Geochronology
Geochronology
GChron
Articles | Volume 6, issue 2
Articles | Volume 6, issue 2
https://doi.org/10.5194/gchron-6-227-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gchron-6-227-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 6, issue 2
Research article
 | 
12 Jun 2024
Research article |  | 12 Jun 2024

Solving crustal heat transfer for thermochronology using physics-informed neural networks

Ruohong Jiao, Shengze Cai, and Jean Braun

Viewed

Total article views: 1,134 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
808 281 45 1,134 38 37
  • HTML: 808
  • PDF: 281
  • XML: 45
  • Total: 1,134
  • BibTeX: 38
  • EndNote: 37
Views and downloads (calculated since 19 Oct 2023)
Cumulative views and downloads (calculated since 19 Oct 2023)

Viewed (geographical distribution)

Total article views: 1,134 (including HTML, PDF, and XML) Thereof 1,058 with geography defined and 76 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 24 Mar 2025
Download
Short summary
We demonstrate a machine learning method to estimate the temperature changes in the Earth's crust over time. The method respects physical laws and conditions imposed by users. By using observed rock cooling ages as constraints, the method can be used to estimate the tectonic and landscape evolution of the Earth. We show the applications of the method using a synthetic rock uplift model in 1D and an evolution model of a real mountain range in 3D.
Read more
Share