Uranium migration prediction model based on particle swarm optimization and application of uranium migration prediction model in deep geological treatment

By using a particle swarm optimization-based uranium migration prediction model, the problems of analytical efficiency and chemical interpretability of traditional models in uranium migration prediction in granite fracture systems are solved. The model achieves a dynamic coupled description of pH-dependent adsorption/desorption and precipitation processes, thereby improving prediction accuracy and efficiency.

CN120913707APending Publication Date: 2025-11-07NANHUA UNIV
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Patent Information

Application Number
CN202510965558.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-14
Publication Date
2025-11-07

AI Technical Summary

Technical Problem

Traditional two-domain models present a contradiction in terms of analytical efficiency and chemical interpretability, making it difficult to simultaneously characterize pH-dependent adsorption/desorption processes and long-tailed decay of solutes. Furthermore, existing studies have high computational complexity and limited generalization ability in predicting the migration behavior of radionuclides in granite fracture systems.

Method used

A uranium migration prediction model based on particle swarm optimization was adopted. By constructing a dual-domain model, the granite fracture system was divided into a fracture domain and a matrix domain. A pH-coupled retention coefficient correction term and a pH-dependent exponential tail decay term were introduced. The parameter inversion was performed in combination with the particle swarm optimization algorithm to optimize the fitting accuracy.

Benefits of technology

It enables accurate prediction of uranium migration behavior under complex chemical conditions, improves parameter inversion efficiency, simplifies model structure, is suitable for rapid evaluation in multiple scenarios, and provides an efficient and interpretable analysis tool.

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Abstract

The invention relates to a uranium migration prediction model based on particle swarm optimization and application of the uranium migration prediction model in uranium migration prediction in granite fractures. According to the method, by introducing a retention coefficient and an exponential decay item coupled with pH sensitivity, solute retention behaviors of a fissure domain and a matrix domain are dynamically corrected, and accurate description of adsorption / desorption, precipitation and re-release processes of U (VI) under an acid-alkali condition is realized. Parameter inversion is performed on the model by combining a particle swarm optimization (PSO) algorithm, so that the calculation efficiency and the prediction precision are remarkably improved. Experimental verification shows that the model has high stability and reliability (SSE is smaller than or equal to 0.026, RMSE is smaller than or equal to 0.045, and Error is smaller than or equal to 2.82%) under various pH, pressure and temperature conditions, and an efficient and interpretable analysis tool is provided for uranium migration risk assessment in the deep geological disposal environment.
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