Numerical Flow Computation Around 3d Square Cylinder Using Inflow Turbulence

Kataoka, Hiroto; Mizuno, Minoru

doi:10.3130/aija.64.71

Cited by 23 publications

(16 citation statements)

References 5 publications

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“…The method follows the one described by Lund et al (1998), with the modifications introduced by Kataoka and Mizuno (2002). Figure 3 gives an overview of the recycling method used in PALM.…”

Section: Turbulence Recyclingmentioning

confidence: 99%

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

et al. 2015

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Abstract. In this paper we present the current version of the Parallelized Large-Eddy Simulation Model (PALM) whose core has been developed at the Institute of Meteorology and Climatology at Leibniz Universität Hannover (Germany). PALM is a Fortran 95-based code with some Fortran 2003 extensions and has been applied for the simulation of a variety of atmospheric and oceanic boundary layers for more than 15 years. PALM is optimized for use on massively parallel computer architectures and was recently ported to general-purpose graphics processing units. In the present paper we give a detailed description of the current version of the model and its features, such as an embedded Lagrangian cloud model and the possibility to use Cartesian topography. Moreover, we discuss recent model developments and future perspectives for LES applications.

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“…The method follows the one described by Lund et al (1998), with the modifications introduced by Kataoka and Mizuno (2002). Figure 3 gives an overview of the recycling method used in PALM.…”

Section: Turbulence Recyclingmentioning

confidence: 99%

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

et al. 2015

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“…In this study the relationship shown in equation (8) is assumed. (8) Here, uRAMS and uRMS denote wind speed predicted by RAMS and JMA-RSM respectively , k(e) denotes coefficient rnalrix as a function of predicted wind direction e by JMA-RSM and e denotes error term. This assumption is based on the idea that the speed up by local terrain is only the function of wind direction.…”

Section: Basic Ideamentioning

confidence: 99%

MC4 Wind Energy And Topography 2

Al‐Deen

Yamaguchi

Ishihara

et al. 2006

Wind Engineers, JAWE

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In this study mesoscale meteorological model and CFD model was used to downscale the numerical weather prediction (NWP) data and verified at Hachijo Jima wind power plant. To reduce the computational cost of mesoscale model, coefficient matrix method was proposed. Following results were obtained. The root mean square error (RMSE) was reduced to 3.1 m/s and 2.8m/s by mesoscale and CFD model respectively from 5.7m/s of original NWP. The coefficient matrix method reduced the computational time to a few seconds by one PC from two hours by parallel computers with 8CPUs without increasing the prediction error. KEYWORDS: Physical model, Wind speed Prediction, Wind energy forecasting, Mesoscale model, CFD 1 INTRODUCTION For electric power supply system, good agreement between demand and supply is essential. But in case of wind energy it is difficult to know the power output fluctuation in advance as it fluctuates with wind speed. This uncertainty causes problem in demand and supply planning for electric power and in real time electricity supply operation everyday. In countries with high wind energy penetration like Denmark and Germany, the day ahead forecast and the daily forecast of wind energy output are carried out based on the numerical weather prediction data and online measurement of the wind energy output))However, operational models use statistical methods somehow, which means the power prediction is based on the past experience on the relationship between the prediction and measurement. This approach is efficient when past measurement data is available. On the other hand, the needs for the wind power prediction exist at the beginning of the operation of a new wind farm or even before the construction of the wind farm. In such cases, physical approach is needed, in which wind speed is predicted by physical model without using any past measurement data.In this study, a physical model based wind speed prediction system was developed for online power prediction and verified by the anemometer located at the nacelle of the wind turbine at the Tokyo Electric Power Company Hachijo Jima wind power station.

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“…The standard Smagorinsky model is adopted to estimate the term of τ ij ,a s shown in Eqs. (11)- (13).…”

Section: Computational and Boundary Conditionsmentioning

confidence: 99%

LES of Unsteady Aerodynamic Forces on a Long-Span Curved Roof

Ding¹

2018

Flight Physics - Models, Techniques and Technologies

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The present paper discusses the unsteady aerodynamic forces on long-span curved roofs by using large eddy simulation (LES). The forced vibration test in a turbulent boundary layer is simulated. The models are force vibrated in the first anti-symmetric mode to investigate the influences of a roof's vibration on the wind pressure and flow field around a vibrating roof. The characteristics of unsteady aerodynamic forces in a wider range of reduced frequency of vibration are also investigated. A comparison between the wind tunnel experiment and the LES indicates that the LES can be used effectively to evaluate the unsteady aerodynamic force.

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Numerical Flow Computation Around 3d Square Cylinder Using Inflow Turbulence

Cited by 23 publications

References 5 publications

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

MC4 Wind Energy And Topography 2

LES of Unsteady Aerodynamic Forces on a Long-Span Curved Roof

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