Download - ROUTES TO TRANSITION IN SHEAR FLOWS
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ROUTES TO TRANSITION IN SHEAR FLOWS
Alessandro Bottaro
with contributions from:
S. Zuccher, I. Gavarini,
P. Luchini and F.T.M. Nieuwstadt
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1. TRANSITION IN SHEAR FLOWS IS A PHENOMENON
STILL NOT FULLY UNDERSTOOD. For the simplest parallel or quasi-parallel flows there is poor agreement between predictions from the classical linear stability theory (Recrit) and
experimentals results (Retrans)
Poiseuille Couette Hagen-Poiseuille Blasius
Recrit 5772 ~ 500
Retrans ~ 1000 ~400 ~2000 ~400
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2. TRANSITION IN SHEAR FLOWS IS A PHENOMENON
STILL NOT FULLY UNDERSTOOD.
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THE MECHANISM: a stationary algebraic instability exists in the inviscid system (“lift-up” effect). In the viscous case the growth of the streaks is hampered by diffusion transient growth
P.H. Alfredsson and M. Matsubara (1996); streaky structures in a boundary
layer. Free-stream speed: 2 [m/s], free-stream turbulence level: 6%
THE TRANSIENT GROWTH
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Proposition: Optimal and robust control of streaks during their initial development phase, in pipes and boundary layers by
acting at the level of the disturbances (“cancellation control”)
acting at the level of the mean flow (“laminar flow control”)
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Optimal cancellation control of streaks
Cancellation Control
Known base flow U(r); disturbance O() control O()
Disturbance field(system’s state)
Control O()
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Optimal laminar flow control of streaks
Laminar Flow Control
Compute base flow O(1) together with the disturbance field O() control O(1)
Whole flow field(system’s state)
Control O(1)
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OPTIMAL CONTROL: A PARABOLIC MODEL PROBLEM
ut + uux = uxx + S u(t,x): state of the systemu(0,x)=u0(x) u0(x): initial conditionu(t,0)=uw(t) uw(t): boundary controlu(t,)=0 S(t,x): volume control
Suppose u0(x) is known; we wish to find thecontrols, uw and S, that minimize the functional:
I(u, uw, S) = u2 dt dx + 2 uw2 dt + 2 S2 dt dx
disturbance norm energy needed to control
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I(u,uw,S) = u2 dt dx + 2 uw2 dt + 2 S2 dt dx
==0 no limitation on the cost of the control
and/or small cost of employing uw and/or S is not important
and/or large cost of employing uw and/or S is important
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For the purpose of minimizing I, let us introduce an augmented functional L = L(u,uw,S,a,b), with a(t,x) and b(t) Lagrange multipliers, and let us minimize the new objective functional
L(u, uw, S, a, b) = I + a (ut + uux - uxx - S) dt dx +
+ b(t) [u(t,0)-uw(t)] dt
Constrained minimization of I
Unconstrained minimization of L
Optimal control
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Optimal control
Each directional derivative must independentlyvanish for a relative minimum of L to exist.
For example it must be:
termsinitialandboundarydt)0,t(ub
dtdxuauuauauu2dt)0,t(ub
dtdxuauuauuauaududI
δududL
xxxt
xxxxt
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Optimal control
Since u is an arbitrary variation, the double integralvanish if and only if the linear adjoint equation
at + uax = - axx + 2u
is satisfied, together with:
a(T,x)=0 terminal conditiona(t,0)=a(t,)=0 boundary conditions
The vanishing of the other directional derivatives is accomplished by letting:
)x,t(a)x,t(S2iff0δSdSdL
)0,t(a)t(b)t(u2iff0δududL
2
xw2
ww
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Optimal control
Resolution algorithm:
adjoint equationsfor dual state a
direct equationsfor state u
(using uw and S)
optimalityconditions:
uw(t)=ax(t,0)/22
S(t,x)=a(t,x)/22
convergencetest
Optimality conditions are enforced by employing a simple gradient or a conjugate gradient method
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ROBUST CONTROL: A PARABOLIC MODEL PROBLEM
ut + uux = uxx + S u(t,x): state of the systemu(0,x)=u0(x) u0(x): initial conditionu(t,0)=uw(t) uw(t): boundary controlu(t,)=0 S(t,x): volume control
Now u0(x) is not known; we wish to find the controls, uw and S, and the initial condition u0(x) that minimize the functional:
I1(u, u0, uw, S) = u2 dt dx + 2 uw2 dt + 2 S2 dt dx -
- 2 u02 dx
i.e. we want to maximize over all u0.
