Periodic Cellular Structure Design for Additive Manufacturing
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Solution Overview
Problem
Current additive manufacturing techniques face challenges in accurately predicting and tuning the physical properties of cubic periodic cellular structures (CPCS) for structural components, requiring extensive experimental data and lacking efficient methods to optimize their geometry and orientation for specific mechanical behaviors.
Innovation Solution
The system and method involve analyzing and predicting structural properties of CPCS using finite element analysis, allowing for the selection of different unit cells and orientations to tune physical properties, with a focus on compressive deformation responses, and employing surrogate models for optimization, enabling the design of lightweight and strong functional parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Weight of moving object
If cellular structures are used to reduce weight, then weight is reduced, but manufacturing precision and prediction accuracy deteriorate due to lack of experimental data
Solution Approach 1:
The patent creates a digital surrogate model that copies and simulates the physical behavior of CPCS. Instead of relying on extensive physical experiments, the surrogate model replicates the mechanical response of cellular structures through computational simulation, enabling accurate prediction of physical properties without requiring numerous physical prototypes or test specimens.
Solution Approach 2:
The patent replaces the traditional experimental mechanical testing system with a computational surrogate model. The surrogate model uses finite element analysis and machine learning to substitute physical compression tests and material characterization experiments, enabling virtual prediction of mechanical behaviors including compressive deformation responses.
2Measurement precision
If extensive experimental data is collected to improve prediction accuracy, then measurement precision improves, but loss of time and productivity deteriorate
Solution Approach 1:
The patent performs preliminary action by creating a comprehensive surrogate model before actual manufacturing and testing. The surrogate model is trained on a limited set of experimental data and then used to predict the behavior of various CPCS configurations, eliminating the need for extensive time-consuming experiments for each new design iteration.
Solution Approach 2:
The surrogate model creates a digital copy of the physical experimental system, allowing virtual experimentation instead of physical testing. This copying approach enables rapid prediction of mechanical properties without repeating time-consuming compression tests and material characterization experiments for each design variant.
3Strength
If unit cell geometry and orientation are optimized for specific mechanical behaviors, then strength is improved, but device complexity increases
Solution Approach 1:
The patent optimizes the physical properties of CPCS by systematically varying geometric parameters such as unit cell shape, size, and orientation angles. The surrogate model enables efficient exploration of parameter space to identify optimal combinations that maximize compressive strength and structural integrity while minimizing weight, without requiring complex manufacturing processes.
Solution Approach 2:
The patent applies different unit cell configurations and orientations to different regions of the functional part based on local stress and loading conditions. The surrogate model predicts the mechanical behavior of each regional configuration, enabling localized optimization of geometry to enhance strength where needed while maintaining simplicity in less critical areas.
Data Source
AI summary
A method of additively manufacturing a 3D structure, comprising defining a boundary conditions, load constraints, and a periodic cell structure for lattifying the 3D structure; providing a surrogate FE model predicting a relationship between the boundary conditions, load constraints, periodic cell structure, and 3D orientation angle of the periodic cell structure; optimizing lattification of the 3D structure, according to orientation angle, and a cost function while meeting the load constraints; and additively manufacturing the optimized 3D structure, optimized e.g., for mass and stress concentration under a pre-determined loading condition.