@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}
}
@inproceedings{MeckMuellerAltherretal.2020,
  author    = {Meck, Marvin M. and M{\"u}ller, Tim M. and Altherr, Lena and Pelz, Peter F.},
  title     = {Improving an industrial cooling system using MINLP, considering capital and operating costs},
  series = {Operations Research Proceedings 2019},
  booktitle = {Operations Research Proceedings 2019},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-48438-5 (Print)},
  doi       = {10.1007/978-3-030-48439-2_61},
  pages     = {505 -- 512},
  year      = {2020},
  abstract  = {The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system.},
  language  = {en}
}
@inproceedings{MuellerAltherrLeiseetal.2020,
  author    = {M{\"u}ller, Tim M. and Altherr, Lena and Leise, Philipp and Pelz, Peter F.},
  title     = {Optimization of pumping systems for buildings: Experimental validation of different degrees of model detail on a modular test rig},
  series = {Operations Research Proceedings 2019},
  booktitle = {Operations Research Proceedings 2019},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-48438-5},
  doi       = {10.1007/978-3-030-48439-2_58},
  pages     = {481 -- 488},
  year      = {2020},
  abstract  = {Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.},
  language  = {en}
}