Transitions in Turbulent Rotating Thermal Convection

Principal Investigator:
Olga Shishkina

German Aerospace Center (DLR)

Local Project ID:

HPC Platform used:
SuperMUC of LRZ

Date published:

Turbulent thermal convection is of fundamental interest in many fields of physics and engineering. Examples to mention here are the convective flows in the Earth’s atmosphere and oceans, in its core and mantle, but also in the outer layer of stars, in chemical engineering or in aircraft cabins. Frequently, these systems are also strongly influenced by rotation.

For the sake of simplicity, in experiments and numerical simulations very basic geometries are preferable and in rotating convection a cylindrical geometry is the one to use. This makes it easier to gain insight into the physical problem itself. Nonetheless, the flow structures are highly complex and vary a lot in scale. Rotation can dramatically alter the flow. Different regimes are known to exist, where amongst other things the typical flow structures and the way heat is transported change. One important question that Olga Shishkina and Susanne Horn address is how to identify the transitions between these different regimes.

To accurately predict the flow in rotating thermal convection by means of numerical simulations, the underlying governing equations have to be solved on meshes with a very high resolution. Furthermore, a lot of different scenarios with varying control parameters have to be investigated. Typical simulations have to run for several weeks to months and occupy several terabyte of disk space. Therefore, these simulations are only possible on large-scale supercomputers such as SuperMUC of the LRZ in Garching near Munich.

In opposite to nowadays’ experiments, here the fully three-dimensional velocity and temperature fields are known. With this knowledge, a new method based on velocity potentials, i.e. on the toroidal and the poloidal part of the kinetic energy, was developed. This also allowed to connect empirically found relations with the actual underlying physics, showing that the interplay of experiments and high-resolved numerical simulations is essential for turbulence research.