Scientific simulations are often used to gain insight into foundational questions. However, many potentially useful simulation results are difficult to visualize without powerful computers. In this research, we seek to build a surrogate model, using a generative adversarial network, to allow for the visualization of the Earth's Mantle Convection data set on readily accessible hardware. We present our preliminary method and results, and all code is made publicly available. The preliminary results show that a surrogate model of the Earth's Mantle Convection data set can generate useful results. A comparison to the "ground-truth" is provided.
@article{arxiv.2110.13315,
title = {EarthGAN: Can we visualize the Earth's mantle convection using a surrogate model?},
author = {Tim von Hahn and Chris K. Mechefske},
journal= {arXiv preprint arXiv:2110.13315},
year = {2021}
}
Comments
Accepted at IEEE VIS 2021 as part of the SciVis contest. For associated code, see https://github.com/tvhahn/EarthGAN