@inproceedings{LorenzAltherrPelz2020, author = {Lorenz, Imke-Sophie and Altherr, Lena and Pelz, Peter F.}, title = {Resilience enhancement of critical infrastructure - graph-theoretical resilience analysis of the water distribution system in the German city of Darmstadt}, series = {14th WCEAM Proceedings}, booktitle = {14th WCEAM Proceedings}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-64228-0}, doi = {10.1007/978-3-030-64228-0_13}, pages = {137 -- 149}, year = {2020}, abstract = {Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS.}, language = {en} } @inproceedings{AltherrEdererFarnetaneetal.2017, author = {Altherr, Lena and Ederer, Thorsten and Farnetane, Lucas S. and P{\"o}ttgen, Philipp and Verg{\´e}, Angela and Pelz, Peter F.}, title = {Multicriterial design of a hydrostatic transmission system via mixed-integer programming}, series = {Operations Research Proceedings 2015}, booktitle = {Operations Research Proceedings 2015}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-42901-4}, doi = {10.1007/978-3-319-42902-1_41}, pages = {301 -- 307}, year = {2017}, abstract = {In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system's reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system.}, language = {en} } @inproceedings{SchaenzleAltherrEdereretal.2015, author = {Sch{\"a}nzle, Christian and Altherr, Lena and Ederer, Thorsten and Lorenz, Ulf and Pelz, Peter F.}, title = {As good as it can be: Ventilation system design by a combined scaling and discrete optimization method}, series = {Proceedings of FAN 2015}, booktitle = {Proceedings of FAN 2015}, pages = {1 -- 11}, year = {2015}, abstract = {The understanding that optimized components do not automatically lead to energy-efficient systems sets the attention from the single component on the entire technical system. At TU Darmstadt, a new field of research named Technical Operations Research (TOR) has its origin. It combines mathematical and technical know-how for the optimal design of technical systems. We illustrate our optimization approach in a case study for the design of a ventilation system with the ambition to minimize the energy consumption for a temporal distribution of diverse load demands. By combining scaling laws with our optimization methods we find the optimal combination of fans and show the advantage of the use of multiple fans.}, language = {en} } @inproceedings{AltherrEdererVergeetal.2015, author = {Altherr, Lena and Ederer, Thorsten and Verg{\´e}, Angela and Pelz, Peter F.}, title = {Algorithmische Struktursynthese eines hydrostatischen Getriebes}, series = {Antriebssysteme 2015 : Elektrik, Mechanik, Fluidtechnik in der Anwendung}, booktitle = {Antriebssysteme 2015 : Elektrik, Mechanik, Fluidtechnik in der Anwendung}, publisher = {VDI-Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-092268-3}, pages = {145 -- 155}, year = {2015}, language = {de} } @inproceedings{AltherrEdererSchaenzleetal.2017, author = {Altherr, Lena and Ederer, Thorsten and Sch{\"a}nzle, Christian and Lorenz, Ulf and Pelz, Peter F.}, title = {Algorithmic system design using scaling and affinity laws}, series = {Operations Research Proceedings 2015}, booktitle = {Operations Research Proceedings 2015}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-42901-4}, doi = {10.1007/978-3-319-42902-1}, pages = {605 -- 611}, year = {2017}, abstract = {Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem.}, language = {en} } @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{RauschFriesenAltherretal.2018, author = {Rausch, Lea and Friesen, John and Altherr, Lena and Pelz, Peter F.}, title = {Using mixed-integer programming for the optimal design of water supply networks for slums}, series = {Operations Research Proceedings 2017}, booktitle = {Operations Research Proceedings 2017}, editor = {Kliewer, Natalia and Ehmke, Jan Fabian and Bornd{\"o}rfer, Ralf}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-89919-0 (Print)}, doi = {10.1007/978-3-319-89920-6_68}, pages = {509 -- 516}, year = {2018}, abstract = {The UN sets the goal to ensure access to water and sanitation for all people by 2030. To address this goal, we present a multidisciplinary approach for designing water supply networks for slums in large cities by applying mathematical optimization. The problem is modeled as a mixed-integer linear problem (MILP) aiming to find a network describing the optimal supply infrastructure. To illustrate the approach, we apply it on a small slum cluster in Dhaka, Bangladesh.}, language = {en} } @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} } @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{MuellerAltherrAholaetal.2019, author = {M{\"u}ller, Tim M. and Altherr, Lena and Ahola, Marja and Schabel, Samuel and Pelz, Peter F.}, title = {Multi-Criteria optimization of pressure screen systems in paper recycling - balancing quality, yield, energy consumption and system complexity}, series = {EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization}, booktitle = {EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization}, editor = {Rodrigues, H. C.}, publisher = {Springer International Publishing}, address = {Basel}, isbn = {978-3-319-97773-7}, doi = {10.1007/978-3-319-97773-7_105}, year = {2019}, abstract = {The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.}, language = {en} }