An adaptive optimization method for flip bucket geometry in high-dam flood discharge and its application

Key Points

• The research aims to optimize flip bucket geometry for better flood discharge in high-dam systems by integrating adaptive methods from biology.
• Employs artificial neural networks and NSGA-II for parameter optimization of flip bucket designs.
• Focuses on hydraulic characteristics and geological conditions to guide the design process.
• Utilizes small-sample optimization methods for efficient design adaptation.
• Achieves an improved design with high energy dissipation efficiency and reduced scour impact.
• Proposes novel flip bucket shapes that enhance discharge and minimize engineering costs.
• Provides a theoretical framework for adaptive design that can apply to various energy dissipation structures.