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Search: id:"swepub:oai:DiVA.org:kth-237220" > Optimal disturbance...

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  • Adjoint-based iterative methods are employed in order to compute linear optimal disturbances in the case of a spatially growing boundary layer around an elliptic leading edge. The Lagrangian approach is used where an objective function is chosen and constraints are assigned. The optimization problem is solved using power iterations combined with a matrix-free formulation, where the state is marched forward in time with a standard DNS solver and backward with the adjoint solver until a chosen criterion is fulfilled. We consider the global and the upstream localized optimal initial condition leading to the largest possible energy amplification at time T . We find that the two-dimensional initial condition with the largest potential for growth is a Tollmien-Schichting-like wave packet that includes the Orr mechanism and is located inside the boundary layer, downstream of the leading edge. The localized optimal initial condition method allows a more precise systematic study of leading edge effects; we propose it a new method to study receptivity. We find the two-dimensional disturbances are inefficient at triggering an unstable eigenmode. The three-dimensional disturbances exploit the lift up mechanism; both the global and upstream localized disturbances give significant growth. These findings support the hypothesis of high receptivity to three-dimensional disturbances. 

Subject headings

NATURVETENSKAP  -- Matematik -- Beräkningsmatematik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Computational Mathematics (hsv//eng)

Keyword

Atmospheric thermodynamics
Boundary layers
Iterative methods
Lagrange multipliers
Turbulence
Energy amplification
Initial conditions
La-grangian approaches
Objective functions
Optimal disturbances
Optimization problems
Three-dimensional disturbances
Turbulence and shears
Shear flow

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Monokrousos, Ant ...
Brandt, Luca
Mavriplis, Cathe ...
Henningson, Dan ...
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NATURAL SCIENCES
NATURAL SCIENCES
and Mathematics
and Computational Ma ...
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Royal Institute of Technology

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