@incollection{PfetschAbeleAltherretal.2021,
  author    = {Pfetsch, Marc E. and Abele, Eberhard and Altherr, Lena and B{\"o}lling, Christian and Br{\"o}tz, Nicolas and Dietrich, Ingo and Gally, Tristan and Geßner, Felix and Groche, Peter and Hoppe, Florian and Kirchner, Eckhard and Kloberdanz, Hermann and Knoll, Maximilian and Kolvenbach, Philip and Kuttich-Meinlschmidt, Anja and Leise, Philipp and Lorenz, Ulf and Matei, Alexander and Molitor, Dirk A. and Niessen, Pia and Pelz, Peter F. and Rexer, Manuel and Schmitt, Andreas and Schmitt, Johann M. and Schulte, Fiona and Ulbrich, Stefan and Weigold, Matthias},
  title     = {Strategies for mastering uncertainty},
  series = {Mastering uncertainty in mechanical engineering},
  booktitle = {Mastering uncertainty in mechanical engineering},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-78353-2},
  doi       = {10.1007/978-3-030-78354-9_6},
  pages     = {365 -- 456},
  year      = {2021},
  abstract  = {This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems.},
  language  = {en}
}
@inproceedings{MuellerSchmittLeiseetal.2021,
  author    = {M{\"u}ller, Tim M. and Schmitt, Andreas and Leise, Philipp and Meck, Tobias and Altherr, Lena and Pelz, Peter F. and Pfetsch, Marc E.},
  title     = {Validation of an optimized resilient water supply system},
  series = {Uncertainty in Mechanical Engineering},
  booktitle = {Uncertainty in Mechanical Engineering},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-77255-0},
  doi       = {10.1007/978-3-030-77256-7_7},
  pages     = {70 -- 80},
  year      = {2021},
  abstract  = {Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.},
  language  = {en}
}
@article{AltherrEdererPfetschetal.2018,
  author    = {Altherr, Lena and Ederer, Thorsten and Pfetsch, Marc E. and Pelz, Peter F.},
  title     = {Maschinelles Design eines optimalen Getriebes},
  series = {ATZ - Automobiltechnische Zeitschrift},
  volume    = {120},
  journal   = {ATZ - Automobiltechnische Zeitschrift},
  number    = {10},
  publisher = {Springer Nature},
  address   = {Cham},
  isbn      = {2192-8800},
  doi       = {10.1007/s35148-018-0131-3},
  pages     = {72 -- 77},
  year      = {2018},
  abstract  = {Nahezu 100.000 denkbare Strukturen kann ein Getriebe bei gleicher Funktion aufweisen - je nach Ganganzahl und gefordertem Freiheitsgrad. Mit dem traditionellen Ansatz bei der Entwicklung, einzelne vielversprechende Systemkonfigurationen manuell zu identifizieren und zu vergleichen, k{\"o}nnen leicht innovative und vor allem kostenminimale L{\"o}sungen {\"u}bersehen werden. Im Rahmen eines Forschungsprojekts hat die TU Darmstadt spezielle Optimierungsmethoden angewendet, um auch bei großen L{\"o}sungsr{\"a}umen zielsicher ein f{\"u}r die individuellen Zielstellungen optimales Layout zu finden.},
  language  = {de}
}
@inproceedings{AltherrPelzEdereretal.2017,
  author    = {Altherr, Lena and Pelz, Peter F. and Ederer, Thorsten and Pfetsch, Marc E.},
  title     = {Optimale Getriebe auf Knopfdruck: Gemischt-ganzzahlige nichtlineare Optimierung zur Entscheidungsunterst{\"u}tzung bei der Auslegung von Getrieben f{\"u}r Kraftfahrzeuge},
  series = {Antriebstechnisches Kolloquium ATK 2017},
  booktitle = {Antriebstechnisches Kolloquium ATK 2017},
  editor    = {Jacobs, Georg},
  isbn      = {9783743148970},
  pages     = {313 -- 325},
  year      = {2017},
  language  = {de}
}