Modular Mesh Generation for Resin Transfer Molding
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Solution Overview
Problem
The complexity of resin products in the resin transfer molding (RTM) process makes it time-consuming for computer-aided engineering (CAE) to accurately predict resin flow, necessitating an efficient method for forecasting the RTM process.
Innovation Solution
A mesh generation method that involves obtaining the geometry of a target object, generating a solid mesh with modular meshes of different grid dimensions, assembling a runner mesh with unique grid dimensions, determining process parameters, and generating a forecasted result using computational fluid dynamics, with iterative adjustments to parameters and orientations as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CAE methods are used to predict resin flow in RTM process, then prediction accuracy is improved, but time consumption increases significantly
Solution Approach 1:
The patent divides the target object into multiple modules, each with its own mesh structure. This segmentation allows parallel processing of different modules, reducing overall computation time while maintaining prediction accuracy through localized detailed meshing in critical areas.
Solution Approach 2:
The patent introduces a multi-scale mesh approach with different grid dimensions at different locations and levels of detail. Fine mesh is applied to critical regions requiring high prediction accuracy, while coarse mesh is used in non-critical areas, reducing total element count and computation time while maintaining overall prediction quality.
2Measurement precision
If fine mesh is used throughout the entire target object, then prediction accuracy is improved, but computational complexity and time increase
Solution Approach 1:
The patent applies different mesh densities to different regions of the target object based on their importance to resin flow prediction. Critical regions such as gate areas, thick sections, and geometrically complex zones receive fine meshing, while simple regions use coarser meshing, optimizing the balance between accuracy and computational complexity.
Solution Approach 2:
The patent implements a multi-resolution mesh strategy where the overall domain uses a coarser base mesh, and localized fine meshes are overlaid only in regions requiring high prediction accuracy. This dimensional approach to mesh refinement reduces total element count while maintaining prediction quality in critical areas.
3Ease of manufacture
If uniform mesh dimensions are used for runner and target object, then mesh generation simplicity is improved, but adaptability to different process requirements decreases
Solution Approach 1:
The patent implements a dynamic mesh system where the runner mesh and target object mesh can have independent, adjustable dimensions and densities. This allows the mesh structure to adapt to different process requirements, material characteristics, and geometric complexities without requiring complete remeshing, enhancing versatility while maintaining generation simplicity through automated parameter adjustment.
Solution Approach 2:
The patent creates a universal mesh generation framework that can handle both the runner system and the target object with a single integrated process. The system automatically determines appropriate mesh dimensions for each component based on their specific requirements, making the mesh generation process universally applicable to various RTM configurations while maintaining simplicity through automation.
Data Source
AI summary
The present disclosure provides a method of mesh generation for an RTM process, including operations of: obtaining a geometry of a target object; generating a solid mesh of the target object according to the geometry; obtaining material characteristics of the target object; assembling a runner mesh with the solid mesh, wherein the runner mesh has grid dimensions different from those of the solid mesh; determining process parameters of the RTM process; and generating a forecasted result of the RTM process according to the solid mesh, the runner mesh, the process parameters, and the material characteristics. Generating the solid mesh includes operations of: dividing the geometry into modules; generating a first and second modular meshes corresponding to a first and second modules, wherein the second modular mesh abuts the first modular mesh, and the second modular mesh has grid dimensions different from those of the first modular mesh.