(aside image)

News

Open positions (both now filled)

In conjunction with the Metsähovi Observatory within the Aalto School of Engineering the group have a six month Master's Project 1, funded, and also Master's Project 2, both to commence immediately. Read more for details.

Hidden solar magnetic cycle explained with modifications in turbulent induction and pumping

The Sun, aside from its eleven year sunspot cycle is additionally subject to long term variation in its activity. We make use of a solar-like convective dynamo simulation of Käpylä et al. 2016, exhibiting equatorward propagation of the magnetic field, multiple frequencies, and irregular variability, including a missed cycle and complex parity transitions between dipolar and quadrupolar modes, to study the physical causes of such events. We use the test field analysis tool to measure and quantify the effects of turbulence in the generation and evolution of the large-scale magnetic field. The test-field analysis provides an explanation of the missing surface magnetic cycle in terms of the reduction of part of the alpha effect, the one of the key ingredients for dynamo action. Furthermore, we found an enhancement of downward turbulent pumping during the event to confine some of the magnetic field at the bottom of the convection zone, where local maximum of magnetic energy is observed during the event. At the same time, however, a quenching of the turbulent magnetic diffusivities is observed. For more detailed analysis, we will perform dedicated mean-field modelling with the measured turbulent transport coefficients in the future.

Convection zone surface Bφ (top), base transport coefficient αφφ (middle) and radial turbulent pumping (bottom) at 40oN, where a magnetic field disturbance occurs.

The Sun, aside from its eleven year sunspot cycle is additionally subject to long term variation in its activity. We make use of a solar-like convective dynamo simulation of Käpylä et al. 2016, exhibiting equatorward propagation of the magnetic field, multiple frequencies, and irregular variability, including a missed cycle and complex parity transitions between dipolar and quadrupolar modes, to study the physical causes of such events. We use the test field analysis tool to measure and quantify the effects of turbulence in the generation and evolution of the large-scale magnetic field. The test-field analysis provides an explanation of the missing surface magnetic cycle in terms of the reduction of part of the alpha effect, the one of the key ingredients for dynamo action. Furthermore, we found an enhancement of downward turbulent pumping during the event to confine some of the magnetic field at the bottom of the convection zone, where local maximum of magnetic energy is observed during the event. At the same time, however, a quenching of the turbulent magnetic diffusivities is observed. For more detailed analysis, we will perform dedicated mean-field modelling with the measured turbulent transport coefficients in the future."
The method results are published in Gent, Käpylä & Warnecke (2017)." [more]


Development of HPC and data analysis tools


  We have developed an effective method for accelerating fluid dynamics
  calculations with high-order precision on graphics processing units (GPUs).
  This is done by efficient use of GPU memory with cache blocking and by 
  dividing computation algorithms into memory efficient chunks.
  Our Nvidia CUDA based, proof of concept code Astaroth is able to achieve
  3.6 times speedup in comparison to the reference code, which in practice
  allows for a week-long turbulence simulation to be performed within a
  couple of days.
  The method is published in Pekkilä Väisälä et al. (2017).

The power of graphics processing units harnessed for high-accuracy turbulence modelling

We have developed an effective method for accelerating fluid dynamics calculations with high-order precision on graphics processing units (GPUs). This is done by efficient use of GPU memory with cache blocking and by dividing computation algorithms into memory efficient chunks. Our Nvidia CUDA based, proof of concept code Astaroth is able to achieve 3.6 times speedup in comparison to the reference code, which in practice allows for a week-long turbulence simulation to be performed within a couple of days. The method is published in Pekkilä Väisälä et al. (2017)."
The method is published in Pekkilä Väisälä et al. (2017)." [more]


Jul 2017

Meeting

Pencil Code Meeting 2017

Astroinformatics

Members

Alumni

Projects

Publications

MPS Team