Mistuning, which refers to inevitable variations in blades properties, will change the vibration of bladed disks dramatically. Bladed disks are exposed to effects of forces caused by bladed disk rotation, such as centrifugal and Coriolis forces. However, there is little research on the vibration behavior of a realistic bladed disk with Coriolis force. An investigation of the speed effect, i.e., the effects of centrifugal and Coriolis forces, on the vibration characteristics of a realistic mistuned bladed disk model is presented in this paper. Finite element method (FEM) is used to obtain the system mass, stiffness and damping matrix. The effects of Coriolis force and centrifugal force on the modal frequency and harmonic response characteristics of tuned bladed disk are investigated first, then the modal localization and response characteristics of mistuned bladed disk are researched. This investigation indicates that: Coriolis force has efficient influences on the modal and response characteristics of a realistic mistuned bladed disk: it can both increase and decrease the localization of the mistuned bladed disk for different situations.
The periodic flows, such as vortex shedding and rotating flow in turbomachinery, are very common in both scientific and engineering fields. However, high-fidelity numerical simulations of unsteady flows are usually time-consuming, particularly when varying flow parameters need to be considered. In this paper, a novel nonintrusive parametrized reduced order model (PROM) approach for prediction of periodic flows is presented. The establishment of this ROM is based on two techniques, proper orthogonal decomposition (POD) and discrete Fourier transform (DFT), where the first one can extract the spatial features and the second has the ability to quantify the temporal effects of parameters. A prediction model based on artificial neural networks (ANNs) is used to map the flow parameters with DFT coefficients. Flows past a cylinder and two dimensions turbine flows are used to demonstrate the effectiveness of the proposed PROM. It is shown that the proposed POD-DFT-ANN (PDA) ROM are both efficient and accurate for the predictions of periodic flows with varying flow parameters.
The forced responses of bladed disks are highly sensitive to inevitable random mistuning. Considerable computational efforts are required for the sampling process to assess the statistical vibration properties of mistuned bladed disks. Therefore, efficient surrogate models are preferred to accelerate the process for probabilistic analysis. In this paper, four surrogate models are utilized to construct the relation between random mistuning and forced response amplitudes, which are polynomial chaos expansion (PCE), response surface method (RSM), artificial neural networks (ANN) and Kriging interpolation, respectively. A bladed disk with 2-degrees-of-freedom (2-DOF) each sector is used to validate the effectiveness of the surrogate models. The effects of number of training samples on the surrogate model accuracy are discussed. The responses results of one blade (single output) and maximum response of all blades (multi-output) indicate that PCE and Kriging interpolation could yield accurate and stable predictions of the statistical characteristics of the forced responses. PCE is recommended for the mistuned response predictions due to its accuracy and efficiency.
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