@inproceedings{RauschLeiseEdereretal.2016, author = {Rausch, Lea and Leise, Philipp and Ederer, Thorsten and Altherr, Lena and Pelz, Peter F.}, title = {A comparison of MILP and MINLP solver performance on the example of a drinking water supply system design problem}, series = {ECCOMAS Congress 2016 VII European Congress on Computational Methods in Applied Sciences and Engineering}, booktitle = {ECCOMAS Congress 2016 VII European Congress on Computational Methods in Applied Sciences and Engineering}, editor = {Papadrakakis, M. and Ppadopoulos, V. and Stefanou, G. and Plevris, V.}, isbn = {978-618-82844-0-1}, pages = {8509 -- 8527}, year = {2016}, abstract = {Finding a good system topology with more than a handful of components is a highly non-trivial task. The system needs to be able to fulfil all expected load cases, but at the same time the components should interact in an energy-efficient way. An example for a system design problem is the layout of the drinking water supply of a residential building. It may be reasonable to choose a design of spatially distributed pumps which are connected by pipes in at least two dimensions. This leads to a large variety of possible system topologies. To solve such problems in a reasonable time frame, the nonlinear technical characteristics must be modelled as simple as possible, while still achieving a sufficiently good representation of reality. The aim of this paper is to compare the speed and reliability of a selection of leading mathematical programming solvers on a set of varying model formulations. This gives us empirical evidence on what combinations of model formulations and solver packages are the means of choice with the current state of the art.}, language = {en} } @inproceedings{LeiseAltherr2018, author = {Leise, Philipp and Altherr, Lena}, title = {Optimizing the design and control of decentralized water supply systems - a case-study of a hotel building}, series = {EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization}, booktitle = {EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-97773-7}, doi = {10.1007/978-3-319-97773-7_107}, pages = {1241 -- 1252}, year = {2018}, abstract = {To increase pressure to supply all floors of high buildings with water, booster stations, normally consisting of several parallel pumps in the basement, are used. In this work, we demonstrate the potential of a decentralized pump topology regarding energy savings in water supply systems of skyscrapers. We present an approach, based on Mixed-Integer Nonlinear Programming, that allows to choose an optimal network topology and optimal pumps from a predefined construction kit comprising different pump types. Using domain-specific scaling laws and Latin Hypercube Sampling, we generate different input sets of pump types and compare their impact on the efficiency and cost of the total system design. As a realistic application example, we consider a hotel building with 325 rooms, 12 floors and up to four pressure zones.}, language = {en} } @inproceedings{LeiseAltherrPelz2018, author = {Leise, Philipp and Altherr, Lena and Pelz, Peter F.}, title = {Technical Operations Research (TOR) - Algorithms, not Engineers, Design Optimal Energy Efficient and Resilient Cooling Systems}, series = {FAN2018 - Proceedings of the International Conference on Fan Noise, Aerodynamics, Applications and Systems}, booktitle = {FAN2018 - Proceedings of the International Conference on Fan Noise, Aerodynamics, Applications and Systems}, pages = {1 -- 12}, year = {2018}, abstract = {The overall energy efficiency of ventilation systems can be improved by considering not only single components, but by considering as well the interplay between every part of the system. With the help of the method "TOR" ("Technical Operations Research"), which was developed at the Chair of Fluid Systems at TU Darmstadt, it is possible to improve the energy efficiency of the whole system by considering all possible design choices programmatically. We show the ability of this systematic design approach with a ventilation system for buildings as a use case example. Based on a Mixed-Integer Nonlinear Program (MINLP) we model the ventilation system. We use binary variables to model the selection of different pipe diameters. Multiple fans are model with the help of scaling laws. The whole system is represented by a graph, where the edges represent the pipes and fans and the nodes represents the source of air for cooling and the sinks, that have to be cooled. At the beginning, the human designer chooses a construction kit of different suitable fans and pipes of different diameters and different load cases. These boundary conditions define a variety of different possible system topologies. It is not possible to consider all topologies by hand. With the help of state of the art solvers, on the other side, it is possible to solve this MINLP. Next to this, we also consider the effects of malfunctions in different components. Therefore, we show a first approach to measure the resilience of the shown example use case. Further, we compare the conventional approach with designs that are more resilient. These more resilient designs are derived by extending the before mentioned model with further constraints, that consider explicitly the resilience of the overall system. We show that it is possible to design resilient systems with this method already in the early design stage and compare the energy efficiency and resilience of these different system designs.}, language = {en} } @inproceedings{LeiseSimonAltherr2020, author = {Leise, Philipp and Simon, Nicolai and Altherr, Lena}, title = {Comparison of Piecewise Linearization Techniques to Model Electric Motor Efficiency Maps: A Computational Study}, series = {Operations Research Proceedings 2019}, booktitle = {Operations Research Proceedings 2019}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-48439-2}, doi = {10.1007/978-3-030-48439-2_55}, pages = {457 -- 463}, year = {2020}, abstract = {To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.}, language = {en} } @inproceedings{LeiseBreuerAltherretal.2020, author = {Leise, Philipp and Breuer, Tim and Altherr, Lena and Pelz, Peter F.}, title = {Development, validation and assessment of a resilient pumping system}, series = {Proceedings of the Joint International Resilience Conference, JIRC2020}, booktitle = {Proceedings of the Joint International Resilience Conference, JIRC2020}, isbn = {978-90-365-5095-6}, pages = {97 -- 100}, year = {2020}, abstract = {The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient system behaviour.}, 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} } @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} }