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English(EN) Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor

AI框架增强SMR模拟以支持数字孪生

研究人员开发了一种结合降阶模型(ROM)和神经算子来模拟计算流体动力学(CFD)的新框架。该方法旨在实现小型模块化反应堆(SMR)数字孪生技术所需的实时热工水力模拟。研究比较了不同的神经算子架构,包括DeepONet和傅里叶神经算子(FNO),并引入了一种多尺度技术来改进复杂流动动力学的预测。 AI

影响 这项研究通过实现更快、更准确的模拟,有望加速SMR数字孪生的开发和部署。

排序理由 该集群包含一篇学术论文,详细介绍了一种用于特定工程应用的新型基于AI的建模技术。

在 arXiv cs.LG 阅读 →

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AI框架增强SMR模拟以支持数字孪生

报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Minseo Lee, Seongmin Oh, Chaehyeon Song, Bumjin Cho, Shilaj Baral, Sangam Khanal, Minseop Song, Joongoo Jeon ·

    Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor

    arXiv:2605.30277v1 Announce Type: new Abstract: Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular reactors (SMRs). Computational fluid dynamics (CFD) provides high-fidelity flow ana…

  2. arXiv cs.LG TIER_1 English(EN) · Joongoo Jeon ·

    Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor

    Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular reactors (SMRs). Computational fluid dynamics (CFD) provides high-fidelity flow analysis, but its computational cost prevents direc…