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Non-Parametric Kinematic Optimization of Flapping Foil Propulsion Using a Discrete Adjoint Method
Zhaoran Yin1,2, Chao Zhou1, Xiaofei Wang3
1The Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
This study introduces a new non-parametric optimization method for flapping-foil propulsion, significantly boosting underwater vehicle efficiency. Optimized motions outperform traditional ones, enabling better thrust and power management.
Area of Science:
- Fluid dynamics
- Robotics
- Biomimetics
Background:
- Optimizing flapping-foil propulsion is complex due to fluid-structure interactions and limited design spaces with parameterized motions.
- Existing methods struggle with the nonlinear dynamics and temporal coupling inherent in flapping-foil systems.
Purpose of the Study:
- To develop a non-parametric optimization framework for flapping-foil kinematics.
- To enable direct optimization of time-resolved motions without predefined functional forms.
- To enhance underwater propulsion performance and design flexibility.
Main Methods:
- Developed a non-parametric kinematic optimization framework using the discrete adjoint method.
- Employed a Morison-based low-order hydrodynamic model calibrated with Computational Fluid Dynamics (CFD).
- Validated the model for efficient evaluation within its operational regime.
Main Results:
- Optimized non-sinusoidal motions significantly improved propulsion performance compared to sinusoidal motions.
- Achieved a 50.29% increase in mean thrust by optimizing heave and pitch timing and amplitudes.
- Demonstrated a 'generator-like' regime in power-minimization cases, indicating net energy transfer reversal.
Conclusions:
- Non-parametric optimization offers superior design flexibility for flapping-foil kinematics.
- The framework enables substantial improvements in underwater propulsion efficiency.
- Provides a practical approach for designing efficient biomimetic underwater vehicles.
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