Injection Mold Cavity Simulation Using Cell Coordinate Systems
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Solution Overview
Problem
Current injection molding simulation methods are time-consuming and computationally intensive, requiring high resources and failing to efficiently consider product properties beyond fill patterns and manufacturability.
Innovation Solution
A computer-implemented method that discretizes the mold cavity into cells, determines cell coordinate systems, and simulates the flow direction, fiber orientation, and pressure distribution, using a database for fiber orientation data and similarity considerations to reduce computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex numerical solving methods are used to simulate the filling process, then the accuracy of simulation results is improved, but the computation time and resource requirements increase significantly
Solution Approach 1:
The mold cavity is divided into multiple cells or control volumes, and the simulation domain is segmented into different regions based on flow characteristics. This allows complex 3D simulations to be broken down into simpler sub-problems that can be solved more efficiently while maintaining overall accuracy.
Solution Approach 2:
The method changes the mathematical parameters and governing equations used in the simulation. Instead of solving full Navier-Stokes equations, it uses simplified flow models with modified parameters that capture essential physics while reducing computational complexity. The simulation uses a reduced set of process variables and simplified boundary conditions.
2Measurement precision
If detailed 3D modeling and mesh refinement are performed to improve simulation accuracy, then the precision of flow and fiber orientation prediction is improved, but the device complexity and preparation effort increase
Solution Approach 1:
The method uses 2D cross-sectional models and simplified geometric representations instead of detailed 3D models. It creates simplified copies of the essential flow features and geometry that capture the dominant physics without requiring complex mesh generation and detailed surface modeling.
Solution Approach 2:
The method extracts only the essential geometric features and flow characteristics needed for accurate simulation, removing unnecessary details from the model. It takes out the critical parameters such as gate locations, cavity geometry, and flow paths while eliminating complex surface definitions and fine mesh requirements.
3Measurement precision
If comprehensive simulation of fiber orientation and flow dynamics is performed, then the accuracy of product property prediction is improved, but the computation capacity requirements increase
Solution Approach 1:
The method changes the computational parameters by using simplified constitutive equations for fiber suspension and reduced-order models for flow dynamics. It transforms the complex coupled PDE system into a set of algebraic equations or simplified differential equations that require less computational power while maintaining prediction accuracy for fiber orientation and flow patterns.
Data Source
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AI summary
A computer-implemented method, a computer system (132) configured to perform the computer implemented method, a computer program comprising instructions which, when the program is executed by a computer or computer system (132), cause the computer or computer system (132) to carry out the method and a database (128) for use in the method are disclosed. The computer- implemented method for simulating a filling process of a mold cavity (112) in an injection molding process using a plastic material, the method comprises: i) discretizing at least a part of the mold cavity (112) into a plurality of cells (116); ii) defining a cavity injection point (114); iii) determining a surface normal direction (124) perpendicular to the nearest cavity sur-face (125) for each cell (116); iv) determining a cell coordinate system for each cell (116), defined by15 - a first principal direction (118) parallel to a flow direction (120), - a third principal direction (122) parallel to the normal direction (124), and - a second principal direction (126) perpendicular to the first (118) and third (122) principal directions; and v) determining the flow direction (120) of a mold flow for each cell (116).