Predicted Reactor Simulation Using Response Surface Method
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Solution Overview
Problem
Optimizing the operation of a nuclear reactor core is challenging due to the vast number of possible fuel bundle configurations and control blade positions, which requires extensive computational resources and time to find an arrangement that satisfies design constraints and maximizes core cycle energy, often relying on trial-and-error methods that may not identify the actual optimum configuration.
Innovation Solution
A response surface method is used to create a cyber-workspace that defines relationships between design inputs and operational outputs, allowing for real-time predicted reactor simulations by deriving operational outputs using polynomial functions, thereby reducing the computational burden and enabling faster optimization of control variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional trial-and-error methods are used to optimize fuel bundle configurations and control blade positions, then design constraints can be satisfied, but the computational time and resources required become excessively large
Solution Approach 1:
The patent pre-calculates and stores performance data for various fuel bundle configurations and control blade positions in lookup tables before optimization is needed. This preliminary action allows the optimization process to quickly retrieve pre-computed results instead of performing time-consuming simulations during the actual optimization, thereby reducing computational time while still satisfying design constraints
Solution Approach 2:
The patent creates simplified mathematical models and lookup tables that replicate the behavior of complex reactor physics simulations. These copies allow for rapid evaluation of different configurations without running full-scale simulations, significantly reducing computational time while maintaining sufficient accuracy for optimization purposes
2Power
If the number of fuel bundle configurations is increased to find the optimal loading arrangement, then core cycle energy can be maximized, but the complexity of the optimization problem increases dramatically
Solution Approach 1:
The patent divides the optimization problem into separate segments: fuel bundle configuration optimization and control blade position optimization. By segmenting the problem, the patent can apply different optimization strategies to each part and reduce the overall complexity while still achieving maximum core cycle energy through coordinated optimization of all variables
3Productivity
If comprehensive analysis of all operational controls is performed to optimize reactor performance, then efficiency can be improved, but the computational burden becomes formidable
Solution Approach 1:
The patent performs partial analysis by focusing on the most influential operational controls (fuel bundle configurations and control blade positions) while using lookup tables to approximate the effects of other controls. This partial action approach achieves sufficient reactor efficiency optimization without requiring computationally exhaustive analysis of all possible operational parameters
Data Source
AI summary
In the method for reactor simulation, a user modifies one or more design inputs used in creating a response surface. The response surface defines relationships between the design inputs and operational outputs of at least one or more aspects of a core design. A reactor simulation is then generated based on the response surface for the core design and the modified design input.