Data assimilation is one of the crucial technical pathways for achieving cyber-physical integration in the digital twin systems of nuclear power plants, and it is of great significance for improving simulation accuracy. However, performing data assimilation on the thermal-hydraulic models of Once-Through Steam Generators (OTSGs) faces multiple challenges: sparse observation information due to limited sensor configurations; the difficulty in uniquely determining states caused by the decoupling of the working fluid's temperature and vapor quality in the two-phase coexistence region; the high sensitivity of dual-flow boundaries to errors in empirical correlations; and the physical consistency imbalance and state rebound phenomena induced by the direct assimilation of key parameters such as pressure. Consequently, traditional data assimilation methods are difficult to apply directly.To address these issues, this paper investigates the data assimilation problem concerning the two-phase flow and heat transfer processes of OTSGs in nuclear power plant simulation systems. An embedded three-dimensional variational (3D-Var) data assimilation method for OTSGs is proposed, and the feasibility of this model is verified through the synergistic design of the solution process and the assimilation strategy. Furthermore, the proposed method is validated under various operating conditions. The results demonstrate that this method can effectively integrate limited sensory information, significantly enhancing the tracking accuracy and robustness of the simulation model.

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