Research on Ekman at the Linn

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Research on Ekmanat the Linné Flow Center, KTH
Mechanics
Dan Henningson, Director
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• Funded by VR as an one of the 20 original Linné
  centers of excellence

http//www.flow.kth.se
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Linné FLOW Centre

• Vision
• FLOW as an outstanding environment for
  fundamental research in fluid mechanics, where
  innovative research is born and future research
  leaders are fostered

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Activities and infrastructure

• Research projects
• Graduate school
• Summer programs
• Workshops/conferences
• Seminars and visiting scientists
• Infrastructure
• World class wind-tunnels and acoustic measurement
  facilities
• Climate and Turbulence computer Ekman

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Research areas

• Why do flows become turbulent?
• How does turbulence behave in the ocean and
  atmosphere?
• Why does turbulence generate noise?
• How can we make flows behave the way we want to?
• Why do fibers bundle?

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Turbulent flows are everywhere, and they can be
described by
From www.efluids.com
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How do we perform numerical experiments?

• Solve the Navier-Stokes equations for the
  velocity on grid points using super computers

Ekman Dell cluster (2008) 100 Tflops 12000
processors
Cray-1 (1976) 100 Mflops 1 processor
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Efficient simulations on many processors
Nek5000
SIMSON
speed-up
processors
processors
How much faster does the simulation run on many
processors? linear scaling
measurements (IBM BG/L)
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How can simulations help make modern aircraft
more environmentally friendly?

• Suppressing turbulence on the wings (laminar flow
  control) improve fuel efficiency
• Better models of turbulence on wing surfaces
  improve engineering design
• Example Airbus green aircraft concept

EU NACRE project Concept for quiet, light fuel
efficient aircraft
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Direct Numerical Simulations of all scales in the
turbulent flow (no models)
Turbulence close to the surface ? Friction ? Drag
? Fuel consumption
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Direct Numerical Simulations of turbulent flow

• 6144 x 385 x 576 1.4 billion grid points

Large range of scales require huge number of
gridpoints
Simulations streamwise velocity in wall-parallel
plane 20 cm x 0.8 cm, simulation on BlueGene at
PDC
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What can we learn from even larger simulations?

• 12288 x 721 x 1152 11 billion grid points
• Overlap with large scale experiments

Domain size
Large scale experiments
Ekman
Ciclope project large pipe flow facility in 130
m Italian tunnel
Previous simulations
Re
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What can we learn from even larger simulations?

• 12288 x 721 x 1152 11 billion grid points
• Overlap with large scale experiments
• Dynamics of large scale turbulent structures and
  their interaction with small near-wall structures
• Provide quantities difficult to measure, input in
  engineering models of turbulence
• Independent prediction of quantities like drag
• How to best suppress turbulence on the wing

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How will the ocean circulation respond to global
warming?

• Ocean large heat regulator of climate
• Great conveyor belt transport warm surface water
  to north pole and cold water back along bottom
• Circulation affected by global warming?

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The ocean is turbulent!
Simulation ECCO code using MITgcm. JPL. NASA Ames
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The global circulation is very sensitive to the
turbulent diffusivity(Nilsson et al., MISU)
There is even turbulence at centimeter scale!
Smaller scales determine turbulent diffusivity,
how fast is the cold water cooling the warmer
water above ?
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What are we doing now?
Direct Numerical Simulation of ocean
turbulence2048 x 2048 x 384 1.6 billion grid
points
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What will we do?Larger DNS of ocean
turbulence4096 x 4096 x 1024 17 billion grid
points
Simulation Kelvin-Helmholz breakdown by Colorado
Res. Ass.
Ekman may give answer on turbulent diffusivity in
ocean
bridge gap between larger scales affected by
density differences and smaller isotropic scales
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Simulations on Ekman will help fill the gap
between smallest scales accounted for in climate
and engineering models and those of importance in
nature

• Examples
• Simulations of ocean turbulence to predict
  turbulent diffusivity influencing how the ocean
  responds to global warming
• Simulations of turbulence in boundary layers on
  aircraft and ground vehicles to improve
  engineering predictions of drag
• Simulations of the onset of turbulence on wings
  to develop laminar flow control and lower fuel
  consumption