3D Truss Modular Layout Optimization With Relaxed Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for three-dimensional truss optimization face high calculation costs and complexity, especially in large-scale designs, limiting their application due to reliance on predefined modules and strict modular constraints, which hinder efficient design and manufacturing of complex structures.
Innovation Solution
A three-dimensional truss optimal designing and manufacturing method based on relaxed modular constraints, involving initial layout optimization, cluster analysis for module arrangement, and iterative relaxed modular constraint design, using cluster analysis and relaxed constraints to optimize module types and reduce structural volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If strict modular constraints and predefined modules are used in three-dimensional truss optimization, then manufacturing ease and assembly simplicity are improved, but device complexity and calculation cost increase significantly
Solution Approach 1:
The patent divides the truss structure into modular units that can be independently optimized and then assembled. The design domain is segmented into multiple sub-regions, each containing potential module candidates. This segmentation allows the complex optimization problem to be broken down into smaller, more manageable sub-problems, reducing overall computational complexity while maintaining manufacturability through standardized module assembly.
Solution Approach 2:
The patent introduces a dynamic optimization process where module types and arrangements are not fixed beforehand but evolve iteratively. The algorithm dynamically adjusts module configurations, merges similar modules, and optimizes module types during the design process. This dynamic approach allows the system to find optimal solutions without being constrained by predefined module catalogs, reducing device complexity while maintaining ease of manufacture.
2Volume of moving object
If various module types and arrangements are optimized simultaneously, then structural volume is reduced, but calculation cost increases
Solution Approach 1:
The optimization process is segmented into distinct phases: first identifying potential module candidates in sub-regions, then determining module types, and finally optimizing module arrangements. This segmentation of the optimization process allows each phase to focus on specific aspects, reducing overall calculation time while achieving volume reduction through systematic optimization of multiple module types and configurations.
Solution Approach 2:
The patent performs preliminary identification of module candidates and their potential arrangements before final optimization. By pre-processing the design domain into sub-regions and identifying potential module locations upfront, the algorithm reduces the search space for subsequent optimization steps. This preliminary action significantly reduces calculation time while still allowing for comprehensive optimization of structural volume in later stages.
3Manufacturing precision
If continuum topology optimization method is used for truss design, then structural optimization capability is improved, but applicability to large-scale problems decreases due to high calculation cost
Solution Approach 1:
The patent applies segmentation by dividing the continuous design domain into discrete sub-regions and identifying potential module candidates within each sub-region. This transformation of the continuous optimization problem into a discrete modular problem maintains the structural optimization capabilities of continuum topology optimization while significantly reducing computational complexity for large-scale applications. The segmented approach enables parallel processing and reduces memory requirements.
Solution Approach 2:
The patent substitutes the traditional continuum topology optimization mechanical system with a discrete modular optimization system. Instead of continuously varying material distribution throughout the design domain, the method uses discrete module units with defined geometries and properties. This substitution maintains optimization capability while improving computational efficiency and productivity for large-scale truss design problems.
Data Source
AI summary
Provided is a three-dimensional truss optimal designing and manufacturing method based on relaxed modular constraint. The method includes the following steps: initial design layout optimization, cluster analysis identification module arrangement, relaxed modular constraint design, geometric optimization, and 3D printing manufacturing and integrated assembly. The method has the following beneficial effect. A three-dimensional truss structure containing various module types is automatically designed by an iterative method. In the iterative process, a cluster analysis method is introduced to identify the module arrangement. By applying relaxed modular constraints, an optimized solution is gradually pushed to the modular structure. The optimization results of the three-dimensional truss have the characteristics of various types of modular structures, which is relatively easy to manufacture. An iterative solution method of cluster analysis identification module arrangement and relaxed modular constraint design is proposed.