Automated Fatigue Margin Correction for Structural Components
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Solution Overview
Problem
Current methods for fatigue and structural analysis of structural components, such as aircraft and bridges, are inefficient in identifying and correcting negative fatigue margins, often requiring manual trial and error, which can lead to increased weight and cost due to non-optimal dimensional adjustments and lack of automated data organization and biaxial stress analysis.
Innovation Solution
An automated system and method that uses a processor to calculate fatigue margins for structural components, identifies negative margins, and adjusts dimensional characteristics locally to achieve positive margins with minimal weight impact, utilizing finite element models and iterative processes to optimize structural design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual trial and error methods are used to adjust dimensional characteristics, then fatigue margins can be corrected, but the process is inefficient and increases weight and cost
Solution Approach 1:
The system automatically performs fatigue analysis and identifies negative fatigue margins without requiring manual intervention. The automated iterative process adjusts dimensional characteristics itself based on the analysis results, eliminating the need for manual trial and error methods while maintaining reliability of fatigue margin correction.
Solution Approach 2:
The patent replaces manual mechanical trial and error adjustments with an automated computational system. The processor automatically calculates fatigue margins, identifies problematic areas, and adjusts dimensional characteristics through iterative computational processes, substituting manual mechanical methods with automated digital systems.
2Reliability
If dimensional characteristics are adjusted to correct negative fatigue margins, then fatigue life is improved, but weight increases
Solution Approach 1:
The system adjusts dimensional characteristics locally only at specific areas where negative fatigue margins are identified, rather than uniformly increasing dimensions throughout the entire structure. This localized adjustment approach corrects fatigue issues while minimizing unnecessary weight increases in areas that do not require reinforcement.
Solution Approach 2:
The automated system iteratively adjusts dimensional parameters (such as thickness or cross-sectional dimensions) at critical locations to achieve positive fatigue margins. By systematically varying these parameters and recalculating fatigue margins in each iteration, the system optimizes the balance between fatigue life improvement and weight minimization.
3Weight of moving object
If automated iterative adjustment is used, then weight is minimized, but computational complexity increases
Solution Approach 1:
The automated system divides the structural analysis into discrete segments by identifying specific details of interest where negative fatigue margins occur. Rather than analyzing the entire structure uniformly, the system segments the problem into localized areas requiring adjustment, making the computational process more manageable and efficient while still achieving optimal weight reduction.
4Manufacturing precision
If manual trial and error methods are used, then dimensional adjustments can be made, but costs increase due to inefficiency
Solution Approach 1:
The automated system incorporates feedback loops where fatigue margins are calculated, areas with negative margins are identified, dimensional adjustments are automatically applied, and the analysis is repeated. This iterative feedback process continuously refines the dimensional characteristics to achieve optimal fatigue performance, eliminating costly manual trial and error methods while maintaining manufacturing precision.
Data Source
AI summary
Methods and apparatus for analyzing fatigue of a structure and optimizing a characteristic of the structure based on the fatigue analysis are disclosed herein. An example method disclosed herein includes obtaining mass and unit stress values of a plurality of details of interest of a structural component, calculating fatigue margins for each of the details of interest, identifying among the calculated fatigue margins any negative fatigue margins associated with one or more of the details of interest, and adjusting, via a processor, a dimensional characteristic of each detail of interest associated with the negative fatigue margin(s) until positive fatigue margin(s) at each detail of interest is obtained.


