BNCT digital twinborn model construction and dynamic optimization method, equipment and medium

Through the separate physical information neural network model (D-PINN) and data assimilation processing, the contradiction between multi-scale modeling and data assimilation in BNCT digital twin technology is solved, and a BNCT digital twin system with high precision and real-time response is realized.

CN120493769AActive Publication Date: 2025-08-15HUABORON NEUTRON TECH (HANGZHOU) CO LTD
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Patent Information

Application Number
CN202510983303.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-17
Publication Date
2025-08-15
Estimated Expiration
2045-07-17

AI Technical Summary

Technical Problem

There are multi-scale modeling contradictions and data assimilation contradictions in BNCT digital twin technology, resulting in increased computational complexity, difficulty in accuracy control and insufficient real-time.

Method used

The separated physical information neural network model (D-PINN) is used to generate equivalent measured data matching the historical measured data through data assimilation processing, and the first sub-model and the second sub-model are trained to characterize the accelerator physical process and the neutron beam flow analysis process respectively, and dynamic data transmission is carried out in combination with the OPC-UA protocol.

Benefits of technology

It improves the calculation accuracy and processing complexity of the BNCT digital twin system, ensures real-time response capabilities, and enhances the adaptability and prediction capabilities of the model.

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Abstract

The invention relates to the technical field of data processing, and discloses a BNCT digital twinborn model construction method, a BNCT digital twinborn model dynamic optimization method, BNCT digital twinborn model dynamic optimization equipment and a medium, and the construction method comprises the following steps: carrying out data assimilation processing on obtained multi-physical field simulation data to generate equivalent measured data matched with physical characteristics of historical measured data, generating a data assimilation training set based on the historical measured data and the equivalent measured data; wherein the multi-physical field simulation data represents simulation data of the accelerator and the beam shaping device in various physical processes; based on the data assimilation training set, a first sub-model used for representing the physical process of the accelerator and a second sub-model used for representing the neutron beam analysis process are obtained through training; and constructing the BNCT digital twinborn model according to the first sub-model and the second sub-model obtained by training. According to the technical scheme provided by the invention, the calculation precision and the processing complexity of the BNCT digital twin system can be improved, and real-time response is ensured.
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