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Robust control
This non-cooperative strategy consists in finding the worst initial condition in the presence of the bestpossible control.
Procedure: like previously we introduce a Lagrangian functional, including a statement on u0
L1(u, u0, uw, S, a, b, c) = I1 + a (ut + uux - uxx - S) dt dx +
b(t) [u(t,0)-uw(t)] dt + c(x) [u(0,x)-u0(x)] dx
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Robust control
Vanishing of yields: 22u0(x)=a(0,x)
Robust control algorithm requires
alternating ascent iterations to find u0 and descent
iterations to find uw and/or S.
Convergence to a saddle point in the space of variables.
00
δududL
22u0(x)=a(0,x)
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Optimal cancellation control of streaks
Optimal control of streaks in pipe flow
Spatially parabolic model for the streaks: structures elongated in the streamwise direction x
Long scale for x: R ReShort scale for r: R
Fast velocity scale for u: Umax
Slow velocity scale for v, w: Umax/Re
Long time: R Re/Umax
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Optimal cancellation control of streaks
Optimal control of streaks in pipe flow
with
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Optimal cancellation control of streaks
withwith
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Initial condition for the state: optimal perturbation, i.e. the disturbance which maximizes the gain G in the absence of control.
Optimal disturbance at x=0
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Optimal disturbance at x=0
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Optimal control
Optimal cancellation control of streaks
with
where is the control statement=
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increases Small
increases Flat
Optimal cancellation control of streaks
Order of magnitude analysis:
Equilibrium
increases Cheap
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As usual we introduce a Lagrangian functional, weimpose stationarity with respect to all independentvariables and recover a system of direct and adjointequations, coupled by transfer and optimality conditions. The system is solved iteratively; at convergence we have the optimal control.
Optimal cancellation control of streaks
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Optimal cancellation control of streaks
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Optimal cancellation control of streaks
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Optimal cancellation control of streaks
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Optimal cancellation control of streaks
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Robust cancellation control of streaks
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Robust cancellation control of streaks
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Optimal and robust cancellation control of streaks
• In theory it is possible to optimally counteract disturbances propagating downstream of an initial point (trivial to counteract a mode)
• Physics: role of buffer streaks
• Robust control laws are available
• Next:• Feedback control, using the framework recently proposed by Cathalifaud & Bewley (2004)
• Is it technically feasible?
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Optimal laminar flow control of streaks
Optimal control of streaks in boundary layer flow
Spatially parabolic model for the streaks: steady structures elongated in the streamwise direction x
Long scale for x: LShort scale for y and z: L/Re
Fast velocity scale for u: U
Slow velocity scale for v, w: U /Re
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Optimal laminar flow control of streaks
Optimal control of streaks in boundary layer flow
with
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Optimal laminar flow control of streaks
::
with the Gain given by:
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Optimal laminar flow control of streaks
Lagrangian functional:
Stationarity of Optimality system
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Optimal laminar flow control of streaks
__________
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Optimal laminar flow control of streaks
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Optimal laminar flow control of streaks
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Robust laminar flow control of streaks
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Robust laminar flow control of streaks
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Optimal and robust laminar flow control of streaks
• Mean flow suction can be found to optimally damp the growth of streaks in the linear and non-linear regimes
• Both in the optimal and robust control case the control laws are remarkably self-similar Bonus for applications
• No need for feedback
• Technically feasible (cf. ALTTA EU project)
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• Optimal control theory is a powerful tool
• Robust control strategies are available through the direct- adjoint machinery
• Optimal feedback control is under way
• Optimal control via tailored magnetic fields should be feasible