On the implementation of low-dissipative Runge–Kutta projection methods for time dependent flows using OpenFOAM®

Vuorinen, Ville; Keskinen, Jukka-Pekka; Duwig, Christophe; Boersma, Bendiks Jan

doi:10.1016/j.compfluid.2014.01.026

Cited by 73 publications

(60 citation statements)

References 34 publications

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“…The pressure is obtained by solving the Poisson equation. In OpenFOAM, the solver was first incorporated by Vuorinen et al (2014) and further extended for atmospheric flows by Vuorinen et al (2015). Since LES does not resolve eddies smaller than grid size, their effects are modelled using the one-equation eddy viscosity SGS model proposed by Yoshizawa (1993),…”

Section: Methodsmentioning

confidence: 99%

Experimental and Numerical Modelling of Flow over Complex Terrain: The Bolund Hill

Conan

Chaudhari

Aubrun

et al. 2015

Boundary-Layer Meteorol

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In the wind-energy sector, wind-power forecasting, turbine siting, and turbinedesign selection are all highly dependent on a precise evaluation of atmospheric wind conditions. On-site measurements provide reliable data; however, in complex terrain and at the scale of a wind farm, local measurements may be insufficient for a detailed site description. On highly variable terrain, numerical models are commonly used but still constitute a challenge regarding simulation and interpretation. We propose a joint state-of-the-art study of two approaches to modelling atmospheric flow over the Bolund hill: a wind-tunnel test and a large-eddy simulation (LES). The approach has the particularity of describing both methods in parallel in order to highlight their similarities and differences. The work provides a first detailed comparison between field measurements, wind-tunnel experiments and numerical simulations. The systematic and quantitative approach used for the comparison contributes to a better understanding of the strengths and weaknesses of each model and, therefore, to their enhancement. Despite fundamental modelling differences, both techniques result in only a 5 % difference in the mean wind speed and 15 % in the turbulent kinetic energy (TKE). The joint comparison makes it possible to identify the most difficult features to model: the near-ground flow and the wake of the hill. When compared to field data, both models reach 11 % error for the mean wind speed, which is close to the best performance reported in the literature. For the TKE, a great improvement is found using the LES model compared to previous studies (20 % error). Wind-tunnel results are in the low range of error when compared B Boris Conan 123 B. Conan et al.to experiments reported previously (40 % error). This comparison highlights the potential of such approaches and gives directions for the improvement of complex flow modelling.

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Section: Methodsmentioning

confidence: 99%

Experimental and Numerical Modelling of Flow over Complex Terrain: The Bolund Hill

Conan

Chaudhari

Aubrun

et al. 2015

Boundary-Layer Meteorol

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“…In contrast to other pressure correction methods, (e.g., pressure implicit with splitting of operator (PISO) [32] or semi-implicit method for pressure-linked equations (SIMPLE) [33]), no corrector loop is required, which significantly speed up the calculation. Moreover, it was shown by [34] that it is further less dissipative than the standard methods in OpenFOAM and well suited for time-resolved numerical simulations. The method is applied with a three-stage explicit Runge-Kutta scheme of second order accuracy for time integration [35].…”

Section: Direct Numerical Simulationmentioning

confidence: 99%

Database of Near-Wall Turbulent Flow Properties of a Jet Impinging on a Solid Surface under Different Inclination Angles

Ries

Rißmann

et al. 2018

Fluids

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Abstract:In the present paper, direct numerical simulation (DNS) and particle image velocimetry (PIV) have been applied complementarily in order to generate a database of near-wall turbulence properties of a highly turbulent jet impinging on a solid surface under different inclination angles. Thereby, the main focus is placed on an impingement angle of 45 • , since it represents a good generic benchmark test case for a wide range of technical fluid flow applications. This specific configuration features very complex flow properties including the presence of a stagnation point, development of the shear boundary layer and strong streamline curvature. In particular, this database includes near-wall turbulence statistics along with mean and rms velocities, budget terms in the turbulent kinetic energy equation, anisotropy invariant maps, turbulent length/time scales and near-wall shear stresses. These properties are useful for the validation of near-wall modeling approaches in the context of Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulations (LES). From this study, in which further impingement angles (0 • , 90 • ) have been considered in the experiments only, it turns out that (1) the production of turbulent kinetic energy appears negative at the stagnation point for an impingement angle other than 0 • and is balanced predominantly by pressure-related diffusion, (2) quasi-coherent thin streaks with large characteristic time scales appear at the stagnation region, while the organization of the flow is predominantly toroidal further downstream, and (3) near-wall shear stresses are low at the stagnation region and intense in regions where the direction of the flow changes suddenly.

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“…To enforce stability, the PISO loop in OpenFOAM ® usually has incorporated a term of artificial diffusion for the advection term ∇ · (ρu ⊗ u). As studied and suggested in Vuorinen et al (2014), we avoid using this extra term which is not present in the original PISO implementation. We refer to Jasak (1996) for a complete description of the discretization strategy adopted in OpenFOAM ® .…”

Section: Finite Volume Discretization Strategymentioning

confidence: 99%

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

2016

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Abstract.A new fluid-dynamic model is developed to numerically simulate the non-equilibrium dynamics of polydisperse gas-particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model, valid for low-concentration regimes (particle volume fraction less than 10 −3 ) and particle Stokes number (St -i.e., the ratio between relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capability to describe gas-particle non-equilibrium effects. Direct Numerical Simulation accurately reproduces the dynamics of isotropic, compressible turbulence in subsonic regimes. For gas-particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of highReynolds number and high-temperature regimes in the presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to reproduce the averaged and instantaneous flow properties. In particular, the self-similar Gaussian radial profile and the development of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of the important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal and maximum plume height. For very fine particles (St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and preferentially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas-particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.

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On the implementation of low-dissipative Runge–Kutta projection methods for time dependent flows using OpenFOAM®

Cited by 73 publications

References 34 publications

Experimental and Numerical Modelling of Flow over Complex Terrain: The Bolund Hill

Experimental and Numerical Modelling of Flow over Complex Terrain: The Bolund Hill

Database of Near-Wall Turbulent Flow Properties of a Jet Impinging on a Solid Surface under Different Inclination Angles

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

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