An overset mesh approach for 3D mixed element high-order discretizations

Brazell, Michael; Sitaraman, Jayanarayanan; Mavriplis, Dimitri J.

doi:10.1016/j.jcp.2016.06.031

Cited by 67 publications

(12 citation statements)

References 41 publications

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“…3 The overset grid method was first used in finite-difference structured CFD codes back in 1980s, 1 the 1990s saw the first implementations for structured-grid finite volume codes for maritime applications. 4 Currently, unstructured-grid finite volume codes [5][6][7][8][9] and higher-order finite element codes 10 often have an overset grid capabilities. In the current work, the overset grid technique is studied for face-based unstructured-grid finite volume viscous-flow codes, particularly for incompressible hydrodynamic flows at high Reynolds numbers.…”

Section: Introductionmentioning

confidence: 99%

On the accuracy, robustness, and performance of high order interpolation schemes for the overset method on unstructured grids

Lemaire

Vaz

Rijswijk

et al. 2021

Numerical Methods in Fluids

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A comprehensive study on interpolation schemes used in overset grid techniques is here presented. Based on a literature review, numerous schemes are implemented, and their robustness, accuracy, and performance are assessed. Two code verification exercises are performed for this purpose: a 2D analytical solution of a laminar Poiseuille steady flow; and an intricate manufactured solution of a turbulent flow case, characteristic of a boundary layer flow combined with an unsteady separation bubble. For both cases, the influence of grid layouts, grid refinement, and time-step is investigated. Local and global errors, convergence orders, and mass imbalance are quantified. In terms of computational performance, strong scalability, cpu timings, load imbalancing, and domain connectivity information (DCI) overhead are reported. The effect of the overset-grid interpolation schemes on the numerical performance of the solver, that is, number of nonlinear iterations, is also scrutinized. The results show that, for a second order finite volume code, once diffusion is dominant (low Reynolds number), interpolation schemes higher than second order, for example, least squares of degree 2, are needed not to increase the total discretization errors. For convection dominated flows (high Reynolds numbers), the results suggest that second order schemes, for example, nearest cell gradient, are sufficient to prevent overset grid schemes to taint the underlying discretization errors. In terms of performance, by single-process and parallel communication optimization, the total overset-grid overhead (with DCI done externally to the CFD code) may be less than 4% of the total run time for second-order schemes and 8% for third-order ones, therefore empowering higher-order schemes and more accurate solutions.

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Section: Introductionmentioning

confidence: 99%

On the accuracy, robustness, and performance of high order interpolation schemes for the overset method on unstructured grids

Lemaire

Vaz

Rijswijk

et al. 2021

Numerical Methods in Fluids

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show abstract

“…Overset-grid methods are also included in commercial and research software packages such as Star-CCM [12], Overflow [13] and Overture [14]. Most of these implementations, however, are at most fourthorder accurate in space [9,11,15,16,17,18]. Sixth-order finite-difference based methods have been presented in [19,13], while sixthorder finite volume based schemes are available in elsA [20].…”

Section: Introductionmentioning

confidence: 99%

Nonconforming Schwarz-spectral element methods for incompressible flow

2019

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We present scalable implementations of spectral-element-based Schwarz overlapping (overset) methods for the incompressible Navier-Stokes (NS) equations. Our SEM-based overset grid method is implemented at the level of the NS equations, which are advanced independently within separate subdomains using interdomain velocity and pressure boundarydata exchanges at each timestep or sub-timestep. Central to this implementation is a general, robust, and scalable interpolation routine, gslib-findpts, that rapidly determines the computational coordinates (processor p, element number e, and local coordinates (r, s, t) ∈Ω := [−1, 1] 3 ) for any arbitrary point x * = (x * , y * , z * ) ∈ Ω ⊂ lR 3 . The communication kernels in gslib execute with at most log P complexity for P MPI ranks, have scaled to P > 10 6 , and obviate the need for development of any additional MPI-based code for the Schwarz implementation. The original interpolation routine has been extended to account for multiple overlapping domains. The new implementation discriminates the possessing subdomain by distance to the domain boundary, such that the interface boundary data is taken from the inner-most interior points. We present application of this approach to several heat transfer and fluid dynamic problems, discuss the computation/communication complexity and accuracy of the approach, and present performance measurements for P > 12, 000.

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“…The use of a static linear basis for ROM in Ω A limits its predictive capabilities. It is pointed out that the interface mismatches are not unique to ROM/FOM coupling, but more general issues for finite-element [73] and finite-volume [74] methods, especially with non-matching grids (i.e., inconsistent orders of modeling accuracy)-for example, the coupling of low-and high-order CFD solvers (FOMs) may require-for example-an overset-mesh approach [21,75]. Though such methods can be effective in coupling of low-and high-order FOMs, it is not clear whether such methods can be applied directly to ROM and FOM coupling since ROM evolves on a reduced dimensional trajectory determined by the basis, while the FOM (either with low-or high-order numerical methods) solves the dynamical system on the full state space trajectory.…”

Section: Performancementioning

confidence: 99%

Component-Based Reduced Order Modeling of Large-Scale Complex Systems

2022

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Large-scale engineering systems, such as propulsive engines, ship structures, and wind farms, feature complex, multi-scale interactions between multiple physical phenomena. Characterizing the operation and performance of such systems requires detailed computational models. Even with advances in modern computational capabilities, however, high-fidelity (e.g., large eddy) simulations of such a system remain out of reach. In this work, we develop a reduced‐order modeling framework to enable accurate predictions of large-scale systems. We target engineering systems which are difficult to simulate at a high-enough level of fidelity, but are decomposable into different components. These components can be modeled using a combination of strategies, such as reduced-order models (ROM) or reduced-fidelity full-order models (RF-FOM). Component-based training strategies are developed to construct ROMs for each individual component. These ROMs are then integrated to represent the full system. Notably, this approach only requires high-fidelity simulations of a much smaller computational domain. System-level responses are mimicked via external boundary forcing during training. Model reduction is accomplished using model-form preserving least-squares projections with variable transformation (MP-LSVT) (Huang et al., Journal of Computational Physics, 2022, 448: 110742). Predictive capabilities are greatly enhanced by developing adaptive bases which are locally linear in time. The trained ROMs are then coupled and integrated into the framework to model the full large-scale system. We apply the methodology to extremely complex flow physics involving combustion dynamics. With the use of the adaptive basis, the framework is demonstrated to accurately predict local pressure oscillations, time-averaged and RMS fields of target state variables, even with geometric changes.

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An overset mesh approach for 3D mixed element high-order discretizations

Cited by 67 publications

References 41 publications

On the accuracy, robustness, and performance of high order interpolation schemes for the overset method on unstructured grids

On the accuracy, robustness, and performance of high order interpolation schemes for the overset method on unstructured grids

Nonconforming Schwarz-spectral element methods for incompressible flow

Component-Based Reduced Order Modeling of Large-Scale Complex Systems

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