Solution Adaptive Mesh Generation Using Feature-Aligned Embedded Surface Meshes

Ito, Yasushi; Shih, Alan M.; Koomullil, Roy P.; Kasmai, N.; Jankun-Kelly, Monika; Thompson, David S.

doi:10.2514/1.39378

Cited by 20 publications

(14 citation statements)

References 21 publications

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“…Daso et al 16 did not report any three-dimensionality effects for the zero angle of attack cases, and hence assumption of an axisymmetric flow is valid. With triangular meshes being the preferred grid topology for the CESE framework, unstructured triangular meshes, generated by GRIDGEN ® and University of Alabama at Birmingham's in-house code, the Mixed-Element Grid Generator in 3 Dimensions (MEGG3D), 28,29 have been utilized in this study. The meshes for all the computations here have been generated based on our previous experience.…”

Section: Resultsmentioning

confidence: 99%

Numerical Investigation of the Interaction of Counterflowing Jets and Supersonic Capsule Flows

Venkatachari

Ito

Cheng

et al. 2011

42nd AIAA Thermophysics Conference

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Section: Resultsmentioning

confidence: 99%

Numerical Investigation of the Interaction of Counterflowing Jets and Supersonic Capsule Flows

Venkatachari

Ito

Cheng

et al. 2011

42nd AIAA Thermophysics Conference

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“…Figure 17(d) shows the best agreement with the experimental data. Table I shows the non-dimensional location of the vortex core, as defined by the location at which the crossflow velocity is a minimum, for selected refinement cycles and from other simulation results [42,59]. Here, /c is the non-dimensional nominal mesh spacing in the region near the vortex core.…”

Section: Results For Wing In Wind Tunnelmentioning

confidence: 99%

“…Here, /c is the non-dimensional nominal mesh spacing in the region near the vortex core. Ito et al [42] employed an adaptive mesh regeneration strategy that used embedded surfaces to control the point spacing in the interior of the domain while Luke et al [59] used a priori mesh refinement in the region near the wing in which it was anticipated that the wingtip vortex would occur. In both cases, the vortex core position was extracted from the simulation data.…”

Section: Results For Wing In Wind Tunnelmentioning

confidence: 99%

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Feature‐based adaptive mesh refinement for wingtip vortices

Kasmai

Thompson

Luke

et al. 2011

Numerical Methods in Fluids

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SUMMARYFeature-based solution-adaptive mesh refinement is an attractive strategy when it is known a priori that the resolution of certain key features is critical to achieving the objectives of a simulation. In this paper, we apply vortex characterization techniques, which are typically employed to visualize vortices, to identify regions of the computational domain for mesh refinement. We investigate different refinement strategies that are facilitated by these vortex characterization techniques to simulate the flow past a wing in a wind tunnel. Our results, which we compare with experimental data, indicate that it is necessary to refine the region within and near the vortex extent surface to obtain an accurate prediction. Application of the identified mesh refinement strategy also produced observed improvement in the results predicted for a spinning missile with deflected canards.

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“…A number of approaches have targeted a feature of the flow for refinement (e.g., vorticity). 86,119,[146][147][148] These methods clearly improve the resolution of these features, but there is no guarantee that the features are not displaced by discretization errors elsewhere in the domain or that resolving these features improve the accuracy of integrated forces and moments. For example, Warren et al 83 show that an adaptation indicator like the norm of the gradient may predict the wrong location of a shock given coarse initial grids.…”

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confidence: 99%

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Towards CFD 2030

Park

Krakos

Michal

et al. 2016

46th AIAA Fluid Dynamics Conference

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Unstructured grid adaptation is a powerful tool to control Computational Fluid Dynamics (CFD) discretization error. It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provide a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The study authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity will continue to be significant bottlenecks in the CFD workflow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to di↵use grid adaptation technology into production CFD work flows.

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Solution Adaptive Mesh Generation Using Feature-Aligned Embedded Surface Meshes

Cited by 20 publications

References 21 publications

Numerical Investigation of the Interaction of Counterflowing Jets and Supersonic Capsule Flows

Numerical Investigation of the Interaction of Counterflowing Jets and Supersonic Capsule Flows

Feature‐based adaptive mesh refinement for wingtip vortices

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Towards CFD 2030

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