Detailed 3D finite-element simulations are state of the art for structural analyses of wind turbine rotor blades. It is of utmost importance to validate the underlying modeling methodology in order to obtain reliable results. Validation of the global response can ideally be done by comparing simulations with full-scale blade tests. However, there is a lack of test results for which also the finite-element model with blade geometry and layup as well as the test documentation and results are completely available. The aim of this paper is to validate the presented fully parameterized blade modeling methodology that is implemented in an in-house model generator and to provide respective test results for validation purpose to the public. This methodology includes parameter definition based on splines for all design and material parameters, which enables fast and easy parameter analysis. A hybrid 3D shell/solid element model is created including the respective boundary conditions. The problem is solved via a commercially available finite-element code. A static full-scale blade test is performed, which is used as the validation reference. All information, e.g., on sensor location, displacement, and strains, is available to reproduce the tests. The tests comprise classical bending tests in flapwise and lead–lag directions according to IEC 61400-23 as well as torsion tests. For the validation of the modeling methodology, global blade characteristics from measurements and simulation are compared. These include the overall mass and center of gravity location, as well as their distributions along the blade, bending deflections, strain levels, and natural frequencies and modes. Overall, the global results meet the defined validation thresholds during bending, though some improvements are required for very local analysis and especially the response in torsion. As a conclusion, the modeling strategy can be rated as validated, though necessary improvements are highlighted for future works.

Fabricated wind turbine blades have unavoidable deviations from their designs due to imperfections in the manufacturing processes. Model updating is a common approach to enhance model predictions and therefore improve the numerical blade design accuracy compared to the built blade. An updated model can provide a basis for a digital twin of the rotor blade including the manufacturing deviations. Classical optimization algorithms, most often combined with reduced order or surrogate models, represent the state of the art in structural model updating. However, these deterministic methods suffer from high computational costs and a missing probabilistic evaluation. This feasibility study approaches the model updating task by inverting the model through the application of invertible neural networks, which allow for inferring a posterior distribution of the input parameters from given output parameters, without costly optimization or sampling algorithms. In our use case, rotor blade cross sections are updated to match given cross‐sectional parameters. To this end, a sensitivity analysis of the input (material properties or layup locations) and output parameters (such as stiffness and mass matrix entries) first selects relevant features in advance to then set up and train the invertible neural network. The trained network predicts with outstanding accuracy most of the selected cross‐sectional input parameters for different radial positions; that is, the posterior distribution of these parameters shows a narrow width. At the same time, it identifies some parameters that are hard to recover accurately or contain intrinsic ambiguities. Hence, we demonstrate that invertible neural networks are highly capable for structural model updating.

During the preliminary design phase of wind turbine blades, the evaluation of many design candidates in a short period of time plays an important role. Computationally efficient methods for the structural analysis that correctly predict stiffness matrix entries for beam models including the (bend–twist) coupling terms are thus needed. The present paper provides an extended overview of available approaches and shows their abilities to fulfill the requirements for the composite design of rotor blades with respect to accuracy and computational efficiency. Three cross-sectional theories are selected and implemented to compare the prediction quality of the cross-sectional coupling stiffness terms and the stress distribution based on different multi-cell test cross-sections. The cross-sectional results are compared with the 2D finite element code BECAS and are discussed in the context of accuracy and computational efficiency. The analytical solution performing best shows very small deviations in the stiffness matrix entries compared to BECAS (below 1 % in the majority of test cases). It achieved a better resolution of the stress distribution and a computation time that is more than an order of magnitude smaller using the same spatial discretization. The deviations of the stress distributions are below 10 % for most test cases. The analytical solution can thus be rated as a feasible approach for a beam-based pre-design of wind turbine rotor blades.

Digitalization, especially in the form of a digital twin, is fast becoming a key instrument for the monitoring of a product's life cycle from manufacturing to operation and maintenance and has recently been applied to wind turbine blades. Here, model updating plays an important role for digital twins, in the form of adjusting the model to best replicate the corresponding real-world counterpart. However, classical updating methods are generally limited to a reduced parameter space due to low computational efficiency. Moreover, these approaches most likely lack a probabilistic evaluation of the result. The purpose of this paper is to extend a previous feasibility study to a finite element Timoshenko beam model of a full blade for which the model updating process is conducted through the novel approach with invertible neural networks (INNs). This type of artificial neural network is trained to represent an inversion of the physical model, which in general is complex and non-linear. During the updating process, the inverse model is evaluated based on the target model's modal responses. It then returns the posterior prediction for the input parameters. In advance, a global sensitivity study will reduce the parameter space to a significant subset on which the updating process will focus. The finally trained INN excellently predicts the input parameters' posterior distributions of the proposed generic updating problem. Moreover, intrinsic model ambiguities, such as material densities of two closely located laminates, are correctly captured. A robustness analysis with noisy response reveals a few sensitive parameters, though most can still be recovered with equal accuracy. And, finally, after the resimulation analysis with the updated model, the modal response perfectly matches the target values. Thus, we successfully confirmed that INNs offer an extraordinary capability for structural model updating of even more complex and larger models of wind turbine blades.

The aerodynamic performance of a wind turbine rotor blade depends on the geometry of the airfoils used. The airfoil shape can be affected by elastic deformations of the blade during operation due to structural loads. This paper provides an initial estimation of the extent to which cross-sectional deformations influence the aerodynamic loads on the rotor. The IEA 15 MW reference wind turbine model is used for this study. A constant wind field at rated wind speed is applied as an operational load test case. The resulting loads are calculated by an aero-servo-elastic simulation of the turbine. The loads are applied to a three-dimensional (3D) finite shell element model of the rotor blade, which serves to calculate the cross-sectional deformations. For the individual cross-sections in the deformed configuration, the new lift and drag coefficients are calculated. These are then included in the aero-servo-elastic simulation, and the obtained results are compared with those of the initial simulation that is based on the undeformed cross-sections. The cross-sectional deformations consist of a change in the chord length and the geometry of the trailing edge panels and depend on the azimuth position of the blade. The change in the airfoil geometries results in altered aerodynamic characteristics and therefore a deviation of the blade root bending moments, the maximum change of which is −1.4 % in the in-plane direction and +0.71 % in the out-of-plane direction. These results show that cross-sectional deformations have a minor influence on the internal loads of rotor blades in normal operation.