Dam Flood Discharge Digital Twin for Gas Supersaturation Warning
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Solution Overview
Problem
Current technologies struggle to accurately monitor and mitigate the impact of dissolved gas supersaturation in flood discharge from high dams, which affects aquatic ecosystems and downstream structures due to dynamic and uncertain parameters, lacking real-time monitoring and effective early warning systems.
Innovation Solution
An early-warning and regulating control system utilizing a flood discharge digital twin, data interaction prediction module, and underwater gliding detection apparatus to predict and manage gas supersaturation, guiding aquatic life to optimal tolerance zones through intelligent prediction and biological signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time monitoring of gas saturation degree is implemented in flood discharge process, then prediction accuracy of dissolved gas supersaturation is improved, but system complexity and measurement difficulty increase due to dynamic and uncertain parameters
Solution Approach 1:
The system divides the flood discharge process into multiple monitoring sections along the downstream path, with sensors placed at different locations to measure gas saturation degree at various stages. This segmentation allows tracking the evolution of gas supersaturation from the dam outlet through the downstream basin, improving prediction accuracy while managing system complexity through modular deployment
Solution Approach 2:
The system performs preliminary monitoring and prediction of gas saturation levels before critical supersaturation conditions develop. By continuously measuring dissolved gas concentrations and flow parameters in advance, the system can predict upcoming supersaturation events and trigger early warnings before harmful effects occur to aquatic ecosystems
Solution Approach 3:
The system implements feedback control by using real-time measurements of gas saturation degree, water flow rate, and other parameters to continuously update predictions and adjust monitoring strategies. The measured data feeds back into the prediction model to refine accuracy and trigger appropriate warnings or mitigation actions when thresholds are approached
2Measurement precision
If comprehensive multi-scale data collection is performed including topographical, flow, and chemical parameters, then prediction accuracy is improved, but data processing complexity and time consumption increase
Solution Approach 1:
Topographical data, baseline chemical parameters, and flow characteristics are pre-measured and stored in the system before flood events occur. When flooding occurs, the system only needs to collect real-time variations from these baselines, significantly reducing data processing time while maintaining comprehensive prediction accuracy
Solution Approach 2:
The data collection system is divided into multiple independent modules measuring different parameters (topography, flow rate, dissolved gas concentration, temperature) that can operate and process data independently. This modular approach allows parallel processing of different data streams, reducing overall processing time while maintaining comprehensive data quality
3Measurement precision
If digital twin technology is used to construct flood discharge digital twin, then real-time prediction capability is improved, but device complexity and computational requirements increase
Solution Approach 1:
The system creates a simplified digital twin (virtual model) of the flood discharge process that replicates the essential physics and chemistry of gas dissolution and transport. This virtual model receives real-time data from physical sensors and produces predictions without requiring complex computational resources, achieving real-time prediction capability while managing device complexity through model simplification
Data Source
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AI summary
Disclosed in this specification is an early-warning and regulating control system for dissolved gas supersaturation in flood discharge of a hydraulic dam, which can provide an early warning accurately in time about a gas supersaturation status of a downstream water body in a flood discharge process. The system includes: a flood discharge body digital module, configured to acquire multi-scale data of a flood discharge process, including a flood discharge basin data unit, a flood discharge influence factor unit, and a basin physical and chemical monitoring unit; a flood discharge digital twin module, configured to construct a flood discharge digital twin according to the multi-scale data, and including a dam digital twin unit and a downstream basin digital twin unit; a data interaction prediction module, configured to predict a dissolved gas supersaturation status, and including a data interaction unit, a machine learning unit, and an intelligent prediction unit; and an early-warning protection module, configured to generate early-warning information according to the predicted dissolved gas supersaturation status and perform protective regulating on aquatic life in the downstream basin.