AIAA Journal · 2012 · 37 citations · 34 references
EngineeringAerospace EngineeringMechanical EngineeringAerodynamicsComputational Fluid DynamicsFluid DynamicsAdaptive Mesh RefinementComputational AerodynamicsError EstimationFinite Volume MethodsGrid AdaptationAdjoint-based Error EstimationFinite Volume DiscretizationFinite-volume Mesh AdaptationMesh AdaptationMesh RefinementMesh Refinement TechniquesTruncation ErrorTruncation Error Analysis
Mesh adaptation driven by error estimation is essential for accurate CFD, yet adjoint‑based methods, though promising, remain underused in industry due to high computational cost. This study introduces a new mesh refinement technique that estimates truncation error within a finite‑volume framework. The approach employs auxiliary coarser meshes to compute local truncation error, guiding the adaptation algorithm. When applied to 2‑D NACA0012 and 3‑D ONERA M6 wing inviscid flows, the method matches or exceeds the performance of adjoint‑based and sensor‑based refinement, demonstrating its effectiveness.
Mesh adaptation based on error estimation has become a key technique to improve th eaccuracy o fcomputational-fluid-dynamics computations. The adjoint-based approach for error estimation is one of the most promising techniques for computational-fluid-dynamics applications. Nevertheless, the level of implementation of this technique in the aeronautical industrial environment is still low because it is a computationally expensive method. In the present investigation, a new mesh refinement method based on estimation of truncation error is presented in the context of finite-volume discretization. The estimation method uses auxiliary coarser meshes to estimate the local truncation error, which can be used for driving an adaptation algorithm. The method is demonstrated in the context of two-dimensional NACA0012 and three-dimensional ONERA M6 wing inviscid flows, and the results are compared against the adjoint-based approach and physical sensors based on features of the flow field.
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Adaptive remeshing for compressible flow computations
J. Peraire, Mehdi Vahdati, K. Morgan et al. · Journal of Computational Physics · 1987 · 1K citations
Grid convergence for adaptive methods
Gary P. Warren, W. Kyle Anderson, James L. Thomas et al. · 1991 · 134 citations