Abstract
This paper presents a novel method for the maximization of eigenfrequency gaps around external excitation frequencies by stacking sequence optimization in laminated structures. The proposed procedure enables the creation of an array of suggested lamination angles to avoid resonance for each excitation frequency within the considered range. The proposed optimization algorithm, which involves genetic algorithms, artificial neural networks, and iterative retraining of the networks using data obtained from tentative optimization loops, is accurate, robust, and significantly faster than typical genetic algorithm optimization in which the objective function values are calculated using the finite element method. The combined genetic algorithm–neural network procedure was successfully applied to problems related to the avoidance of vibration resonance, which is a major concern for every structure subjected to periodic external excitations. The presented examples illustrate a combined approach to avoiding resonance through the maximization of a frequency gap around external excitation frequencies complemented by the maximization of the fundamental natural frequency. The necessary changes in natural frequencies are caused only by appropriate changes in the lamination angles. The investigated structures are thin-walled, laminated one- or three-segment shells with different boundary conditions.
Highlights
For many years, composites have been used for a variety of applications, such as mechanical, aerospace, and civil engineering structures [1,2,3]
This paper presents the maximization of the fundamental natural frequency by determining the optimal fiber orientation in a cylindrical shell’s layers of composite material
In order to verify the compatibility of MODEL3 with the FE model used by Koide and Luersen in [41], the fundamental natural frequency was calculated for three different stacking sequences described in [41] and compared with the values in that paper
Summary
Composites have been used for a variety of applications, such as mechanical, aerospace, and civil engineering structures [1,2,3]. Vortex-induced vibration strictly depends on the natural frequencies of the risers, so there is a need for optimizing the design of fiber reinforced polymer composite risers by considering different laminate stacking sequences and different lamina thicknesses [14,15] This approach grants the possibility of avoiding resonance if external excitation frequencies are confined to a large interval with finite lower and upper limits [16]. The fiber orientation angles in all layers were selected, and the search for the optimum solution in N-dimensional space was replaced by N repetitions of the optimization, with each repetition in one-dimensional space This idea is based on the physical consideration of bending plates, during which the outer layer has a greater influence on the structure stiffness than the inner layer and is more important in the determination of the natural frequency. The results obtained using the proposed method are more accurate and significantly less time-consuming—which should be emphasized—because so-called “deep networks” were applied, enabling the use of very large sets, with the number of patterns reaching at least 10,000
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