Giuliano De Stefano

Abstract: The large eddy simulation (LES) equations of turbulent flows are formally derived by applying a low-pass filter to the Navier–Stokes equations. As a result the subgrid-scale (SGS) stress tensor strongly depends on the assumed filter shape, which causes a SGS model to be filter dependent. In particular, depending on the choice of the filter the corresponding SGS model should satisfy very different requirements in terms of large scale dynamics and kinetic energy budget. This paper is an attempt to systematically study the effect of the filter shape on the subgrid scale model and its subsequent effect on LES. For the sake of simplicity, we consider numerical simulation of a one-dimensional homogeneous flow, governed by the viscous Burgers equation. Large eddy simulations of the solution of the Burgers problem are performed using subgrid scale models obtained by filtering data from direct numerical simulations. Diagnostics include temporal evolution of energy and dissipation as well as energy spectra. It is demonstrated both theoretically and numerically that the assumed filter shape can have a significant effect on LES in terms of spectral content and physical interpretation of the solution. The results are generalized for LES of three-dimensional turbulent flows and specific recommendations for the use of filters and corresponding SGS models are made.

Abstract: Stochastic coherent adaptive large eddy simulation (SCALES) is an extension of the large eddy simulation approach in which a wavelet filter-based dynamic grid adaptation strategy is employed to solve for the most “energetic” coherent structures in a turbulent field while modeling the effect of the less energetic background flow. In order to take full advantage of the ability of the method in simulating complex flows, the use of localized subgrid-scale models is required. In this paper, new local dynamic one-equation subgrid-scale models based on both eddy-viscosity and non-eddy-viscosity assumptions are proposed for SCALES. The models involve the definition of an additional field variable that represents the kinetic energy associated with the unresolved motions. This way, the energy transfer between resolved and residual flow structures is explicitly taken into account by the modeling procedure without an equilibrium assumption, as in the classical Smagorinsky approach. The wavelet-filtered incompressible...

Abstract: The wavelet-based eddy-capturing approach with variable thresholding is extended to bluff-body flows, where the obstacle geometry is enforced through Brinkman volume penalization. The use of a spatio-temporally varying threshold allows one to perform adaptive large-eddy simulations with the prescribed fidelity on a near optimal computational mesh. The space–time evolution of the threshold variable is achieved by solving a transport equation based on the Lagrangian path-line diffusive averaging methodology. The coupled wavelet-collocation/volume-penalization approach with variable thresholding is illustrated for a turbulent incompressible flow around an isolated stationary prism with square cross-section. Wavelet-based adaptive large-eddy simulations supplied with the one-equation localized dynamic kinetic energy-based model are successfully performed at moderately high Reynolds number. The present study demonstrates that the proposed variable thresholding methodology for wavelet-based modelling of turbulent flows around solid obstacles is feasible, accurate and efficient.

Abstract: A perfect modeling framework for the systematic study of the effect of filter shape on the resolved scales of motion in large eddy simulation is developed. The effects of the explicit and implicit filtering approaches in large eddy simulation are considered. A simple model for smooth filtering is proposed and the related effects are analyzed. The proposed approach provides an effective research tool for assessing the behavior of sub-grid scale models in a dynamic fashion. The performances of various classical models are examined by using the perfect modeling formalism for simulating the large and/or the small residual scales effect. Numerical experiments are performed for decaying isotropic turbulence. The consistency of the sub-grid scale models with the effective composite filter employed in real simulations is discussed. The necessity of using mixed models when solving doubly-filtered Navier–Stokes equations is verified. It is found that time evolution of large scale velocity field is more sensitive to sub-grid large scale models like Bardina model, while the grid-filtered sub-filter scale model is necessary to ensure the proper energy dissipation.

Abstract: Stochastic coherent adaptive large eddy simulation (SCALES) is an extension of large eddy simulation that uses a wavelet filter-based dynamic grid adaptation strategy to solve for the most energetic coherent structures in a turbulent flow field, while modeling the effect of the less energetic ones. A localized dynamic subgrid scale model is needed to fully exploit the ability of the method to track coherent structures. In this paper, new local Lagrangian models based on a modified Germano dynamic procedure, redefined in terms of wavelet thresholding filters, are proposed. These models extend the original path-line formulation of Meneveau et al. [J. Fluid Mech. 319 (1996)] in two ways: as Lagrangian path-line diffusive and Lagrangian path-tube averaging procedures. The proposed models are tested for freely decaying homogeneous turbulence with initial Re λ = 72. It is shown that the SCALES results, obtained with less than 0.4% of the total non-adaptive nodes required for a DNS with the same wavelet solver, ...

