一种天然河道一维非恒定流数学模型糙率参数的自动率定方法及系统
By using the Levenberg–Marquardt algorithm and Jacobian matrix optimization, the roughness parameters of one-dimensional unsteady flow in natural channels are automatically calibrated, solving the problems of time-consuming and large error in existing roughness calibration techniques, and achieving efficient and accurate roughness parameter updates.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUHAN UNIV
- Filing Date
- 2023-06-27
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient for automatically calibrating the roughness parameters of one-dimensional unsteady flow in natural river channels, leading to significant errors when there are large variations in water level or flow rate at the river cross-section. Furthermore, manual calibration methods are time-consuming and highly random.
The Levenberg–Marquardt optimization algorithm is adopted to establish a roughness relation database based on water level or flow rate classification. The roughness parameters are automatically calibrated through iterative optimization, and the partial derivative terms are calculated by combining the Jacobian matrix and the difference method to realize the non-steady flow update of roughness.
It improves the accuracy and efficiency of roughness calibration, reduces the time and cost of manual debugging, can reasonably reflect the characteristics of river resistance changing with water level or flow, and reduces calculation errors.
Smart Images
Figure CN116776775B_ABST