Load Distribution Modeling for Balanced Multi-Point Force Layouts

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Solution Overview

Problem

The development of load distribution systems, including whiffletrees, is time-consuming and prone to human error, leading to undesirable or unbalanced distribution of loads to a structure, especially as the number of load points increases, resulting in numerous unsuitable or unfeasible configurations.

Innovation Solution

A computing system employs a regression algorithm to segment load points into subgroups and generate a model of a load distribution system, which can be refined by users, incorporating changes and outputting an updated model.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual design methods are used for load distribution systems, then flexibility in design adjustments is maintained, but the design process becomes time-consuming and prone to human error

Engineering Contradiction:
Improvedesign accuracyVSAvoiddesign time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical design processes with an automated computing system that uses algorithms to calculate and optimize load distribution configurations. The system automatically determines member forces, identifies valid configurations, and generates design models without human intervention, eliminating time-consuming manual calculations while maintaining high accuracy through systematic computational methods.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The design system performs self-validation by automatically checking whether calculated configurations satisfy all design constraints and validity criteria. The system independently identifies invalid configurations and iterates to find valid solutions without requiring external verification, enabling rapid design exploration and optimization while ensuring reliability through built-in validation mechanisms.

Inventive Principle:
Principle #25Self-service

2Adaptability or versatility

If the number of load points increases to improve load distribution coverage, then better load distribution is achieved, but the complexity of system configuration increases leading to more unsuitable configurations

Engineering Contradiction:
Improveload distribution capabilityVSAvoidconfiguration complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the complex design space by systematically evaluating each potential configuration through automated calculation of member forces and validity checks. The computing system divides the overall design problem into discrete configuration options, each subjected to systematic validation against design constraints, enabling manageable analysis of complex multi-load-point systems while identifying only valid configurations.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system automatically adjusts design parameters such as member orientations, connection configurations, and load path assignments to optimize the load distribution system for varying numbers of load points. By dynamically changing these parameters based on computational analysis, the system adapts to different configuration complexities while maintaining design validity and eliminating unsuitable configurations through automated constraint checking.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP4675486A1Model generation for load distribution systems
Publication Date: 2026.01.07 THE BOEING CO
  • EP4675486A1 patent drawingFigure 1
  • EP4675486A1 patent drawingFigure 2
  • EP4675486A1 patent drawingFigure 3

AI summary

A computing system performs a method for generating a model of a load distribution system. The computing system receives a respective location of each load point, a respective force to be applied at each load point, and a force direction. A load segmentation loop is performed over a plurality of iterations that includes: selecting an iteration group of load points from among the set of load points, determining a weighted linear regression line and a center of force for the iteration group, identifying a first subgroup of load points that are located on a first side of a boundary line, and identifying a second subgroup of load points that are located on a second side of the boundary line. The model of the load distribution system is generated based on the center of force, the first subgroup, and the second subgroup of one or more iterations of the loop.