arXiv subjects

Manuel Ayala

Publications and source records attributed to Manuel Ayala.

4 recordsLinked to original sources

arXiv2026

Actuator Disk Models reproduce Actuator Line Model power and thrust fluctuation statistics in wind farm simulations

Actuator-disk models (ADM) are widely used in wind-farm simulations, but their accuracy in reproducing power and thrust temporal fluctuation statistics has not yet been compared to the more accurate and detailed predictions of actuator-line models (ALM). This work provides a detailed comparison of such model predictions under three distinct atmospheric conditions. Data is obtained from a database (JHTDB-Wind) containing actuator-line turbine-response and time-resolved flow field data from a large-eddy simulation of a small windfarm operating over a full diurnal cycle. Power and thrust time series corresponding to ADM are constructed from disk-averaged velocity signals and compared with the corresponding more detailed actuator-line signals over three temporal windows within the diurnal cycle. The analysis compares time series, power spectral densities, and both the fluctuation and increment probability density distributions. The results show that the ADM time-series capture the dominant temporal, spectral, and statistical features of the ALM values at resolved and disk-averaged flow-field time scales, i.e. slower than the rotor frequency. Effects of temporal filtering that are often applied to ADM inputs are examined. Overall, the results provide strong support for the use of ADM for predicting power and thrust fluctuation statistics in wind-farm simulations.

physics.flu-dyn↗

arXiv2026

Wind farms as sensor arrays of turbulent boundary layer spatio-temporal flow structure

Temporal fluctuations of wind farm-generated power arise from the interaction between atmospheric turbulence, turbine properties, and wind-farm layout. However, accurately characterizing these fluctuations remains an open challenge. We here present and extend an analytical framework to predict the temporal spectrum of wind farm power-fluctuations, and compare its predictions with detailed large-eddy-simulations (LES) of a wind farm operating within a conventionally neutral boundary layer. The modeling framework assembles several established concepts from turbulent boundary layer physics: a spatio-temporal turbulence spectral model accounting for mean advection and assuming random sweeping by large eddies, a top-down wind farm model of a fully developed wind turbine array boundary layer flow providing the required mean-flow and turbulence scales, and a spatial sampling kernel representing turbine positions and finite rotor size. The latter is extended to three dimensions to represent filtering of spatial fluctuations of turbulence along the vertical direction. Using only atmospheric, turbine, and layout parameters, the model predictions are evaluated against an extensive LES database of a large wind farm on flat terrain. The model accurately predicts the aggregate power frequency spectrum, including peaks associated with advection between turbine rows, the decay of inertial-range turbulence fluctuations due to rotor averaging, and spectra of aggregate power signals from various arrangements of groups of turbines within the array (e.g. staggered or random subsets). The ability to predict wind power fluctuation spectra from fundamental fluid dynamics and existing boundary layer turbulence models could help improve wind farm grid integration.

physics.flu-dyn↗

arXiv2025

Surface Wave-Aerodynamic Roughness Length Model for Air-Sea Interactions

A new model to evaluate the equivalent hydrodynamic length or surface roughness, z0, of ocean waves is developed and tested. The proposed Surface Wave-Aerodynamic Roughness Length (SWARL) model requires maps of the wave surface height at consecutive times and the air flow characteristic Reynolds number as inputs. Pressure drag is accounted for by approximating the relative velocity in a frame moving with the local wave phase-speed assuming ideal inviscid ramp flow (Ayala et al. 2024). Drag from viscous and unresolved ripples is modeled using the standard equilibrium model. The SWARL model is tested using over 300 datasets for monochromatic and broad-spectrum wave surfaces. The model-predicted z0 and drag coefficients are compared to measured values, as well as commonly used wave parametrization methods found in the literature. For datasets with well-characterized surfaces, the proposed model shows significantly better agreement with data compared to prior models. For data that did not include a full characterization of the wave fields (typically field data), the model yields predictions with accuracy similar to prior models. Results highlight that including detailed flow physics and extensive wave-field characterization in the modeling of z0 can provide significant improvements in roughness-length based modeling of air-sea interactions.

physics.flu-dyn↗

arXiv2024

A Moving Surface Drag Model for LES of Wind over Waves

Numerical prediction of the interactions between wind and ocean waves is essential for climate modeling and a wide range of offshore operations. Large Eddy Simulation (LES) of the marine atmospheric boundary layer is a practical numerical predictive tool but requires parameterization of surface fluxes at the air-water interface. Current momentum flux parameterizations primarily use wave-phase adapting computational grids, incurring high computational costs, or use an equilibrium model based on Monin-Obukhov similarity theory for rough surfaces that cannot resolve wave phase information. To include wave phase-resolving physics at a cost similar to the equilibrium model, the Moving Surface Drag (MOSD) model is introduced. It assumes ideal airflow over locally piece-wise planar representations of moving water wave surfaces. Horizontally unresolved interactions are still modeled using the equilibrium model. Validation against experimental and numerical datasets with known monochromatic waves demonstrates the robustness and accuracy of the model in representing wave-induced impacts on mean velocity and Reynolds stress profiles. The model is formulated to be applicable to a broad range of wave fields and its ability to represent cross-swell and multiple wavelength cases is illustrated. Additionally, the model is applied to LES of a laboratory-scale fixed-bottom offshore wind turbine model, and the results are compared with wind tunnel experimental data. The LES with the MOSD model shows good agreement in wind-wave-wake interactions and phase-dependent physics at a low computational cost. The model's simplicity and minimal computational needs make it valuable for studying turbulent atmospheric-scale flows over the sea, particularly in offshore wind energy research.

physics.flu-dyn↗