Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session D31: Large Eddy Simulations: Modeling |
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Chair: Anthony Leonard, California Institute of Technology Room: Georgia World Congress Center B403 |
Sunday, November 18, 2018 2:30PM - 2:43PM |
D31.00001: A novel hybrid two-level and kinetic-eddy simulation model for high Reynolds number wall-bounded turbulent flows Reetesh Ranjan, Achyut Panchal, Suresh Menon A novel hybrid model for simulation of wall-bounded turbulent flows is developed by blending the two-level simulation (TLS) method [1] in the near-wall inner region with the kinetic-eddy simulation (KES) method [2] in the outer region. TLS is a multi-scale approach, where a field variable is decomposed into its large-scale (LS) and small-scale (SS) components, and both LS and SS fields are obtained explicitly by employing modeling assumptions for the small-scales. It does not employ the notion of spatial filtering and eddy viscosity. KES is a two-equation based model, where transport equations for the local subgrid kinetic energy and length scale are solved, thus allowing the method to approach to very large-eddy simulation (VLES), LES, and direct numerical simulation (DNS) in the limit of resolution of turbulence length scales corresponding to only large scales, grid size, and fully resolved, respectively. The generalized hybrid formulation is evaluated for its capabilities by simulating fully developed turbulent channel flow at different frictional Reynolds number, and comparing with the reference DNS results. [1] K. A. Kemenov, S. Menon, J. Comput. Phys., 220 (2006), 290-311. |
Sunday, November 18, 2018 2:43PM - 2:56PM |
D31.00002: Local Variational Germano Identity for Dynamic Large Eddy Simulations based on Finite Elements Onkar Sahni In this talk we will present a localized formulation of the variational Germano identity (VGI) that is applicable to inhomogeneous turbulent flows. This is done in the context of stabilized finite element methods where a combined subgrid-scale (SGS) model is employed. In particular, the combined SGS model uses the residual-based variational multiscale (RBVMS) approach along with the Smagorinsky eddy-viscosity model. The RBVMS model is used to represent the cross-stress terms while the eddy-viscosity model is used for the Reynolds stresses. The unknown parameter related to the eddy-viscosity model is computed using a dynamic procedure based on the local VGI. The overall idea of the local VGI is to compare the numerical solution at two different levels of discretization/grid in a local fashion. The local VGI based dynamic procedure is made practical by employing suitable assumptions. Further, the procedure is made robust by employing a Lagrangian averaging scheme along with a local spatial averaging. This is equivalent to averaging along local pathtubes and maintains the applicability of the current methodology to inhomogeneous turbulent flows. We demonstrate the current LES methodology on a variety of problems including flow over cylinders and surging airfoils. |
Sunday, November 18, 2018 2:56PM - 3:09PM |
D31.00003: A simple extension to eddy-viscosity models for Large Eddy Simulations based on tensor decompositions. Felipe A. V. de Bragança Alves, Stephen de Bruyn Kops Using tensor decompositions theorems and a nonlinear tensor formed by the Lie product of the strain rate and the rate of rotation tensor we form a simple 2-element tensorial basis set to model the residual stress tensor attributing specific roles to each tensor. The strain rate tensor is responsible for reproducing the correct energy transfer from the resolved to the unresolved scales, while the nonlinear term is responsible for the correct energy redistribution among the resolved scales. The coefficients multiplying each tensor are uncoupled, so the nonlinear term can be added to any commonly used version of eddy viscosity model without the need for rethinking the eddy viscosity modeling. |
Sunday, November 18, 2018 3:09PM - 3:22PM |
D31.00004: Data-driven deconvolution for the large eddy simulation of Kraichnan turbulence Romit Maulik, Omer San, Adil Rasheed, Prakash Vedula In this study, we demonstrate the use of artificial neural networks as optimal maps which are utilized for the convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. We demonstrate that an effective eddy-viscosity is characterized by our purely data-driven large eddy simulation framework without the explicit utilization of phenomenological arguments. In addition, our data-driven framework does not require the knowledge of true sub-grid stress information during the training phase due to its focus on estimating an effective filter and its inverse so that grid-resolved variables may be related to direct numerical simulation data statistically. Through this we seek to unite the structural and functional modeling strategies for modeling non-linear partial differential equations using reduced degrees of freedom. Both a-priori and a-posteriori results are shown for the Kraichnan turbulence case in addition to a detailed description of validation and testing. Our findings indicate that the proposed framework approximates a robust and stable sub-grid closure which compares favorably to the Smagorinsky and Leith hypotheses for capturing theoretical kinetic-energy scaling trends in the wavenumber domain. |
