一种泄洪挑流鼻坎体型智能优化方法
By optimizing the shape of the nasal sill using a BP neural network and the NSGA-II multi-objective algorithm, the problem of repeated trial and error in the design method of the existing technology is solved, and the design of the nasal sill is fast and accurate, reducing the consumption of manpower and material resources and engineering costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SICHUAN UNIV
- Filing Date
- 2026-01-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for designing water jets require repeated trial and error and revision, consuming a lot of manpower and resources. Furthermore, it is difficult to precisely control the shape and landing point of the water jet, resulting in high construction difficulty and a large workload.
An intelligent optimization method combining BP neural network and NSGA-II multi-objective algorithm is adopted. Through orthogonal experimentation, numerical simulation calculation and physical model test, the body shape parameters of the nasal sill are optimized, a parameter database is constructed, and the ideal body shape parameters that meet the engineering objectives are obtained by inversion.
It enables rapid and accurate optimization of the jet nose design, reduces the consumption of physical model experiments, improves design accuracy, controls the shape and landing point of the jet tongue, and reduces the difficulty and cost of engineering construction.
Smart Images
Figure CN122046469B_ABST