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UID:news823@dmi.unibas.ch
DTSTAMP;TZID=Europe/Zurich:20190214T222417
DTSTART;TZID=Europe/Zurich:20190222T110000
SUMMARY:Seminar in Numerical Analysis: Edwin Mai  (Universität der Bundesw
 ehr München)
DESCRIPTION:With an increasing range of applications\, Shape Optimisation p
 roblems receive more and more interest in the engineering community\, whil
 e solving such problems is still a demanding task. In this talk the exampl
 e of a Stokes channel flow with the objective to reduce the energy dissipa
 tion is considered\, on which an optimise-then-discretize approach shall b
 e applied. Starting with a gradient descent method\, based on the analytic
 al shape derivative and the adjoint approach\, an initial optimisation pro
 cedure is discussed and differences in the shape derivative representation
  and their numerical implications are highlighted. Subsequently a possible
  way to derive shape hessian information in a so-called tangent-on-reverse
  method\, i.e. combining the adjoint and sensitivity approach\, is introdu
 ced. The shape hessian is utilised in a reduced SQP method for the equally
  constrained channel flow problem comprising of the objective\, PDE and ad
 ditional geometric constraints. In contrary to a one-shot approach the red
 uced approach requires the state and adjoint equations to be solved exactl
 y for each optimisation step. Finally\, some features of the numerical imp
 lementation using the finite element software package FEniCS and the obtai
 ned results are presented to show superiority of using hessian information
 .For further information about the seminar\, please visit this webpage.
X-ALT-DESC: With an increasing range of applications\, Shape Optimisation p
 roblems receive more and more interest in the engineering community\, whil
 e solving such problems is still a demanding task. In this talk the exampl
 e of a Stokes channel flow with the objective to reduce the energy dissipa
 tion is considered\, on which an optimise-then-discretize approach shall b
 e applied. Starting with a gradient descent method\, based on the analytic
 al shape derivative and the adjoint approach\, an initial optimisation pro
 cedure is discussed and differences in the shape derivative representation
  and their numerical implications are highlighted. Subsequently a possible
  way to derive shape hessian information in a so-called tangent-on-reverse
  method\, i.e. combining the adjoint and sensitivity approach\, is introdu
 ced. The shape hessian is utilised in a reduced SQP method for the equally
  constrained channel flow problem comprising of the objective\, PDE and ad
 ditional geometric constraints. In contrary to a one-shot approach the red
 uced approach requires the state and adjoint equations to be solved exactl
 y for each optimisation step. Finally\, some features of the numerical imp
 lementation using the finite element software package FEniCS and the obtai
 ned results are presented to show superiority of using hessian information
 .<br /><br />For further information about the seminar\, please visit this
  <link de/forschung/mathematik/seminar-in-numerical-analysis/ - - "Opens i
 nternal link in current window">webpage</link>.
DTEND;TZID=Europe/Zurich:20190222T120000
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