Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next...

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Global Mean Field Dynamo simulations with SPMHD Federico Stasyszyn USM - Munich Colaborators: Detlef Elstner (AIP), Alexander Beck (USM), Eva Ntormousi (CEA), Klaus Dolag (USM) 31.10.2012 – EANAM 5 – Kyoto, Japan

Transcript of Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next...

Page 1: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

Global Mean Field Dynamo simulations with SPMHD

Federico StasyszynUSM - Munich

Colaborators:Detlef Elstner (AIP), Alexander Beck (USM), Eva Ntormousi (CEA), Klaus Dolag (USM)

31.10.2012 – EANAM 5 – Kyoto, Japan

Page 2: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

Mean Field Theory.....Mean Field Theory.....

B⃗=⟨ B⃗⟩+ b⃗

∂ B⃗∂ t

=∇×(V⃗× B⃗−η∇× B⃗)

∂ B⃗∂ t

=∇×(V⃗× B⃗−η∇× B⃗+ ξ⃗)

V⃗=⟨V⃗ ⟩+ v⃗

ξ⃗=α B⃗+ γ× B⃗−β∇×B⃗−δ×∇×B⃗+ ...

∂ B⃗∂ t

=∇×(V⃗× B⃗+α B⃗−β∇×B⃗ )

StatisticalProperties

Nice model and workhorse for theoreticians

Non Linear Approach

(from B,V get alpha,beta, etc)

Kinematic approach

(from alpha, beta, etc get B,V)

Theory

Page 3: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD● Lagrangian Scheme

● The mass is discretized, not volume

● Huge dynamical range

● We use a compact Kernel to “smooth” the properties and build derivatives

NOT “Vanilla” SPMHD

● DivB cleaning (Stasyszyn et al. 2012)

● Non-ideal MHD (Bonafede et al. 2011)

● Advanced viscosity formulation (C&D 2012)

Page 4: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

Non-Ideal SPMHD

● Numerical Options:

∂ B⃗∂ t

=∇×(α B⃗−β ∇×B⃗)

∂ B⃗∂ t

=∇×(α B⃗−β ∇×B⃗)

∂ B⃗∂ t

=∇×(α B⃗)−∇ β×∇×B⃗+β∇2 B⃗

Or?

Therefore we have plenty of possible implementations, with their respective performance and different accuracies

Or?

∂ B⃗∂ t

=∇×(α B⃗)−∇×(β×∇× B⃗)

Page 5: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

● Numerical Options:

∂ B⃗∂ t

=∇×(α B⃗−β ∇×B⃗)

∂ B⃗∂ t

=∇×(α B⃗−β ∇×B⃗)

∂ B⃗∂ t

=∇×(α B⃗)−∇ β×∇×B⃗+β∇2 B⃗

Or?

Therefore we have plenty of possible implementations, with their respective performance and different accuracies

Or?

∂ B⃗∂ t

=∇×(α B⃗)−∇×(β×∇× B⃗)+ rearrangement of SPH kernel derivatives

Page 6: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD - Tests● Meinel (1990)

– α2

– Anisotropic

Alpha Quenching

α=α0

B /Beq+1α=

α0

B /Beq+1

Alpha (-)

Alpha (+)

αcrit=( πH

+x1

1

R0)

1/2

SPH Grid

Page 7: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD - Tests● α-Ω

– Rotation: Brandt's law

– Disk Geometry with several boundary conditions

αβ

By

Magnetic field solution:

Page 8: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD - Tests

● Status– α and β terms implemented

– α²-dynamo tested (iso/anisotropic case)

– α-ω dynamo tested

● CωCα = constant, when changing ω (50-200)– Resolution convergence

Page 9: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD – Proof of Concept

Galaxy Model β≈1ρ

α≈±ρSign given by angular momentum

L

Ω ~ 150 Km/s

Page 10: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD – Proof of conceptα

β

Page 11: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD – Proof of concept

Slice trough the center of the galaxy, showing reversal features

Page 12: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

SPMHD – Proof of concept

● Status– We test the sub-grid model with simple mean field

coefficient recipients in Galaxy simulations

– We are able to find some (transient) characteristic features found in galaxies.

Edge on cut of the Galaxy

Page 13: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

● Status and Prospects– We implemented the mean field equations in SPMHD

– Consist checks with solutions (analytically or/and numerically)

– Concept proof of Disk Galaxy initial conditions

– New estimator for Turbulent component

● Next Steps

– Build estimators for local quantities.

– Use Mean field coefficients derived from local high resolution simulations in global simulations (AIP).

– Generate mock observations to compare with real galaxies.

Page 14: Global Mean Field Dynamo simulations with SPMHD...– New estimator for Turbulent component Next Steps – Build estimators for local quantities. – Use Mean field coefficients derived

Thank you!