Hybrid Material Model Fitting for Accurate 3D Morphology
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Solution Overview
Problem
Industrial CT scanning struggles to accurately differentiate between multiple morphologies in materials with complex structures, such as woven materials, leading to inaccurate three-dimensional representations and models that deviate from the actual configuration.
Innovation Solution
A system and method that utilize a geometric template defined by geometric parameters and constraints, iteratively adjusting these parameters to align a model of a material with its three-dimensional representation based on measurements, ensuring the model accurately reflects the material's physical dimensions and constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If industrial CT scanning is used to produce three-dimensional representations of materials, then the ability to inspect and measure internal sections is improved, but the accuracy of representing complex material morphologies deteriorates
Solution Approach 1:
The patent transforms the three-dimensional representation data into updated geometric parameters that define the material morphology. By changing from raw imaging data to parameterized geometric descriptions, the system achieves both accurate representation and ease of measurement, resolving the contradiction between measurement precision and detection difficulty
Solution Approach 2:
The patent creates an idealized geometric model that copies and represents the complex material morphology. This geometric copy serves as an accurate simplified representation that maintains the essential geometric characteristics while being easier to measure and analyze, thus resolving the contradiction between detailed accuracy and measurement ease
2Manufacturing precision
If a geometric template model is used to represent material morphology, then the model accuracy is improved, but the computational complexity of iteratively adjusting parameters increases
Solution Approach 1:
The patent segments the complex morphology adjustment problem into discrete geometric parameters that can be individually optimized. By dividing the overall shape into parameterized components, the system achieves high model accuracy while making the computational process more manageable through structured parameter optimization rather than full-model reprocessing
Solution Approach 2:
The patent implements an iterative process where geometric parameters are dynamically adjusted based on differences between the idealized model and actual three-dimensional representation. This dynamic parameter optimization continues until convergence, achieving high accuracy while the iterative nature allows progressive refinement rather than requiring complete recalculation
Data Source
AI summary
The disclosure describes a method by a controller that includes: executing a model of a material based on a geometric template of the material defined by geometric parameters and at least one geometric constraint of the material; determining a value of an objective function based on differences between a three-dimensional representation of the material based on measurements of the material and the model of the material based on the geometric template of the material; and determining updated values of the geometric parameters of the geometric template. The method further includes iterating the executing the model of the material, the determining the value of the objective function, and the determining the updated values of the geometric parameters until a parameter associated with the objective function satisfies a criterion and, outputting the updated values of the geometric parameters associated with the objective function that satisfies the criterion.