Fully Coupled Floating Wind Turbine Simulator Based on Nonlinear Finite Element Method: Part I — Methodology

Cunff, Cédric Le; Heurtier, Jean-Michel; Piriou, Loïc; Berhault, C.; Perdrizet, Timothée; Teixeira, David; Ferrer, Gilles; Gilloteaux, Jean‐Christophe

doi:10.1115/omae2013-10780

Cited by 20 publications

(28 citation statements)

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“…FarmShadow is an in‐house, steady‐state code developed at IFP Energies Nouvelles (IFPEN). An aerodynamic library based on the IFPEN blade element momentum (BEM) model 22 is coupled to a set of analytical wake models (i.e., the IFPEN implementation and calibration of state‐of‐the‐art velocity deficit and wake‐added turbulence models). The BEM model takes the description of the turbine, blades, and airfoils as inputs and provides notably the thrust coefficient to the wake models.…”

Section: Simulationsmentioning

confidence: 99%

Multimodel validation of single wakes in neutral and stratified atmospheric conditions

et al. 2020

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Previous research has revealed the need for a validation study that considers several wake quantities and code types so that decisions on the trade-off between accuracy and computational cost can be well informed and appropriate to the intended application. In addition to guiding code choice and setup, rigorous model validation exercises are needed to identify weaknesses and strengths of specific models and guide future improvements. Here, we consider 13 approaches to simulating wakes observed with a nacelle-mounted lidar at the Scaled Wind Technology Facility (SWiFT) under varying atmospheric conditions. We find that some of the main challenges in wind turbine wake modeling are related to simulating the inflow. In the neutral benchmark, model performance tracked as expected with model fidelity, with large-eddy simulations performing the best. In the more challenging stable case, steady-state Reynolds-averaged Navier-Stokes simulations were found to outperform other model alternatives because they provide the ability to more easily prescribe noncanonical inflows and their low cost allows for simulations to be repeated as needed. Dynamic measurements were only available for the unstable benchmark at a single downstream distance. These dynamic analyses revealed that differences in the performance of time-stepping models come largely from differences in wake meandering. This highlights the need for more validation exercises that take into account wake dynamics and are able to identify where these differences come from: mesh setup, inflow, turbulence models, or wake-meandering parameterizations. In addition to model validation findings, we summarize lessons learned and provide recommendations for future benchmark exercises.

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Section: Simulationsmentioning

confidence: 99%

Multimodel validation of single wakes in neutral and stratified atmospheric conditions

et al. 2020

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“…Le Cunff et al [83] have developed a coupled dynamics model based on the DeepLines software that incorporates aerodynamics, hydrodynamics, structural and control dynamics. Although this model has been developed mainly for floating HAWTs it also has the capability to model floating VAWTs using a simplified aerodynamic momentum model.…”

Section: Current Implementationsmentioning

confidence: 99%

Offshore floating vertical axis wind turbines, dynamics modelling state of the art. Part III: Hydrodynamics and coupled modelling approaches

Borg

Collu

2015

Renewable and Sustainable Energy Reviews

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“…In our study, a simulator of a Senvion MM82 wind turbine has been developed using Deeplines Wind™ software from technical specifications. This software is a fully coupled simulation tool taking into account the aerodynamics of the aero‐generator, the elasticity of the structural wind turbine components (mast, blades, and drive‐train systems) and the control system 57 . The software architecture developed by IFPEN and Principia is fully modular with different dynamic libraries (DLL) called by the solver.…”

Section: Description Of the Wind Turbine Numerical Modelmentioning

confidence: 99%

Quantification and reduction of uncertainties in a wind turbine numerical model based on a global sensitivity analysis and a recursive Bayesian inference approach

Hirvoas

Prieur

Arnaud

et al. 2021

Numerical Meth Engineering

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A framework to perform quantification and reduction of uncertainties in a wind turbine numerical model using a global sensitivity analysis and a recursive Bayesian inference method is developed in this article. We explain how a prior probability distribution on the model parameters is transformed into a posterior probability distribution, by incorporating a physical model and real field noisy observations. Nevertheless, these approaches suffer from the so‐called curse of dimensionality. In order to reduce the dimension, Sobol' indices approach for global sensitivity analysis, in the context of wind turbine modeling, is presented. A major issue arising for such inverse problems is identifiability, that is, whether the observations are sufficient to unambiguously determine the input parameters that generated the observations. Global sensitivity analysis is also used in the context of identifiability.

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Fully Coupled Floating Wind Turbine Simulator Based on Nonlinear Finite Element Method: Part I — Methodology

Cited by 20 publications

References 0 publications

Multimodel validation of single wakes in neutral and stratified atmospheric conditions

Multimodel validation of single wakes in neutral and stratified atmospheric conditions

Offshore floating vertical axis wind turbines, dynamics modelling state of the art. Part III: Hydrodynamics and coupled modelling approaches

Quantification and reduction of uncertainties in a wind turbine numerical model based on a global sensitivity analysis and a recursive Bayesian inference approach

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