Two-Stage Casting Modeling for Turbine Hardware Validation
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Solution Overview
Problem
The traditional metal casting process for single crystal turbine hardware is inefficient, relying on preexisting knowledge and requiring extensive time and budget for design and validation, with current high-fidelity simulations being time-consuming and not adequately addressing issues of metal flow, part withdrawal rates, and temperature profiles.
Innovation Solution
A two-stage casting modeling process involving a low-fidelity simulation followed by a high-fidelity simulation, with the results of the low-fidelity stage being used to inform and optimize the high-fidelity simulation, allowing for parallel casting trials and iterative adjustments based on evaluation results, thereby reducing the time and cost of the design and validation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-fidelity FEA computer simulation is performed to validate the casting process, then manufacturing precision and reliability are improved, but time consumption and cost increase significantly
Solution Approach 1:
The validation process is segmented into multiple simulation fidelities (low-fidelity and high-fidelity models). The low-fidelity model performs rapid initial validation, while the high-fidelity model provides detailed verification only for critical parameters, thus reducing overall validation time while maintaining precision where needed.
Solution Approach 2:
Low-fidelity simulations are performed preliminarily to identify potential issues and optimize process parameters before conducting time-consuming high-fidelity simulations. This preliminary action filters out obvious problems early, preventing wasted time on flawed designs in the high-fidelity stage.
2Manufacturing precision
If comprehensive casting process design is performed including all features (gating, venting, seed configuration), then manufacturing precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The complex casting process design is segmented into modular components (gating system, venting system, seed configuration) that can be independently optimized using low-fidelity models and then integrated. This modular approach manages complexity while ensuring comprehensive quality.
Solution Approach 2:
The invention uses parameter studies and sensitivity analysis to identify which process parameters have the most significant impact on casting quality. By focusing optimization efforts on critical parameters and using parameter changes systematically, the design process becomes more manageable while maintaining high precision.
3Ease of manufacture
If traditional preexisting knowledge base is used for process design, then ease of manufacture is improved, but adaptability to new designs and productivity are reduced
Solution Approach 1:
The invention creates simplified digital copies (low-fidelity simulation models) of the casting process that capture essential physics without the complexity of full high-fidelity models. These simplified models enable rapid iteration and optimization, significantly improving productivity while maintaining ease of use through familiar simulation interfaces.
Data Source
AI summary
A process includes: a first casting modelling stage producing resulting casting parameters; a second casting modelling stage performed using the resulting casting parameters of the first casting modelling stage and of higher fidelity than the first casting modelling stage; in parallel with the second casting modelling stage, a casting trial using the resulting casting parameters of the first casting modelling stage; and evaluating the casting trial.