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Content available remote Assessment of the role of structural nonlinearity in galloping energy harvesters
Sarbinowski Filip, Starosta Roman
Vibrations in Physical Systems
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2021
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Vol. 32, nr 2
art. no. 2021209
EN
The study compares different variants of aeroelastic energy harvesters due to the power they generate. For this purpose, models of devices with different stiffness characteristics were prepared: linear, nonlinear, with combined stiffness and bistable. Then, using the authorial procedure, analytical expressions that describe the power of each system were determined and the influence of individual parameters on this quantity was examined. By way of optimization, the system parameters have been selected in such a way that, regardless of the flow velocity, each of them generates the maximum possible power. Based on the results obtained in this way, the advisability of using a device with combined stiffness and bistable characteristics was rejected. Moreover, it was pointed out that the linear system would provide greater efficiency for lower flow velocities.
2
Content available Minimization of critical flow velocity of aeroelastic energy harvester via delayed feedback control
Sarbinowski Filip, Starosta Roman
Vibrations in Physical Systems
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2020
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Vol. 31, nr 2
art. no. 2020225
EN
The paper describes the procedure of modelling and optimization of the aeroelastic energy harvester from the point of view of their operation at very low flow velocities. Using analytical solutions of models of different device variants, the relationships between their efficiency and flow velocity were presented. By way of analytical considerations, the conditions for high performance operation of the device have been demonstrated, indicating at the same time the difficulty in maintaining it at low operation velocities. As a solution to the problem, the application of external delayed feedback control was proposed and its effectiveness was demonstrated.
3
Content available AI-based method of vortex core tracking as an alternative for Lambda2
Majchrzak Maciej, Jakubowski Mateusz, Starosta Roman
Vibrations in Physical Systems
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2020
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Vol. 31, nr 3
art. no. 2020319
EN
The paper presents a new method of vortex core detection developed for use in CFD simulation result analysis. Apart from the conventional approach involving vector algebra, mainly the Lambda2 method, it focuses on the identification of certain features in a graphic representation of the velocity field. It is done by generating a series of slices of the said field in the postprocessing software and training a Convolutional Neural Network (AI) to recognize vortex cores. The neural network can be integrated into a simple python program and used to quickly identify vortex cores on a large number of images and translate their locations to coordinates of a CFD model for visualisation.
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