Nuclear Reactor State Estimation via Stability Parameter
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Solution Overview
Problem
Complex industrial systems, such as nuclear reactors, are difficult to predict and control due to their sensitivity to initial conditions and the interdependence of many physical variables, leading to instability and challenges in maneuverability, especially with the integration of renewable energy sources.
Innovation Solution
A process for estimating the future state of a complex industrial system, specifically a nuclear reactor, involves obtaining sequences of measurements for system variables, normalizing them, determining a stability parameter, and using an estimator to improve predictions based on a re-ordering parameter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional prediction methods are used for complex industrial systems, then the system complexity is maintained, but the prediction precision and control accuracy deteriorate due to sensitivity to initial conditions
Solution Approach 1:
The patent segments the complex system into multiple subsystems, each governed by its own differential equations. The overall system is divided into manageable components that can be analyzed and predicted separately, then integrated through the neural network framework. This segmentation allows prediction of individual subsystem behaviors while maintaining overall system accuracy.
Solution Approach 2:
The patent introduces a neural network as an intermediary layer between the physical system and the prediction output. This neural network mediator learns the complex nonlinear relationships and sensitivity to initial conditions, transforming difficult prediction problems into manageable pattern recognition tasks that improve prediction precision without requiring complete understanding of all system complexities.
2Adaptability or versatility
If the system operates with high maneuverability to integrate renewable energy, then the adaptability improves, but the stability deteriorates due to frequent adjustments and instability
Solution Approach 1:
The patent uses the prediction method to perform preliminary actions by forecasting future system states before they occur. By predicting instability conditions in advance, the system can take preventive control actions to maintain stability during frequent maneuvers for renewable energy integration, allowing adaptability without sacrificing stability.
Solution Approach 2:
The patent implements a feedback mechanism where prediction results are continuously fed back into the control system. This feedback loop allows the system to adjust operations based on predicted future states, maintaining stability during frequent maneuvers by anticipating and compensating for potential instability before it occurs.
Data Source
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AI summary
Method for estimating a quantity of a system (1) comprising the following steps: - for each variable of a plurality of variables, obtaining a sequence of successive measurements, - determining a sequence of successive values of a stability parameter, the parameter being a weighted sum of rates of change of the variables, - identifying a time interval in which the stability parameter is less than or equal to a predetermined threshold for a duration greater than or equal to a predetermined duration, - estimating a sequence of successive estimates of a particular variable, a temporal start of the sequence being included in the time interval, - comparing the sequence of estimates and the sequence of measurements to determine a calibration parameter, and - estimating the physical quantity of the system (1) using the calibration parameter.