Reinicke, Prof. Dr.-Ing. Tamara
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Publication Access status: Open Access , A WaveNet-based fully stochastic dynamic stall modelAccurate modeling of the dynamic stall remains a challenge for the design and construction of turbine blades and helicopter rotors. At the same time, wind turbines, for instance, are becoming steadily larger, further increasing the demands on their structure and necessitating even more detailed modeling of the forces at hand. The primarily used (semi-)empirical models today have a long research history and are invariably based on phase-averaged data from oscillating blade pitch experiments. However, much potential for more accurate modeling of uncertainties and force peaks is wasted here, since averaging blurs many features of the response signals. Even computational fluid dynamics can help little in this regard, since the Reynolds-averaged Navier–Stokes equations used in practice cannot account for cycle variations, and scale-resolving models require extremely large amounts of computational resources. This paper presents an approach for a fully stochastic machine learning model that can nevertheless simulate these critical properties. Aerodynamic coefficients are compared with experimental data for different test cases. It is shown that synthetic force profiles which cannot be distinguished from the experimental data visually and are very close to them in the frequency spectrum can be generated. Additionally, attention is drawn to the difficulty of evaluating such a model, as traditional error metrics are of little use. A combination of dynamic time warping and the Earth mover's distance provides a robust solution for this problem.Source Type:Article345 102 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Open Access , Characterization of 3D-printed PLA parts with different raster orientations and printing speedsFabrication based on additive manufacturing (AM) process from a three-dimensional (3D) model has received significant attention in the past few years. Although 3D printing was introduced for production of prototypes, it has been currently used for fabrication of end-use products. Therefore, the mechanical behavior and strength of additively manufactured parts has become of significant importance. 3D printing has been affected by different parameters during preparation, printing, and post-printing processes, which have influence on quality and behavior of the additively manufactured components. This paper discusses the effects of two printing parameters on the mechanical behavior of additively manufactured components. In detail, polylactic acid material was used to print test coupons based on fused deposition modeling process. The specimens with five different raster orientations were printed with different printing speeds. Later, a series of tensile tests was performed under static loading conditions. Based on the results, strength and stiffness of the examined specimens have been determined. Moreover, dependency of the strength and elastic modulus of 3D-printed parts on the raster orientation has been documented. In the current study, fractured specimens were visually investigated by a free-angle observation system. The experimental findings can be used for the development of computational models and next design of structural components.Source Type:Article350 116 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Open Access , Effects of steps on the load bearing capacity of 3D-printed single lap jointsDamage in adhesively bonded joints typically initiates in the overlap area due to high level of bonding (peel) stress. Different approaches are being considered to decrease the peel stress and improve the overall strength of the joint. One possible approach is to shape the over lap area into a stepped form configuration and enhance the performance of the joint. In the current study, we investigate effects of stepped-shape overlap area on the load bearing capacity of additively manufactured single-lap joints. To this aim, stepped-lap adhesively bonded joints with different designs and geometries in the overlap (bonding) area are considered with 3D-printed polylactic acid (PLA) adherends using the fused deposition modeling (FDM) process. Three configurations with different step sizes are considered to manufactured a set of adhesively bonded single-lap joints and to investigate the optimum length of the steps. The results are compared with our previous experimental findings on 3D-printed conventional single-lap joints. The obtained outcomes reveal that creating steps in the overlap area has a significant influence on the structural integrity and fracture load of 3D-printed adhesive-bonded joints and the bonded structures with identical step size in boding area reveal a better performance in load carrying capacity and shows a higher fracture load. Parallel to the experimental practices, a finite element model also developed to simulate the load carrying performance of the adhesively bonded singlelap joints with equal step size and 3D-printed PLA adherends. The FE model confirms the experimental outcomes and reveals the details of the cohesive failure and damage evolution mechanism in this bonded structures with PLA printed adherends. The proposed technique has a great potential to be a competitive alternative to conventional single-lap joints made by 3D printing. The presented results can be used for further fabrication of 3D-printed joints with a better structural performance.Source Type:Article355 294 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Open Access , Performance optimization of a Kirsten–Boeing turbine by a metamodel based on neural networks coupled with CFDThe supply of energy is sustainable only if it is predominantly based on renewable or regenerative energies. For this reason, the use of micro-hydropower plants on rivers and streams is considered recently. This is a particular challenge for the preservation of ecologically permeable streams, so that no dams or similar structures can be considered. While the axial turbine design has prevailed in wind power, there is still no consensus for the generation of energy in free water flow conditions. In this work, an existing prototype of an unusual vertical axis Kirsten–Boeing turbine was investigated. A multivariate optimization process was created, in which all important machine parameters were checked and improved. By using neural networks as a metamodel coupled with flow simulations in ANSYS CFX, a broadly applicable optimization strategy is presented that yielded a blade design that is 36% more efficient than its predecessor in experiments. During the process, it was shown how to set up a complex sliding mesh problem with ANSYS expressions while evaluating a free surface problem.Source Type:Article457 126