Mechanical Part Microstructure Layout Using Orientation Tensor Fields

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Solution Overview

Problem

Current methods for designing mechanical parts with anisotropic materials lack control over local patterns, reliability in manufacturing, and high physical performance, particularly in creating efficient anisotropic microstructures.

Innovation Solution

A computer-implemented method that uses a multi-scale workflow involving a density field and an orientation tensor field to compute anisotropic reaction-diffusion patterns on higher resolution meshes, combining them through Boolean operations to design mechanical parts with tailored anisotropic microstructures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If traditional design methods are used for mechanical parts with anisotropic materials, then the design process is simpler, but the control over local patterns and manufacturing reliability is insufficient

Engineering Contradiction:
Improvecontrol over local patternsVSAvoiddesign method complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The design method segments the mechanical part into multiple scales: a first mesh for global topology optimization and a second mesh for local microstructure generation. This segmentation allows independent optimization at each scale, enabling precise control over local patterns while maintaining overall structural integrity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The invention implements local quality by using an orientation tensor field that varies spatially across the domain, allowing different regions to have different anisotropic orientations. The reaction-diffusion process then generates locally adapted microstructures that satisfy specific geometrical constraints and manufacturing requirements in each region.

Inventive Principle:
Principle #3Local quality

2Strength

If traditional design methods are used, then the computational process is faster, but the physical performance of anisotropic microstructures is reduced

Engineering Contradiction:
Improvephysical performance of anisotropic microstructuresVSAvoidcomputational time
Core Design Contradiction:
StrengthVSLoss of time

Solution Approach 1:

The method performs preliminary topology optimization on a coarse first mesh to obtain the density field and boundary definition before generating detailed microstructures. This preliminary action establishes the global structural framework, allowing subsequent fine-scale microstructure generation to focus only on local details, thereby reducing overall computational time.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The invention introduces a multi-scale dimensional approach by working with two different mesh resolutions simultaneously. The first mesh provides a coarse global view for topology optimization, while the second mesh provides a fine local view for microstructure generation, enabling high physical performance without proportional increase in computational cost.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

3Reliability

If detailed anisotropic microstructures are generated, then the manufacturing reliability improves, but the design complexity and computational resources increase

Engineering Contradiction:
Improvemanufacturing reliabilityVSAvoiddesign system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The invention changes parameters by using an orientation tensor field that encodes desired anisotropic behavior through mathematical parameters. The reaction-diffusion process transforms these tensor parameters into concrete microstructural patterns, providing a systematic way to control manufacturing reliability through parameter adjustment rather than complex geometric design.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The reaction-diffusion process acts as an intermediary between the orientation tensor field (representing desired anisotropic behavior) and the final microstructure geometry. This intermediary transforms abstract orientation information into manufacturable patterns, simplifying the design system while ensuring manufacturing reliability.

Inventive Principle:
Principle #24Intermediary (Mediator)

4Manufacturing precision

If high-resolution meshes are used for microstructure generation, then the design detail and regularity improve, but the computational cost increases

Engineering Contradiction:
Improvedesign detail and regularityVSAvoidcomputational time
Core Design Contradiction:
Manufacturing precisionVSLoss of time

Solution Approach 1:

The computational domain is segmented into two mesh levels: a coarse first mesh for global topology optimization and a fine second mesh for local microstructure generation. This segmentation allows high-resolution detailing only where necessary, reducing overall computational time while maintaining design detail and regularity in critical regions.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The coarse first mesh performs preliminary topology optimization to define the density field and domain boundaries before the fine second mesh generates detailed microstructures. This preliminary action prevents unnecessary fine-scale computations in regions where only coarse topology is needed, optimizing the computational time-to-detail ratio.

Inventive Principle:
Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enables the creation of mechanical parts with improved regularity and high physical performance, facilitating efficient manufacturing and detailed design, especially in additive manufacturing.

Implementation Method 1

The method further comprises for each i th principal direction of the orientation tensor field computing by a reaction-diffusion process an anisotropic reaction-diffusion pattern

Methodology Applied
Scientific EffectReaction-diffusion: Diffusion

Data Source

PatentEP4163812A1Designing a modeled object
Publication Date: 2023.04.12 DASSAULT SYSTEMES SA
  • EP4163812A1 patent drawingFigure 1
  • EP4163812A1 patent drawingFigure 2
  • EP4163812A1 patent drawingFigure 3A~3D

AI summary

The disclosure notably relates to a computer-implemented method for designing a modeled object representing a mechanical part formed in a material having an anisotropic behavior with respect to a physical property. The method comprises providing a first mesh, a density field representing at least boundary of the modeled object, and an orientation tensor field representing a desired anisotropic behavior. The method further comprises, for each ith principal direction of the orientation tensor field, computing an anisotropic reaction-diffusion pattern on an ith mesh, the ith mesh having higher resolution than the first mesh and being bounded by the boundary of the modeled object. The method further comprises combining by Boolean operations the computed anisotropic reaction-diffusion patterns projected on a second mesh.