Maeyama Shinya, Honda Mitsuru, Narita Emi, Toda Shinichiro
National Institute for Fusion Science, Toki, Gifu, 509-5292, Japan.
Graduate School of Engineering, Kyoto University, Nishikyo, Kyoto, 615-8530, Japan.
Sci Rep. 2024 Dec 12;14(1):28242. doi: 10.1038/s41598-024-78394-3.
Maintaining the high-temperature and pressure conditions required for sustained nuclear fusion is challenging due to the turbulent transport that naturally occurs in the plasma. Developing reliable models for turbulent transport is essential for progress in fusion research and development. This study proposes multi-fidelity modeling for the improved accuracy of regression models for turbulent transport in magnetic fusion plasma. Multi-fidelity modeling combines low-fidelity data, which have low accuracy but many data points, with high-fidelity data, which are highly accurate but have few data points or small parameter ranges, to enhance the overall predictive accuracy of a model. We used a multi-fidelity information fusion technique, Nonlinear AutoRegressive Gaussian Process regression (NARGP), to solve the regression problems associated with turbulent transport in plasma. We applied NARGP to (i) merge the low-resolution and high-resolution simulation results, (ii) apply regression of turbulence diffusivity to the experimental dataset using linear analyses, and (iii) adapt the quasi-linear transport model to nonlinear simulation results of a particular discharge. We demonstrated that NARGP improved the prediction accuracy of the plasma turbulent transport model. NARGP offers a robust and versatile method for integrating multi-fidelity data, and its broad applicability may contribute to optimizing fusion reactor design and operation.
由于等离子体中自然发生的湍流输运，维持持续核聚变所需的高温和高压条件具有挑战性。开发可靠的湍流输运模型对于核聚变研究与开发的进展至关重要。本研究提出了多保真度建模方法，以提高磁聚变等离子体中湍流输运回归模型的准确性。多保真度建模将精度低但数据点多的低保真度数据与精度高但数据点少或参数范围小的高保真度数据相结合，以提高模型的整体预测精度。我们使用了一种多保真度信息融合技术，即非线性自回归高斯过程回归（NARGP），来解决与等离子体中湍流输运相关的回归问题。我们将NARGP应用于：（i）合并低分辨率和高分辨率模拟结果；（ii）使用线性分析将湍流扩散率回归应用于实验数据集；（iii）使准线性输运模型适应特定放电的非线性模拟结果。我们证明了NARGP提高了等离子体湍流输运模型的预测精度。NARGP为整合多保真度数据提供了一种强大且通用的方法，其广泛的适用性可能有助于优化聚变反应堆的设计和运行。
