Mixed composite material layering method considering multi-scale uncertainty

A technology of composite materials and uncertainty, applied in the direction of neural learning methods, biological neural network models, instruments, etc., can solve the complex and cumbersome design process of hybrid composite materials and other problems

Pending Publication Date: 2021-03-09
ZHEJIANG UNIV OF TECH
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  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to solve the complex and cumbersome design process of hybrid composite materials, and pr

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  • Mixed composite material layering method considering multi-scale uncertainty
  • Mixed composite material layering method considering multi-scale uncertainty
  • Mixed composite material layering method considering multi-scale uncertainty

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Embodiment Construction

[0054] Below in conjunction with accompanying drawing and embodiment the present invention will be further described, but protection scope of the present invention is not limited thereto, and method of the present invention specifically comprises the following steps, as image 3 and Figure 4 Shown:

[0055] 1. Determine the basic information of the hybrid composite material to be analyzed: the boundary condition is a nine-layer hybrid composite material simply supported on four sides, the length L=0.508m, the width W=0.406m, and the thickness of each layer is ΔT=0.125mm. The largest overall cost parameter C=9.5USD, the minimum failure probability is Among them, the reliability parameter P f The relationship with the failure parameter FI is: P f =P[1-FI≤0], P is the distributed force on the hybrid composite. Select three candidate materials: material Ⅰ, material Ⅱ, and material Ⅲ. In subsequent calculations, "1" will be used to represent material Ⅰ, "2" will represent mat...

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Abstract

The invention discloses a mixed composite material layering method considering multi-scale uncertainty. The method comprises the steps of selecting an alternative material set, obtaining the microscopic attributes of the alternative material set, and obtaining the distribution type of macroscopic attributes of the alternative material set through a multi-scale analysis model; determining a macroscopic finite element model of the alternative material set by utilizing the macroscopic attributes and the distribution types of the macroscopic attributes; constructing a neural network model of the microscopic attributes of the alternative material set and the mixed composite material parameters, calculating a mean square error MSE for the trained neural network model, and judging the accuracy ofthe trained neural network model according to the mean square error MSE; and optimizing the selection of the alternative material set and the selection of the layer stacking sequence by using a genetic algorithm. According to the method, multiple optimization algorithms are used, so that the burden of designers and computers is greatly reduced, the calculation speed is greatly increased, the optimization accuracy is also improved, Meanwhile the method is more suitable for engineering practical application.

Description

technical field [0001] The invention belongs to the field of methods for optimizing the stacking sequence and material distribution of fiber reinforced composite materials, and in particular relates to a multi-scale uncertainty layup optimization method for a type of hybrid composite materials. Background technique [0002] Fiber-reinforced composites have the advantages of high strength-to-weight ratio, high stiffness-to-weight ratio, and low cost under various loads, and their applications in automotive, marine, civil, aerospace, and construction are growing exponentially. In contrast to traditional composites consisting of single fibers and a single matrix, hybrid composites are manufactured by combining two or more fibers into one matrix. The properties of a hybrid composite are the weighted sum of the individual components, with the strengths of one fiber compensating for properties lacking in other types of components in the hybrid composite. At the same time, for the...

Claims

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Application Information

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IPC IPC(8): G06F30/23G06F30/27G06N3/04G06N3/08G06F113/26G06F111/10
CPCG06F30/23G06F30/27G06N3/086G06F2113/26G06F2111/10G06N3/045
Inventor 彭翔郭玉良王明博高启龙李吉泉姜少飞景立挺吴化平张征
Owner ZHEJIANG UNIV OF TECH
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