A framework to study the thermo-chemical evolution of rocky and icy bodies (planets, moons, and planetoids) on a global scale in the solar system and beyond.
GAIA is a comprehensive framework designed to study the thermo-chemical evolution of rocky and icy bodies (planets, moons, and planetoids) on a global scale within the solar system and beyond. The core part consists of a fluid-dynamics solver for creeping flows under highly spatially varying viscosities with an additional energy solver for natural convection.
Natural convection is a type of heat transfer that occurs due to the movement of a fluid (such as air, water, or in much larger time-scales even rocks) caused by differences in density. When a fluid is heated, it becomes less dense and rises, while cooler, denser fluid sinks. This creates a natural circulation pattern that transfers heat from one area to another without the need for external forces like pumps or fans.
In the context of planetary bodies, natural convection plays a crucial role in the thermal and thermo-chemical evolution of rocky and icy bodies. It drives processes such as mantle convection, which can influence plate tectonics, vulcanism, magnetic field development, and the differentiation of materials within the planet's interior.
A JS compiled (older) version can be found here . Just click Run in the Run tab and switch to Temperature or Velocity tab.
Golden Spike Award 2012, Project: A particle-in-cell Method to model the Influence of Partial Melt on Mantle Convection
Golden Spike Award 2015, Project: Large Scale Numerical Simulations of Planetary Interiors
One of six HPC codes selected to run on HLRS supercomputer Hornet, a Cray XC40 system
Selected cover image for the cover of Journal of Geophysical Research: Planets, Wiley. Publication: Onset of solid-state mantle convection and mixing during magma ocean solidification
Selected cover image for the cover of Geophysical Research Letters, Wiley. Publication: The Thermal State and Interior Structure of Mars
By comparing the numerical simulations with the experiment data, we are able to verify the validity of our computer models and expand the parameter space to ranges not applicable for an experiment.