Digital Twin Fire Simulation for Nuclear Electrical Equipment
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Solution Overview
Problem
Existing fire simulation technologies for nuclear power plants lack the capability to digitally model fire outbreak and damage spread within electrical equipment installations, failing to provide effective fire detection and response strategies.
Innovation Solution
A digital twin platform is implemented to model electrical equipment and related materials, applying fire reactivity information to simulate fire outbreaks, spread, and response scenarios, recommending disaster prevention equipment and evacuation routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a digital twin platform is implemented to digitally model target objects and simulate fire scenarios, then fire detection precision and response capability are improved, but device complexity increases
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical nuclear power plant environment, including target objects like electrical equipment and subsidiary materials. This digital replica allows fire scenario simulation without physical experiments, improving detection precision through virtual sensing while avoiding the complexity of multiple physical test setups.
Solution Approach 2:
The system performs preliminary fire simulations in the digital twin environment to predict fire outbreaks and damage spread before actual incidents occur. By pre-configuring fire reactivity information and conducting virtual experiments, the system prepares response strategies in advance, improving real-time detection capability without requiring complex real-time physical simulation infrastructure.
2Manufacturing precision
If fire reactivity information is applied to build a digital twin with detailed attribute information, then simulation accuracy is improved, but information processing requirements increase
Solution Approach 1:
The patent applies fire reactivity information specifically to target objects and their immediate surroundings in the digital twin, rather than uniformly across the entire plant. This localized approach focuses computational resources on critical areas with electrical equipment and flammable materials, improving simulation accuracy where needed while reducing overall information processing requirements.
Solution Approach 2:
The digital twin model divides the nuclear power plant into discrete target objects (electrical equipment, subsidiary materials) with individual fire reactivity attributes. This segmentation allows selective application of fire simulation parameters to specific objects rather than the entire system, enhancing simulation precision for fire-prone areas while managing data volume through modular object-based modeling.
3Reliability
If comprehensive fire simulation scenarios are provided including fire outbreak prediction and damage spread, then fire response capability is improved, but calculation time increases
Solution Approach 1:
The system pre-calculates and stores fire reactivity information, material properties, and simulation parameters in the digital twin before actual fire incidents occur. By preparing simulation models and attribute data in advance, the system can quickly execute fire outbreak predictions and damage spread simulations when needed, improving response capability while reducing real-time calculation time through pre-configured virtual environments.
Data Source
AI summary
Disclosed is a digital twin platform provision system for detecting and responding to a fire in an installation region of electrical equipment in a nuclear power plant, which includes: a digital twin build unit for building an initial digital twin by digitally modeling target objects including equipment and subsidiary materials related to fire outbreak and damage spread; an attribute information application unit for applying fire reactivity information received from an outside and serves as attribute information about fire outbreak and spread factors to the initial digital twin, thereby building a digital twin; and a simulation information provision unit for generating simulation information, which is information about fire outbreak prediction, fire spread simulation upon fire break, and fire response and evacuation scenarios upon the fire break, by using the digital twin according to a user input and outputting the simulation information to a user terminal.