J. Z. Zhu,et al.  The superconvergent patch recovery and a posteriori error estimates. Part 2: Error estimates and adaptivity , 1992 .

[7]  C. J. Roy Strategies for Driving Mesh Adaptation in CFD (Invited) , 2009 .

[8]  Carl Ollivier-Gooch,et al.  Obtaining and Verifying High-Order Unstructured Finite Volume Solutions to the Euler Equations , 2009 .

[9]  C. W. Clenshaw,et al.  A method for numerical integration on an automatic computer , 1960 .

[10]  E. Stiefel Note on Jordan elimination, linear programming and Tchebycheff approximation , 1960 .

[11]  L. Richardson The Approximate Arithmetical Solution by Finite Differences of Physical Problems Involving Differential Equations, with an Application to the Stresses in a Masonry Dam , 1911 .

[12]  Richard Dwight,et al.  Algebraic multigrid within defect correction for the linearized Euler equations , 2010, Numer. Linear Algebra Appl..

[13]  J. Oden,et al.  A Posteriori Error Estimation in Finite Element Analysis , 2000 .

[14]  R. Skeel Thirteen ways to estimate global error , 1986 .

[15]  Christopher J. Roy,et al.  Review of Discretization Error Estimators in Scientific Computing , 2010 .

[16]  Dominique Pelletier,et al.  VERIFICATION OF ERROR ESTIMATORS FOR THE EULER EQUATIONS , 2000 .

[17]  Christopher J. Roy,et al.  Structured Mesh r-Refinement using Truncation Error Equidistribution for 1D and 2D Euler Problems , 2013 .

[18]  Christopher J. Roy,et al.  Residual Methods for Discretization Error Estimation , 2011 .

[19]  Christopher J. Roy,et al.  Finite Volume Solution Reconstruction Methods For Truncation Error Estimation , 2013 .

[20]  J. Oden,et al.  A Posteriori Error Estimation in Finite Element Analysis: Oden/A Posteriori , 2000 .

[21]  Yuehui Qin,et al.  A Method for Estimating Grid-Induced Errors in Finite-Difference and Finite-Volume Methods , 2003 .

[22]  H. Stetter The defect correction principle and discretization methods , 1978 .

[23]  B. Williams Development and Evaluation of an à Posteriori Method for Estimating and Correcting GridInduced Errors in Solutions of the NavierStokes Equations , 2009 .

[24]  Christopher J. Roy,et al.  SENSEI Computational Fluid Dynamics Code: A Case Study in Modern Fortran Software Development , 2013 .

[25]  V. Pereyra On improving an approximate solution of a functional equation by deferred corrections , 1966 .

[26]  O. C. Zienkiewicz,et al.  A simple error estimator and adaptive procedure for practical engineerng analysis , 1987 .

[27]  S. Richards Completed Richardson extrapolation in space and time , 1997 .

[28]  Christopher J. Roy,et al.  Verification and Validation in Scientific Computing , 2010 .

[29]  Antony Jameson,et al.  Aerodynamic design via control theory , 1988, J. Sci. Comput..

[30]  Gusheng Hu,et al.  Single Grid Error Estimation Using Error Transport Equation , 2004 .

[31]  Michael B. Giles,et al.  Adjoint Recovery of Superconvergent Functionals from PDE Approximations , 2000, SIAM Rev..

[32]  Peter A. Cavallo,et al.  An Error Transport Equation with Practical Applications , 2007 .

[33]  W. Rheinboldt,et al.  Error Estimates for Adaptive Finite Element Computations , 1978 .

[34]  T. Shih,et al.  Modeling the Residual in Error-Transport Equations for Estimating Grid-Induced Errors in CFD Solutions , 2006 .

[35]  William J. Rider,et al.  On sub-linear convergence for linearly degenerate waves in capturing schemes , 2008, J. Comput. Phys..

[36]  P. Knupp,et al.  Completed Richardson extrapolation , 1993 .