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The dynamic behaviour of the wind turbine tower and blade structure is crucial for structural fatigue propagation of large wind turbines at multi megawatt scale. Mitigation the structural response to windinduced vibrations takes therefore a central role in modern wind turbine design. This study investigates the impact of passive tuned mass damper (TMD) on the dynamic behaviour of the W2E 120/3.0fc wind turbine designed by W2E Wind to Energy. Two different TMD concepts are investigated. A TMD is implemented at the tower top to mitigate fore-aft vibrations of the turbine. Further a TMD is mounted on each turbine blade to mitigate flapwise vibrations of the blades. The performance of the TMDs is evaluated by means of a detailed validated multibody model of the turbine prototype.

Experimental analyses of modal parameters on operating wind turbines are associated with great technical expense, standstill times and therefore with high costs. This makes experimental research on operating wind turbines, for example testing innovative measurement strategies, uneconomical. Thus it is desirable to conduct portions of experimental research on laboratory test structures. In this paper the development of a scaled laboratory test rig is presented. It is designed in such a manner that the lower natural frequencies of a reference wind turbine are approximately reproduced. To find feasible physical parameters for the test rig, preliminary analyses based on an analytical model of a vertical cantilever beam with a top body were combined with experiments based on Operational Modal Analysis (OMA) and multibody simulations.

The mechanical design of wind turbines requires a profound understanding of the dynamic behaviour. Even though highly detailed simulation models are already in use to support wind turbine design, modal testing on a real prototype is irreplaceable to identify site-specific conditions such as the stiffness of the tower foundation. Correct identification of the mode shapes of a complex mechanical structure much depends on the placement of the sensors. For operational modal analysis of a 3 MW wind turbine with a 120 m rotor on a 100 m tower developed by W2E Wind to Energy, algorithms for optimal placement of acceleration sensors are applied. The mode shapes used for the optimisation are calculated by means of a detailed flexible multibody model of the wind turbine. Among the three algorithms in this study, the genetic algorithm with weighted off-diagonal criterion yields the sensor configuration with the highest quality. The ongoing measurements on the prototype will be the basis for the development of optimised wind turbine designs.

Wind energy is one of the main renewable energy sources in the current energy transition. Due to ever more and ever larger wind turbines (WT), the requirements for WT operation become more complex. Model predictive control (MPC) for WTs shows the potential to handle these requirements and conflicting control objectives in a single optimization‐based controller. Recent research has widely investigated MPC for WT in simulation, but mostly lacks experimental validation. This work aims to experimentally validate MPC on a full‐scale WT under real conditions. To this end, we combine an extended Kalman filter for nonlinear state estimation with robust linear time‐varying MPC. We evaluate the proposed control algorithm in terms of time‐domain performance and power curve in simulation. However, the main contribution of this work is the experimental validation on a 3MW WT in Northern Germany with a total duration of 3‐h continuous full access of the controller. We were able to demonstrate stable operation of the proposed MPC in the upper partial load regime, transition regime, and lower full load regime, at measured wind speeds between 4.76 and 13.06 m/s, inside and outside the wake shadow of another WT. The power curve determined in simulation shows comparable results to a reference feedback controller. The MPC formulation combines several control objectives in a single optimization problem, yet the tuning effort still remains complex. In future work, we plan to reduce the complexity of the control loop based on this experimentally validated MPC. We provide our experimental data at https://doi.org/10.5281/zenodo.14644908.

The implantation of total knee replacements is an effective treatment for advanced degenerative knee joint diseases. Implant positioning relative to the bones affects the loads occurring in the artificial joint, joint stability, and postoperative functionality. Variance in implant positioning during the surgical implantation of a total knee replacement cannot be entirely ruled out. By simulating implant malpositioning in an experimental setting, particularly critical cases of malalignment can be identified, from which guidelines for orthopedic surgeons can be derived. The AMTI VIVO™ six degree of freedom joint simulator allows reproducible preclinical testing of joint endoprostheses under specific kinematic and loading conditions. It features a virtual ligament model that defines up to 100 ligament fibers between the articulating components. This paper presents a method to investigate the effect of different implant positions on the biomechanics of the knee after total knee arthroplasty. For this, the VIVO joint simulator requires no modification of the physical setup by moving virtual ligament insertion points relative to the bone. As a proof of concept, exemplary shifts and rotations of the femoral and tibial implant components are performed, and dynamic results are compared to a musculoskeletal multibody digital twin and findings from the literature. Video Abstract.

Constant high rates of dislocation-related complications of total hip replacements (THRs) show that contributing factors like implant position and design, soft tissue condition and dynamics of physiological motions have not yet been fully understood. As in vivo measurements of excessive motions are not possible due to ethical objections, a comprehensive approach is proposed which is capable of testing THR stability under dynamic, reproducible and physiological conditions. The approach is based on a hardware-in-the-loop (HiL) simulation where a robotic physical setup interacts with a computational musculoskeletal model based on inverse dynamics. A major objective of this work was the validation of the HiL test system against in vivo data derived from patients with instrumented THRs. Moreover, the impact of certain test conditions, such as joint lubrication, implant position, load level in terms of body mass and removal of muscle structures, was evaluated within several HiL simulations. The outcomes for a normal sitting down and standing up maneuver revealed good agreement in trend and magnitude compared with in vivo measured hip joint forces. For a deep maneuver with femoral adduction, lubrication was shown to cause less friction torques than under dry conditions. Similarly, it could be demonstrated that less cup anteversion and inclination lead to earlier impingement in flexion motion including pelvic tilt for selected combinations of cup and stem positions. Reducing body mass did not influence impingement-free range of motion and dislocation behavior; however, higher resisting torques were observed under higher loads. Muscle removal emulating a posterior surgical approach indicated alterations in THR loading and the instability process in contrast to a reference case with intact musculature. Based on the presented data, it can be concluded that the HiL test system is able to reproduce comparable joint dynamics as present in THR patients.