Abstract:  The first lobopodian known from the Ordovician is described from the Soom Shale Lagerstätte, South Africa. The organism shows features homologous to Palaeozoic marine lobopodians described from the Middle Cambrian Burgess Shale, the Lower Cambrian Chengjiang biota, the Lower Cambrian Sirius Passet Lagerstätte and the Lower Cambrian of the Baltic. The discovery provides a link between marine Cambrian lobopodians and younger forms from the Silurian and Carboniferous. The new fossil preserves an annulated trunk, lobopods with clear annulations, and curved claws. It represents a rare record of a benthic organism from the Soom Shale, and demonstrates intermittent water oxygenation during the deposition of the unit.

Gaussian and intermittent synthetically generated turbulences are investigated as initial conditions for high-resolution numerical simulations. Turbulent fields, namely the Mann and the intermittent Time-mapped Mann model, are injected into large eddy simulations, and subsequently their convergences are investigated. In addition to the usual one-point and two-point characterizations, the higher moments of the velocity increments are addressed to grasp the intermittency. Here, we show that independent of the initial conditions, the evolving turbulence converges to a common state, which is well represented by the classical intermittent turbulence of Kolmogorov. The findings reveal that if the intermittency parameters of the inflow field are adjusted to those of the common state, the convergence behavior is much faster.

Leading edge (LE) surface degradation of wind turbine (WT) blades caused by insect accumulation, erosion and other environmental agents reduces the aerodynamic performance of the blades, causing WT power and energy yield losses. Estimating these losses is paramount for cost-informed maintenance planning. Computational Fluid Dynamics (CFD) can predict aerodynamic performance losses. However, sensitivity of these predictions to physical model choice and detailed model settings can be large. To assess this sensitivity, the International Energy Agency Task 46 – Erosion of Wind Turbine Blades, developed the First Aerodynamic Benchmark, presented herein. The performance degradation of the NACA 63₃-418 airfoil due to moderate and severe LE degradation, assessed experimentally in two wind tunnel measurement campaigns, is studied. The clean and degraded airfoil performance predicted by seven CFD codes and two low-fidelity methods are cross-compared and benchmarked against measurements. A utility-scale WT featuring the NACA 63₃-418 airfoil on the outboard blade is used to determine the resulting power and energy losses onshore and offshore. Most codes succeed in predicting the measured airfoil performance reduction due to moderate LE degradation before stall. Consequently, all energy loss estimates are close. Conversely, the variability of the predicted aerodynamic performance reduction due to severe LE degradation is larger, and the variability of the resulting energy losses is also larger than at moderate LE degradation. These results underline both the significant sensitivity to the specific analysis set-up and the need for further research into methods for predicting the impact of advanced LE degradation, such as geometry perturbation-resolving simulations.

Leading edge (LE) surface degradation of wind turbine (WT) blades caused by insect accumulation, erosion and other environmental agents reduces the aerodynamic performance of the blades, causing WT power and energy yield losses. Estimating these losses is paramount for cost-informed maintenance planning. Computational Fluid Dynamics (CFD) can predict aerodynamic performance losses. However, sensitivity of these predictions to physical model choice and detailed model settings can be large. To assess this sensitivity, the International Energy Agency Task 46 – Erosion of Wind Turbine Blades, developed the First Aerodynamic Benchmark, presented herein. The performance degradation of the NACA 63₃-418 airfoil due to moderate and severe LE degradation, assessed experimentally in two wind tunnel measurement campaigns, is studied. The clean and degraded airfoil performance predicted by seven CFD codes and two low-fidelity methods are cross-compared and benchmarked against measurements. A utility-scale WT featuring the NACA 63₃-418 airfoil on the outboard blade is used to determine the resulting power and energy losses onshore and offshore. Most codes succeed in predicting the measured airfoil performance reduction due to moderate LE degradation before stall. Consequently, all energy loss estimates are close. Conversely, the variability of the predicted aerodynamic performance reduction due to severe LE degradation is larger, and the variability of the resulting energy losses is also larger than at moderate LE degradation. These results underline both the significant sensitivity to the specific analysis set-up and the need for further research into methods for predicting the impact of advanced LE degradation, such as geometry perturbation-resolving simulations.

This study employs wall-resolved Sigma SGS Large-Eddy Simulation (WR-LES) of the Eppler 387 airfoil to evaluate the higher-order Spectral Element Method (SEM) CFD solver NEKO at a moderate Reynolds number of 10⁵ and an angle of attack of 4 degrees. 2.5D simulation is performed with a span of 10% chord length using a polynomial order of 3, resulting in 300,960 elements and approximately 19 million Gauss-Lobatto-Legendre (GLL) quadrature points. Aerodynamic force coefficients and pressure distribution along the airfoil are used to evaluate the SEM solver and to validate results against wind-tunnel experimental data from NASA Technical Memorandum 4062 and OpenFOAM 2D RANS (simpleFoam) simulations (k-$\omega$ SST, k-$\omega$ SST Langtry–Menter, and k-$\omega$ SST CND). NEKO predicts the pressure distribution in good agreement with the experimental results; however, the transition point is captured slightly downstream of the experimentally observed location. The solver predicts the lift coefficient matching experimental values up to the 3rd decimal place, but the drag is overestimated. This discrepancy may be attributed to the absence of inflow turbulence in the numerical setup, which is likely present in the wind-tunnel experiment. This study demonstrates both the potential and limitations of higher-order SEM solver NEKO for CFD simulation.

Leading edge (LE) surface degradation of wind turbine (WT) blades caused by insect accumulation, erosion and other environmental agents reduces the aerodynamic performance of the blades, causing WT power and energy yield losses. Estimating these losses is paramount for cost-informed maintenance planning. Computational Fluid Dynamics (CFD) can predict aerodynamic performance losses. However, sensitivity of these predictions to physical model choice and detailed model settings can be large. To assess this sensitivity, the International Energy Agency Task 46 – Erosion of Wind Turbine Blades, developed the First Aerodynamic Benchmark, presented herein. The performance degradation of the NACA 63₃-418 airfoil due to moderate and severe LE degradation, assessed experimentally in two wind tunnel measurement campaigns, is studied. The clean and degraded airfoil performance predicted by seven CFD codes and two low-fidelity methods are cross-compared and benchmarked against measurements. A utility-scale WT featuring the NACA 63₃-418 airfoil on the outboard blade is used to determine the resulting power and energy losses onshore and offshore. Most codes succeed in predicting the measured airfoil performance reduction due to moderate LE degradation before stall. Consequently, all energy loss estimates are close. Conversely, the variability of the predicted aerodynamic performance reduction due to severe LE degradation is larger, and the variability of the resulting energy losses is also larger than at moderate LE degradation. These results underline both the significant sensitivity to the specific analysis set-up and the need for further research into methods for predicting the impact of advanced LE degradation, such as geometry perturbation-resolving simulations.