Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 7
Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4713-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-4713-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 7
Model evaluation paper
 | 
29 Jul 2021
Model evaluation paper |  | 29 Jul 2021

DecTree v1.0 – chemistry speedup in reactive transport simulations: purely data-driven and physics-based surrogates

Marco De Lucia and Michael Kühn

Viewed

Total article views: 2,327 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,458 795 74 2,327 61 51
  • HTML: 1,458
  • PDF: 795
  • XML: 74
  • Total: 2,327
  • BibTeX: 61
  • EndNote: 51
Views and downloads (calculated since 02 Mar 2021)
Cumulative views and downloads (calculated since 02 Mar 2021)

Viewed (geographical distribution)

Total article views: 2,327 (including HTML, PDF, and XML) Thereof 2,145 with geography defined and 182 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Jan 2025
Download
Short summary
DecTree evaluates a hierarchical coupling method for reactive transport simulations in which pre-trained surrogate models are used to speed up the geochemical subprocess, and equation-based full-physics simulations are called only if the surrogate predictions are implausible. Furthermore, we devise and evaluate a decision tree surrogate approach designed to inject domain knowledge of the surrogate by defining engineered features based on law of mass action or stoichiometric reaction equations.
Read more