Abstract: An efficient ghost-cell immersed boundary method (GCIBM) for simulating turbulent flows in complex geometries is presented. A boundary condition is enforced through a ghost cell method. The reconstruction procedure allows systematic development of numerical schemes for treating the immersed boundary while preserving the overall second-order accuracy of the base solver. Both Dirichlet and Neumann boundary conditions can be treated. The current ghost cell treatment is both suitable for staggered and non-staggered Cartesian grids. The accuracy of the current method is validated using flow past a circular cylinder and large eddy simulation of turbulent flow over a wavy surface. Numerical results are compared with experimental data and boundary-fitted grid results. The method is further extended to an existing ocean model (MITGCM) to simulate geophysical flow over a three-dimensional bump. The method is easily implemented as evidenced by our use of several existing codes.

Abstract: This article reviews state-of-the-art adaptive, multiresolution wavelet methodologies for modeling and simulation of turbulent flows with various examples. Different numerical methods for solving the Navier-Stokes equations in adaptive wavelet bases are described. We summarize coherent vortex extraction methodologies, which utilize the efficient wavelet decomposition of turbulent flows into space-scale contributions, and present a hierarchy of wavelet-based turbulence models. Perspectives for modeling and computing industrially relevant flows are also given.

Abstract: Oxy-coal combustion is one of the leading technologies for carbon capture and storage. This paper presents a review of the opportunities and challenges surrounding the development of oxy-coal combustion models and discusses historical and recent advances in specific areas related to computational fluid dynamics (CFD), including char oxidation, radiation, pollutant formation and removal (Hg, NO x and SO x ), and the impact of turbulence. CFD can be used to assess and optimise full-scale retrofit designs and to provide data on matching air-fired heat duties. In addition, CFD can also be used to improve combustion efficiency and identify potential reductions in corrosion, slagging, fouling and trace pollutant emissions. Transient simulations are becoming more computationally affordable for coal combustion, providing opportunities for model development. High concentrations of CO 2 and H 2 O in oxy-coal can influence chemical kinetic rates, burnout and ash properties. The modelling can be improved by incorporating detailed kinetic mechanisms of gasification reactions. In addition, pollutant formation and removal mechanisms must be understood during oxy-coal firing to aid the selection of flue-gas cleaning strategies. Radiative heat transfer using spectral models for gaseous properties may be necessary in oxy-coal modelling because CO 2 and H 2 O molecules have strong emission bands. Finally this review provides a coherent near-term and long-term oxy-coal specific CFD sub-models development strategy to simulate the complex oxy-coal combustion processes, heat transfer and pollutant emissions in power generation systems.

Abstract: 应用DES(Detached-Eddy Simulation)方法数值模拟了3种不同失速类型的翼型的升力特性.DES方法结合了RANS(Reynolds-averaged Navier-Stokes)和LES(Large Eddy Simulation approaches)的优点.基于Spalart-Allmaras湍流模型,在近壁面DES体现为RANS模型的特点而在远离物面处又具有LES的亚格子模型的特性.对此模型使用了LU-SGS隐式格式求解.通过和实验结果对比,显示这种方法可以有效地预测翼型的失速特性.

Abstract: In this work, we present a novel data-based approach to turbulence modeling for Large Eddy Simulation (LES) by artificial neural networks. We define the perfect LES formulation including the discretization operators and derive the associated perfect closure terms. We then generate training data for these terms from direct numerical simulations of decaying homogeneous isotropic turbulence. We design and train artificial neural networks based on local convolution filters to predict the underlying unknown non-linear mapping from the coarse grid quantities to the closure terms without a priori assumptions. We show that selecting both the coarse grid primitive variables as well as the coarse grid LES operator as input features significantly improves training results. All investigated networks are able to generalize from the data and learn approximations with a cross correlation of up to 47% and even 73% for the inner elements, demonstrating that the perfect closure can indeed be learned from the provided coarse grid data. Since the learned closure terms are approximate, a direct application leads to stability issues. We show how to employ the artificial neural network output to construct stable and accurate models. The best results have been achieved with a data-informed, temporally and spatially adaptive eddy viscosity closure. While further investigations into the generalizability of the approach is warranted, this work thus represents a starting point for further research into data-driven, optimal turbulence models.