Results from the DAN-AERO and aerodynamic glove projects provide significant findings. The effects of inflow turbulence on transition and wind turbine blades are compared to computational fluid dynamic simulations. It is found that the transition scenario changes even over a single revolution. The importance of a suitable choice of amplification factor is evident from the simulations. An agreement between the power spectral density plots from the experiment and large-eddy simulations is seen.

In this research, a cyclic p–y overlay model for monopiles in sand soils could be developed via comparison of numerical simulations of monopile behaviour: once under monotonic and once under cyclic loading with a defined number of load cycles (utilizing the stiffness degradation method). The new cyclic overlay model gives plausible results and can be applied to any monotonic p–y approach for monopiles in sand.

Ice roughness deteriorates wind turbine aerodynamics. We have shown numerically that this also occurs when complex ice shapes are present on the leading edge, as long as the blade's wet region extends beyond the ice shape itself and roughness elements are high enough. Such features are typical of icing events on wind turbines but are not captured by current icing simulation tools. Future research should focus on correctly computing both the wet region of the blade and the roughness height.

In this paper, the capacity to simulate transient wind turbine wake interaction problems using limited wind turbine data has been extended. The key novelty is the creation of two new variants of the actuator line technique in which the rotor blade forces are computed locally using generic load data. The analysis covers a partial wake interaction case between two wind turbines for a uniform laminar inflow and for a turbulent neutral atmospheric boundary layer inflow.

Free-vortex wake (OLAF) and low-fidelity blade-element momentum (BEM) structural results are compared to high-fidelity simulation results for a flexible downwind turbine for varying inflow conditions. Overall, OLAF results were more consistent than BEM results when compared to SOWFA results under challenging inflow conditions. Differences between OLAF and BEM results were dominated by yaw misalignment angle, with varying shear exponent and turbulence intensity causing more subtle differences.

This paper introduces the cumulative-curl wake model that allows for the fast and accurate prediction of wind farm energy production wake interactions. The cumulative-curl model expands several existing wake models to make the simulation of farms more accurate and is implemented in a computationally efficient manner such that it can be used for wind farm layout design and controller development. The model is validated against high-fidelity simulations and data from physical wind farms.

Using renewable energy such as wind energy is vital. To optimize the energy yield from wind turbines, they have increased in size, leading to large blade deformations. This paper measures these deformations for different wind loads and the distance between the blade and the tower from 170 m away from the wind turbine. The paper proves that the blade deformation increases in the wind direction with increasing wind speed, while the distance between the blade and the tower decreases.

Turbulence intensity is critical for wind turbine design and operation as it affects wind power generation efficiency. Turbulence measurements in the marine environment are limited. We use a model to derive turbulence intensity and test how sea surface temperature data may impact the simulated turbulence intensity and atmospheric stability. The model slightly underestimates turbulence, and improved sea surface temperature data reduce the bias. Error with unrealistic mesoscale flow is identified.

In this work we examine the relationship between wind speed and turbulent stresses within a wind turbine wake. This relationship changes further from the turbine as the driving physical phenomena vary throughout the wake. We propose a model for this process and test the effectiveness of our model against existing formulations. Our approach increases the accuracy of wind speed predictions, which will lead to better estimates of wind plant performance and promote more efficient wind plant design.