A Neural Network-Based Method for Optimizing the Ply Angle of a Composite Propeller
A composite material and neural network technology, which is applied in the optimization of the layup angle to maximize the propulsion efficiency of the composite propeller of ships and ships, and the field of layup angle optimization of the composite propeller, which can solve the problem of not carefully considering the back pitch, trim and angle of the blade. Changes in pitch, dependence on finite element software, lack of versatility and other problems, to achieve the effect of saving computing resources and time, simple calculation, and small amount of calculation
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[0044] The present embodiment discloses in conjunction with accompanying drawing, take SEIUN-MARU large skew ship propeller (HSP) as embodiment, the specific embodiment of the present invention is as follows Figure 1-3 shown. The fiber composite material marine propeller ply angle optimization method disclosed in this implementation is realized by the following steps:
[0045] Step 1: Use the ACP module in the WorkBench platform to define the angles of each layer of the composite laminate with the middle surface of the metal propeller blade as the symmetry center to complete the fiber composite layer (unidirectional or braided layer), and import the metal The pressure surface and suction surface models of the propeller blades are used to constrain the shape of the composite material layup, and finally the establishment of the finite element model of the composite material propeller is realized.
[0046] Step 2: Import the finite element model of the composite propeller estab...
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