BriefGPT.xyz
Aug, 2024
利用机器学习加速行星内部动力学稳态的发现
Accelerating the discovery of steady-states of planetary interior dynamics with machine learning
HTML
PDF
Siddhant Agarwal, Nicola Tosi, Christian Hüttig, David S. Greenberg, Ali Can Bekar
TL;DR
本研究解决了模拟地幔对流中达到计算昂贵的稳态所需的时间过长的问题。通过利用机器学习,我们训练神经网络预测稳态温度分布,从而优化数值时间步进方法,显著减少达到稳态所需的时间步数,潜在地推动地幔对流研究的加速发展。
Abstract
Simulating
Mantle Convection
often requires reaching a computationally expensive
Steady-State
, crucial for deriving scaling laws for thermal and dynamical flow properties and benchmarking numerical solutions. The
→