Probabilistic 3-D turbulence modeling for gust buffeting of structures

Solari, Giovanni; Piccardo, Giuseppe

doi:10.1016/s0266-8920(00)00010-2

Cited by 273 publications

(144 citation statements)

References 84 publications

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“…Convenient ways to characterize the probabilistic nature of wind pressures on civil structures are wind tunnel or in situ measurements. Alternatively, a number of stochastic models for wind turbulence and admittances are available, see Dyrbye andHansen (1997), Von Karman (1958), Solari and Piccardo (2001). Computational fluid dynamics (Anderson et al, 2009) is another method yet that provides both velocity and pressure fields.…”

Section: Introductionmentioning

confidence: 99%

Principal static wind loads

Blaise

Denoël

2013

Journal of Wind Engineering and Industrial Aerodynamics

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a b s t r a c tIn current wind design practice, static wind loads are usually defined to obtain, by simple static analyses, the extreme values of any structural response that would be formally obtained with a strict dynamic buffeting analysis. The minimum and maximum values that may reach any response define the envelope. Equivalent static wind loads (ESWLs) allow to recover extreme responses in the envelope. As a first objective, this paper formalizes a general method to determine ESWL, in a nodal basis, by extending the concept of load-response correlation, which is only valid in the background range. The general method, the displacement-response correlation (DRC) method, covers the background and resonant contributions of the considered response. As a second objective, the paper addresses the problem of building a set of static wind loads that adequately reconstructs the envelopes of responses. The concept of principal static wind loads (PSWL) is introduced to form a reduced basis of representative loads well-suited for envelope reconstruction. Its optimality is demonstrated both analytically and with a detailed illustrative example.

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Section: Introductionmentioning

confidence: 99%

Principal static wind loads

Blaise

Denoël

2013

Journal of Wind Engineering and Industrial Aerodynamics

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“…The black dotted line for the longitudinal (u) component indicates an exponential coherence model used in a design standard [16]. Coherence functions for the v and w components, also discussed in a number of studies related to turbulence [19][20][21], are expectedly different from that for u. Coherence appears to depend on height; at lower heights, higher turbulence levels introduced by the lower boundary leads to weaker coherent in the wind field.…”

Section: Free-stream Wind Field Parametersmentioning

confidence: 99%

“…Figure 15 and Table 2 summarize results of regression-related estimation of these parameters based on the LES precursor data and an indication of the fit of the standard deviation profiles for u, v, and w using the estimated parameters. To model free-stream PSD functions, we use the spectral model proposed by Solari and Piccardo [19], which is defined as follows:…”

Section: A Stochastic Wake Modelmentioning

confidence: 99%

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Toward Development of a Stochastic Wake Model: Validation Using LES and Turbine Loads

et al. 2017

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Abstract:Wind turbines within an array do not experience free-stream undisturbed flow fields. Rather, the flow fields on internal turbines are influenced by wakes generated by upwind unit and exhibit different dynamic characteristics relative to the free stream. The International Electrotechnical Commission (IEC) standard 61400-1 for the design of wind turbines only considers a deterministic wake model for the design of a wind plant. This study is focused on the development of a stochastic model for waked wind fields. First, high-fidelity physics-based waked wind velocity fields are generated using Large-Eddy Simulation (LES). Stochastic characteristics of these LES waked wind velocity field, including mean and turbulence components, are analyzed. Wake-related mean and turbulence field-related parameters are then estimated for use with a stochastic model, using Multivariate Multiple Linear Regression (MMLR) with the LES data. To validate the simulated wind fields based on the stochastic model, wind turbine tower and blade loads are generated using aeroelastic simulation for utility-scale wind turbine models and compared with those based directly on the LES inflow. The study's overall objective is to offer efficient and validated stochastic approaches that are computationally tractable for assessing the performance and loads of turbines operating in wakes.

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“…Most related works were carried out in the incompressible flow framework for wind engineering oriented studies, e.g. see Solari and Piccardo [21] and Pagnigni and Solari [18] and references given therein. In these works, the main purpose is to model turbulent wind gusts that are responsible for structural loads and to predict the induced structure deformations and/or vibrations.…”

Section: Introductionmentioning

confidence: 99%

A gPC-based approach to uncertain transonic aerodynamics

Simon

Guillen

Sagaut

et al. 2010

Computer Methods in Applied Mechanics and Engineering

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a b s t r a c tThe present paper focus on the stochastic response of a two-dimensional transonic airfoil to parametric uncertainties. Both the freestream Mach number and the angle of attack are considered as random parameters and the generalized Polynomial Chaos (gPC) theory is coupled with standard deterministic numerical simulations through a spectral collocation projection methodology. The results allow for a better understanding of the flow sensitivity to such uncertainties and underline the coupling process between the stochastic parameters. Two kinds of non-linearities are critical with respect to the skin-friction uncertainties: on one hand, the leeward shock movement characteristic of the supercritical profile and on the other hand, the boundary-layer separation on the aft part of the airfoil downstream the shock. The sensitivity analysis, thanks to the Sobol' decomposition, shows that a strong non-linear coupling exists between the uncertain parameters. Comparisons with the one-dimensional cases demonstrate that the multi-dimensional parametric study is required to get the correct shape and magnitude of the standard deviation distributions of the flow quantities such as pressure and skin-friction.

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Probabilistic 3-D turbulence modeling for gust buffeting of structures

Cited by 273 publications

References 84 publications

Principal static wind loads

Principal static wind loads

Toward Development of a Stochastic Wake Model: Validation Using LES and Turbine Loads

A gPC-based approach to uncertain transonic aerodynamics

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