Generative 3D Shape Optimization for Fatigue Loading Cycles
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Solution Overview
Problem
Current CAD software lacks the capability to effectively optimize 3D geometry designs for physical structures under loading cycles, particularly in preventing damage from fatigue, especially when dealing with multiple materials and complex loading scenarios, which can lead to catastrophic failures.
Innovation Solution
A computer-aided design program that iteratively modifies a generatively designed 3D shape by performing numerical simulations, calculating stress and strain elements, determining expected loading cycles, and redefining fatigue safety factors to prevent damage, using level-set representations and PID controllers for stabilization, allowing for the optimization of designs based on user-specified fatigue constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current CAD software is used for 3D geometry generation, then basic design objectives can be met, but fatigue damage prevention under loading cycles cannot be effectively achieved
Solution Approach 1:
The patent implements an iterative optimization process where numerical simulations of physical responses are performed, fatigue damage is assessed based on loading cycles, and the 3D geometry is continuously modified according to feedback from damage assessments. This closed-loop feedback mechanism enables the system to progressively improve fatigue resistance by adjusting design parameters based on simulated performance data.
Solution Approach 2:
The patent performs fatigue damage assessment and optimization during the design phase before actual manufacturing and use. By conducting numerical simulations and evaluating fatigue damage accumulation under expected loading cycles in advance, the system prevents catastrophic failures before they occur in service, rather than reacting to failures after they happen.
2Adaptability or versatility
If generative design is used to optimize 3D geometry, then design objectives can be improved, but the capability to handle multiple materials and complex loading scenarios is lacking
Solution Approach 1:
The patent creates a universal optimization framework that can handle multiple materials with different fatigue properties and various complex loading scenarios (static loads, dynamic loads, thermal loads) through a single integrated system. The numerical simulation engine and fatigue assessment methodology are designed to accommodate diverse material types and loading conditions, making the tool broadly applicable to different manufacturing scenarios.
Solution Approach 2:
The patent optimizes design parameters such as geometry shape, material distribution, and structural configuration to prevent fatigue damage accumulation. By adjusting these parameters based on simulation results and fatigue assessment data, the system achieves precise design optimization that accounts for multiple materials and complex loading conditions, thereby improving manufacturing precision.
3Reliability
If fatigue safety factors are not considered in design, then design process is simpler, but catastrophic failures can occur under repeated loading
Solution Approach 1:
The system implements continuous feedback regarding fatigue damage accumulation and safety factor compliance throughout the iterative design process. The numerical simulations provide feedback on stress and strain responses, which are used to assess fatigue damage and adjust the geometry to maintain adequate safety factors, preventing catastrophic failures through proactive monitoring and adjustment.
Data Source
AI summary
Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes obtaining a design space for a modeled object, one or more design criteria, one or more in-use load cases, and one or more specifications of material, wherein the design criteria comprise a required number of loading cycles for the modeled object; iteratively modifying a generatively designed three dimensional shape of the modeled object, comprising: performing numerical simulation of the modeled object, finding a maximized stress or strain element for each of the one or more in-use load cases, determining an expected number of loading cycles for each of the one or more in-use load cases, redefining a fatigue safety factor inequality constraint for the modeled object, computing shape change velocities in accordance with at least the fatigue safety factor inequality constraint, and updating the level-set representation.