Stochastic Shape Optimization

Stochastic Shape Optimization is a computational framework within shape optimization that incorporates random variables or probabilistic models to account for uncertainties in design parameters, loading conditions, or material properties, thereby seeking optimal shapes that are robust under stochastic variations.

22

Publications

638

Citations

61

Authors

37

Institutions

Publications per year

2017–2026

6

Authors

61

  1. MR
    Martin Rumpf

    University of Bonn, Germany

    2 publications · 131 citations

    2

    h-index

  2. SA
    Sherif Aly

    Rutgers, The State University of New Jersey, United States

    2 publications · 59 citations

    2

    h-index

  3. MD
    Matteo Diez

    National Research Council, Italy

    2 publications · 27 citations

    2

    h-index

  4. MP
    Martin Pach

    University of Duisburg-Essen, Germany

    2 publications · 131 citations

    2

    h-index

  5. SC
    Sergio Conti

    University of Bonn, Germany

    2 publications · 131 citations

    2

    h-index

1–5 of 61

Venues

  1. IEEE Transactions on Magnetics

    2 publications · 31 citations

    2

    h-index

  2. Journal of Aircraft

    2 publications · 53 citations

    2

    h-index

  3. Engineering Optimization

    1 publications · 12 citations

    1

    h-index

  4. Theoretical Chemistry Accounts

    1 publications · 90 citations

    1

    h-index

  5. SIAM Journal on Control and Optimization

    1 publications · 36 citations

    1

    h-index

1–5