RAM-C Aerodynamic Modeling Feedback Loop for eVTOL
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Solution Overview
Problem
Traditional aerodynamic modeling methods for complex aircraft, such as eVTOL and UAM systems, face challenges in accurately predicting forces and moments under rapidly changing flight conditions, leading to increased computational costs and resource demands, and often result in lower fidelity models that fail to capture nonlinear interactions.
Innovation Solution
The Rapid Aero Modeling (RAM) process, specifically RAM-C, uses computational fluid dynamics (CFD) and feedback loops to automatically generate aerodynamic models by determining required fidelity criteria, forming data test blocks, and iteratively refining models to meet user-defined prediction error requirements, allowing for efficient and accurate estimation of aerodynamic forces and moments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CFD programs are used to determine aerodynamic forces for each flight condition, then measurement precision is improved, but productivity deteriorates because the computation cannot keep up with rapidly changing flight conditions
Solution Approach 1:
The patent creates aerodynamic models in advance using CFD simulations or wind tunnel data before actual flight simulations. These pre-computed models capture the aerodynamic characteristics across a range of flight conditions, allowing rapid prediction during simulations without performing real-time CFD calculations. This preliminary action resolves the contradiction by preparing accurate aerodynamic data beforehand, enabling both high precision and fast computation speed during actual use.
2Productivity
If polynomial models are estimated from wind tunnel tests or CFD simulations to enable rapid prediction, then productivity is improved, but measurement precision deteriorates because the accuracy of predictions cannot be guaranteed
Solution Approach 1:
The patent implements a feedback mechanism where the aerodynamic models are validated against a separate validation dataset that was not used during model creation. This validation process checks prediction accuracy and provides feedback on model quality. If the model accuracy is insufficient, the system can identify which flight conditions or parameters need improved modeling. This feedback loop ensures that the rapid polynomial models maintain guaranteed accuracy levels while enabling fast simulations.
3Measurement precision
If traditional testing methods are used for complex aircraft with aerodynamic nonlinearities, then measurement precision may be improved, but device complexity increases and key factor interactions are missed
Solution Approach 1:
The patent segments the aerodynamic modeling process into distinct phases: data collection from CFD or wind tunnel tests, model creation using polynomial fitting, and validation against independent test data. This segmentation allows systematic handling of complex aircraft with multiple nonlinear factors by breaking down the overall modeling task into manageable steps. Each phase can be optimized independently, reducing overall complexity while maintaining high model fidelity for capturing key factor interactions.
Data Source
AI summary
A Rapid Aero Modeling program and process may be applied to computational experiments such as computational fluid dynamics (CFD) programs to obtain aerodynamic models which may be in the form of polynomial equations. The program and process may be utilized to estimate (develop) aerodynamic models appropriate for flight dynamics studies, simulations, and the like. Feedback loops are provided around computational codes to rapidly guide testing toward aerodynamic models that meet user-defined fidelity criteria. A user has the freedom to choose a specific level of fidelity in terms of prediction error, in advance of a CFD test (computation).