Composite Material Hole Reinforcement Optimization
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Solution Overview
Problem
In composite materials with reinforcement fiber laminates, forming holes in the lamination direction leads to stress concentration at the hole rim, which is mitigated by adding reinforcement parts, but this increases weight, necessitating a method to reduce both stress concentration and weight.
Innovation Solution
A computer-implemented method optimizing the shape of the hole, reinforcement part, and orientation angles of reinforcement fiber layers using a genetic algorithm to minimize strain values under load conditions, thereby reducing stress concentration and reinforcement part size while maintaining structural integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stress or pressure
If a reinforcement part is provided around the hole to reduce stress concentration, then the stress concentration at the hole rim is reduced, but the weight of the composite material increases
Solution Approach 1:
The patent applies parameter changes by optimizing multiple design variables including the shape of the hole, the shape of the reinforcement part, and the orientation angles of reinforcement fiber layers. A genetic algorithm is used to systematically vary these parameters to find the optimal configuration that reduces stress concentration while minimizing the size and weight of the reinforcement part.
Solution Approach 2:
The patent implements local quality by providing reinforcement specifically around the hole area where stress concentration occurs, rather than uniformly reinforcing the entire composite material. The optimization process determines the precise local geometry and fiber orientation needed at the hole vicinity to achieve stress reduction with minimal additional weight.
2Weight of moving object
If the shape of the reinforcement part and orientation angles are optimized to reduce weight, then the weight of the composite material is reduced, but the stress concentration at the hole rim may increase
Solution Approach 1:
The patent uses a genetic algorithm to systematically explore and optimize multiple parameters simultaneously, including the reinforcement part shape and fiber orientation angles. This multi-parameter optimization ensures that weight reduction does not compromise stress concentration control, as the algorithm finds the balanced configuration that satisfies both requirements.
Solution Approach 2:
The optimization process incorporates feedback through the genetic algorithm, which evaluates the performance (stress concentration and weight) of each candidate design and uses this information to guide subsequent generations of designs. This iterative feedback mechanism ensures that weight reduction efforts do not lead to increased stress concentration.
3Device complexity
If only the shape of the hole is optimized, then the design complexity is reduced, but the stress concentration reduction is insufficient compared to optimizing all parameters
Solution Approach 1:
The patent comprehensively optimizes multiple parameters including hole shape, reinforcement part shape, and fiber orientation angles using a genetic algorithm. This multi-parameter approach achieves superior stress concentration reduction compared to optimizing only the hole shape, while the automated optimization process manages the increased design complexity efficiently.
Data Source
AI summary
A computer-implemented method is for designing a composite material in which reinforcement fiber base materials are laminated. The composite material includes a hole extending in a lamination direction of the reinforcement fiber base materials and a reinforcement part provided around the hole. The method includes calculating a strain value generated in the composite material based on design factors and a predetermined load condition, the design factors including a shape of the hole, a shape of the reinforcement part, and an orientation angle of each of the reinforcement fiber base materials in respective layers of the reinforcement part; and optimizing the design factors based on a genetic algorithm such that the calculated strain value tends to decrease.