English(EN) Extracting Single-Mode Rayleigh--Taylor Instability dynamics from data via SINDy

新的SINDy框架从数据中提取瑞利-泰勒不稳定性动力学

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-06 05:00

研究人员开发了一个新的数据驱动框架，使用非线性动力学稀疏识别（SINDy）来提取描述瑞利-泰勒不稳定性（RTI）的方程。该方法能够准确捕捉气泡和尖峰速度的超调行为和再加速阶段，其性能优于传统的势流和浮力-阻力模型。该框架在各种阿特伍德数和初始幅度下都有效，为理解界面不稳定性提供了一种补充方法。 AI

影响这项研究提供了一种新颖的数据驱动方法来模拟复杂的物理现象，可能影响科学模拟和预测的开发方式。

排序理由学术论文，详细介绍了一种从数据中提取科学动力学的新方法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Chuanxing Wang, Hui Luo, Guohuai Zhu, Hongbo Cai, Shaoping Zhu, Mingxing Luo · 2026-11-06 05:00

通过SINDy从数据中提取单模瑞利-泰勒不稳定性动力学

arXiv:2611.07666v1 Announce Type: cross Abstract: Rayleigh-Taylor instability (RTI) is of fundamental importance in fields such as inertial confinement fusion and supernova explosions, and its evolution is commonly described by potential--flow theory and buoyancy--drag models. Ho…

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报道来源 [1]

通过SINDy从数据中提取单模瑞利-泰勒不稳定性动力学

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