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Associate Professor at TU Wien


Contact Information


TU Wien
Institut für Analysis und Scientific Computing
Wiedner Hauptstraße 8-10
1040 Wien, Austria



Office

green area on the 4th floor.



Research Interests:

Theory
  • Shape Optimisation
  • Topology Optimisation
  • Sensitivity Analysis
  • Actuator and Sensor Placement
  • Minimax Theory
  • Reproducing Kernels and Mesh Free Methods
  • Stabilisation of Partial Differential Equations
Application
  • Electrical Impedance Tomography
  • Electrical Machines
  • Elasticity


PhD Students


  • Phillip Baumann, phillip.baumann@tuwien.ac.at
  • FWF project, P 32911, Multiphysical Shape Optimization of Electrical Machines, 2020/07/01-2024/06/30, (joint project with Peter Gangl (Radon Institute))
  • Leon Baeck, leon.baeck@itwm.fraunhofer.de
  • Topology Optimization of a Hydrogen Cell at Fraunhofer ITWM, 2022/07/01- (joint supervison with René Pinnau (Kaiserslautern))


Publications


Submitted/Ongoing

  1. Quasi-Newton Methods for Topology Optimization Using a Level-Set Method
    with Sebastian Blauth
    submitted to Structural and Multidisciplinary Optimisation
    [preprint, 2023]
  2. Complete topological asymptotic expansion for \(L_2\) and \(H^1\) tracking-type cost functionals in dimension two and three
    with Phillip Baumann and Peter Gangl
    submitted
    [preprint, 2021]

Accepted and published work (refereed)

  1. The topological state derivative: an optimal control perspective on topology optimisation
    with Phillip Baumann, Idriss Fouquer-Mazari and Kevin Sturm
    Journal of Geometric Analysis
    [preprint, 2023]
  2. Numerical shape optimization of the Canham-Helfrich-Evans bending energy
    with Michael Neunteufel and Joachim Schöberl
    Journal of Computational Physics
    [preprint, 2021]
  3. Automated computation of topological derivatives with application to nonlinear elasticity and reaction-diffusion problems
    with Peter Gangl
    Computer Methods in Applied Mechanics and Engineering
    [preprint, 2022]
  4. Topological derivative for PDEs on surfaces
    with Peter Gangl
    SIAM J. Control Optim.
    [preprint, 2021]
  5. Adjoint based methods for the computation of higher order topological derivatives
    with Phillip Baumann
    Engineering Computations
    [preprint, 2021]
  6. LQ-based Optimal Actuator Design for Vibration Control
    with M. Sajjad Edalatzadeh, Dante Kalise, and Kirsten A. Morris
    IEEE Control Systems Letters
    [preprint, 2020]
  7. First-order differentiability properties of a class of equality constrained optimal value functions with applications to shape optimization
    Journal of Nonsmooth Analysis and Optimization (2020)
    [preprint, 2020]
  8. Fully and Semi-Automated shape differentiation in NGSolve
    with Peter Gangl, Michael Neunteufel, Joachim Schöberl
    Structural and Multidisciplinary Optimization (2020)
    [preprint, 2020]
  9. Asymptotic analysis and topological derivative for 3D quasi-linear magnetostatics
    with Peter Gangl
    ESAIM:M2AN (2020)
    [preprint]
  10. A shape optimization approach for electrical impedance tomography with pointwise measurements
    with Yuri Flores Albuquerque and Antoine Laurain
    Inverse Problems (2020)
    [preprint]
  11. A simplified derivation technique of topological derivatives for quasi-linear transmission problems
    with Peter Gangl
    ESAIM:COCV (2020)
    [preprint]
  12. Topological sensitivities via a Lagrangian approach for semilinear problems
    Nonlinearity (2020)
    [preprint]
  13. On the explicit feedback stabilization of 1D linear nonautonomous parabolic equations via oblique projections
    with S. S. Rodrigues
    IMA J. Math. Control Inform. (2019)
    [preprint]
  14. Weakly-normal basis vector fields in rkhs with an application to shape newton methods
    with Alberto Paganini
    SIAM J. Numer. Anal. (2019)
    [preprint]
  15. Shape optimization via nearly conformal transformations.
    with Jose A. Iglesias and Florian Wechsung
    SIAM J. Sci. Comput. (2018)
    [preprint]
  16. Optimal actuator placement and shaping based on shape calculus.
    with Dante Kalise and Karl Kunisch
    Math. Models Methods Appl. Sci. (2018)
    [preprint]
  17. Reproducing kernel hilbert spaces and variable metric algorithms in pde-constrained shape optimization.
    with Martin Eigel
    Optim. Methods Softw. (2017)
    [preprint]
  18. Parametric semidifferentiability of minimax of lagrangians: averaged adjoint state approach.
    with Michel C. Delfour
    J. Convex Anal. (2017)
    [preprint]
  19. Shape optimization for a class of semilinear variational inequalities with applications to damage models.
    with Christian Heinemann
    SIAM J. Math. Anal. (2016)
    [preprint]
  20. Minimax differentiability via the averaged adjoint for control/shape sensitivity.
    with Michel C. Delfour
    IFAC-PapersOnLine (open access) (2016)
  21. Distortion compensation as a shape optimisation problem for a sharp interface model.
    with Michael Hintermüller and Dietmar Hömberg
    Comput. Optim. Appl. (2016)
    [preprint]
  22. A structure theorem for shape functions defined on submanifolds.
    Interfaces Free Bound. (2016)
    [preprint]
  23. Distributed shape derivative via averaged adjoint method and applications.
    with Antoine Laurain
    ESAIM Math. Model. Numer. Anal. (2016)
    [preprint]
  24. Shape optimization with nonsmooth cost functions: from theory to numerics.
    SIAM J. Control Optim. (2016)
    [preprint]
  25. Shape optimization of an electric motor subject to nonlinear magnetostatics.
    with Peter Gangl, Ulrich Langer, Antoine Laurain and Houcine Meftahi
    SIAM J. Sci. Comput. (2015)
    [preprint]
  26. Minimax Lagrangian approach to the differentiability of nonlinear PDE constrained shape functions without saddle point assumption.
    SIAM J. Control Optim. (2015)
    [preprint]
  27. Shape differentiability under non-linear PDE constraints.
    Internat. Ser. Numer. Math. (2015)

Others

  1. Convergence analysis of Newton's method in shape optimization via approximate normal functions
    preprint
  2. Discretisation and error analysis for a mathematical model of milling processes.
    with Oliver Rott and Dietmar Hömberg
    preprint


Lectures


The course Computer Mathematik in 2020/2021/2022 was supported by data camp. Wedding
Year Winter Semester Summer Semester
2023 Computermathematik (LaTeX+Python) (VU 3.5 SWS)
Numerical Optimisation (3V+1U)
Seminar:Computational Mathematics (2 SWS)
2022 Optimisation with PDE constraints (VU 4SWS)
Seminar: Optimization and shape optimization with PDEs (2 SWS) 		Computermathematik (LaTeX+Python) (VU 3.5 SWS)
Numerical Optimisation (3V+1U)
Seminar:Computational Mathematics (2 SWS)
2021 Computermathematik (LaTeX+Python) (VU 3.5SWS)
2020 Numerische Mathematik Computermathematik (LaTeX+Python)
Seminar:Optimisation and shape optimisation, (info see TISS)
2019 Optimisation with PDE constraints (VU 4SWS)
Seminar:Optimisation and shape optimisation with partial differential equations, (info see TISS)

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