Sunday, November 18, 2018 3:22PM - 3:35PM |
D31.00005: Consistency and accuracy of LES by explicit filtering Joseph Mathew, Sumit Kumar Patel An explicit filtering method was proposed as an equivalent implementation of the approximate deconvolution method for large eddy simulation (LES). The essential requirement of this method was that all spatial numerical operations (finding derivatives, interpolations) be of high resolution---be spectrally accurate over a large part of the computed, low-wavenumber range. A natural expectation is that the range of scales over which the dynamics are more accurately represented increases with grid-refinement. Second, beyond some level of refinement, large scale dynamics do not change significantly because the energy in small scale content is orders of magnitude smaller. Third, as Reynolds number is increased, in many flows where the spectral range of the active scales increases at the small scale end only, an LES should return the same large scale dynamics. Systematic studies at different resolutions and Reynolds numbers in forced, homogeneous isotropic turbulence and round jets (low-speed and high-speed ones with multiple shock cells, at Reynolds numbers of the order of a million), will be presented that show these expectations to be met in LES by explicit filtering. Such a posteriori consistency and accuracy make this a reliable method for LES. |
Sunday, November 18, 2018 3:35PM - 3:48PM |
D31.00006: OpenFOAM based Evaluation of PANS Method with Non-Linear Eddy Viscosity Closure for Separated Turbulent Flows Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy At high Reynolds number (Re), the traditional Reynolds averaged Navier-Stokes (RANS) approach based on the Boussinesq hypothesis is incapacitated in two aspects: indiscriminate averaging of flow variables and linear eddy-viscosity model (LEVM) closure. Despite satisfactory performance of LEVM+RANS in several flows of practical interest; at high-Re turbulent flows - it fails to capture essential flow features. Partially averaged Navier-Stokes (PANS) methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. However, PANS equations, derived from RANS, continue to inherit the inadequacies from the parent RANS model based on LEVM closure. |
Sunday, November 18, 2018 3:48PM - 4:01PM |
D31.00007: Abstract Withdrawn
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Sunday, November 18, 2018 4:01PM - 4:14PM |
D31.00008: ABSTRACT WITHDRAWN
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Sunday, November 18, 2018 4:14PM - 4:27PM |
D31.00009: Assessment of different cut-off (filter-width) prescription approaches for the scale-resolving PANS method Branislav Basara, Sharath Girimaji, Zoran Pavlovic The Partially-Averaged Navier-Stokes (PANS) is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The unresolved to total kinetic energy ratio fk is the cut-off control parameter and its specification requires the knowledge of the local turbulent (resolved + unresolved) kinetic energy. While the unresolved kinetic energy is computed directly from model equations, in most current formulations, the resolved kinetic energy is obtained by suitably averaging the resolved field – as in dynamic Smagorinsky LES computations. As the averaging process is expensive, recently alternate specification approaches have been developed. One such approach is to solve an additional equation for resolved turbulent kinetic energy as first proposed by Basara and Girimaji (2013) and further developed by Basara, Pavlovic and Girimaji (2018). In this presentation, we analyse the various fk-specification approaches. Important conclusions regarding the merits of each method are drawn. |
Sunday, November 18, 2018 4:27PM - 4:40PM |
D31.00010: The application of data assimilation to combine experimental data and LES for improved state-estimation. Jeffrey Labahn, Hao Wu, Shaun Harris, Bruno Coriton, Werner M. Ihme, Jonathan H Frank In the current study, data assimilation techniques are investigated to integrate high-speed high-resolution experimental data into a Large Eddy Simulation (LES). LES of an inert jet is performed without data assimilation and shown to accurately reproduce statistical flow-field quantities. To capture the transient dynamics, assimilation of experimental data is performed using an Ensemble Kalman Filter (EnKF) algorithm and the performance of the method is investigated to understand its impact on the state estimation. Our first objective is to investigate the impact that data assimilation has on the resulting flow field for this inert jet. This is accomplished by comparing transient predictions and instantaneous flow structures obtained from a baseline LES without data assimilation to those obtained via EnKF. The second objective is to identify the impact that data localization has on the resulting predictions. Following this, we investigate how the state-estimation is affected by changes in experimental uncertainty, assimilation frequency and sparsity of experimental data. |
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