TY - CHAP A1 - Pfetsch, Marc E. A1 - Abele, Eberhard A1 - Altherr, Lena A1 - Bölling, Christian A1 - Brötz, Nicolas A1 - Dietrich, Ingo A1 - Gally, Tristan A1 - Geßner, Felix A1 - Groche, Peter A1 - Hoppe, Florian A1 - Kirchner, Eckhard A1 - Kloberdanz, Hermann A1 - Knoll, Maximilian A1 - Kolvenbach, Philip A1 - Kuttich-Meinlschmidt, Anja A1 - Leise, Philipp A1 - Lorenz, Ulf A1 - Matei, Alexander A1 - Molitor, Dirk A. A1 - Niessen, Pia A1 - Pelz, Peter F. A1 - Rexer, Manuel A1 - Schmitt, Andreas A1 - Schmitt, Johann M. A1 - Schulte, Fiona A1 - Ulbrich, Stefan A1 - Weigold, Matthias T1 - Strategies for mastering uncertainty T2 - Mastering uncertainty in mechanical engineering N2 - 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. Y1 - 2021 SN - 978-3-030-78353-2 U6 - http://dx.doi.org/10.1007/978-3-030-78354-9_6 N1 - Part of the Springer Tracts in Mechanical Engineering book series (STME) SP - 365 EP - 456 PB - Springer CY - Cham ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. ED - Neufeld, Janis S. ED - Buscher, Udo ED - Lasch, Rainer ED - Möst, Dominik ED - Schönberger, Jörn T1 - Assessing and Optimizing the Resilience of Water Distribution Systems Using Graph-Theoretical Metrics T2 - Operations Research Proceedings 2019 N2 - Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience. KW - OR 2019 KW - business analytics KW - decision analytics KW - digital economy KW - mathematical optimization Y1 - 2020 SN - 978-3-030-48439-2 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_63 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 521 EP - 527 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Lorenz, Ulf A1 - Pelz, Peter F. A1 - Pöttgen, Philipp ED - Lübbecke, Marco E. ED - Koster, Arie ED - Letmathe, Peter ED - Madlener, Reihard ED - Preis, Britta ED - Walther, Grit T1 - Designing a feedback control system via mixed-integer programming T2 - Operations Research Proceedings 2014: Selected Papers of the Annual International Conference of the German Operations Research N2 - Pure analytical or experimental methods can only find a control strategy for technical systems with a fixed setup. In former contributions we presented an approach that simultaneously finds the optimal topology and the optimal open-loop control of a system via Mixed Integer Linear Programming (MILP). In order to extend this approach by a closed-loop control we present a Mixed Integer Program for a time discretized tank level control. This model is the basis for an extension by combinatorial decisions and thus for the variation of the network topology. Furthermore, one is able to appraise feasible solutions using the global optimality gap. KW - Optimal Topology KW - Controller Parameter KW - Level Control System KW - Technical Operation Research KW - Optimal Closed Loop Y1 - 2016 SN - 978-3-319-28695-2 U6 - http://dx.doi.org/10.1007/978-3-319-28697-6_18 SP - 121 EP - 127 PB - Springer CY - Cham ER - TY - CHAP A1 - Müller, Tim M. A1 - Schmitt, Andreas A1 - Leise, Philipp A1 - Meck, Tobias A1 - Altherr, Lena A1 - Pelz, Peter F. A1 - Pfetsch, Marc E. T1 - Validation of an optimized resilient water supply system T2 - Uncertainty in Mechanical Engineering N2 - 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. KW - Optimization KW - Mixed-integer nonlinear programming KW - Water distribution system KW - Resilience KW - Validation Y1 - 2021 SN - 978-3-030-77255-0 SN - 978-3-030-77256-7 U6 - http://dx.doi.org/10.1007/978-3-030-77256-7_7 N1 - Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), June 7–8, 2021 SP - 70 EP - 80 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Simon, Nicolai A1 - Pelz, Peter F. T1 - Finding global-optimal gearbox designs for battery electric vehicles T2 - Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019 N2 - In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements. KW - Powertrain KW - Gearbox KW - Optimization KW - BEV KW - WLTP Y1 - 2019 SN - 978-3-030-21802-7 U6 - http://dx.doi.org/10.1007/978-3-030-21803-4_91 SP - 916 EP - 925 PB - Springer CY - Cham ER - TY - JOUR A1 - Rausch, Lea A1 - Friesen, John A1 - Altherr, Lena A1 - Meck, Marvin A1 - Pelz, Peter F. T1 - A holistic concept to design optimal water supply infrastructures for informal settlements using remote sensing data JF - Remote Sensing N2 - Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data. KW - water supply design KW - mathematical optimization KW - slum classification KW - remote sensing Y1 - 2018 SN - 2072-4292 U6 - http://dx.doi.org/10.3390/rs10020216 VL - 10 IS - 2 SP - 1 EP - 23 PB - MDPI CY - Basel ER - TY - JOUR A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Pfetsch, Marc E. A1 - Pelz, Peter F. T1 - Maschinelles Design eines optimalen Getriebes JF - ATZ - Automobiltechnische Zeitschrift N2 - 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, können leicht innovative und vor allem kostenminimale Lösungen übersehen werden. Im Rahmen eines Forschungsprojekts hat die TU Darmstadt spezielle Optimierungsmethoden angewendet, um auch bei großen Lösungsräumen zielsicher ein für die individuellen Zielstellungen optimales Layout zu finden. Y1 - 2018 SN - 2192-8800 U6 - http://dx.doi.org/10.1007/s35148-018-0131-3 VL - 120 IS - 10 SP - 72 EP - 77 PB - Springer Nature CY - Cham ER - TY - CHAP A1 - Müller, Tim M. A1 - Altherr, Lena A1 - Ahola, Marja A1 - Schabel, Samuel A1 - Pelz, Peter F. ED - Rodrigues, H. C. T1 - Multi-Criteria optimization of pressure screen systems in paper recycling – balancing quality, yield, energy consumption and system complexity T2 - EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization N2 - 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. Y1 - 2019 SN - 978-3-319-97773-7 U6 - http://dx.doi.org/10.1007/978-3-319-97773-7_105 N1 - EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization. 17-19 September 2018. Lisboa, Portugal PB - Springer International Publishing CY - Basel ER - TY - JOUR A1 - Sun, Hui A1 - Altherr, Lena A1 - Pei, Ji A1 - Pelz, Peter F. A1 - Yuan, Shouqi T1 - Optimal booster station design and operation under uncertain load JF - Applied Mechanics and Materials N2 - Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the system’s resilience can be engineered KW - Stochastic Programming KW - Chance Constraint KW - Engineering Application KW - Pump System KW - Water Distribution Y1 - 2018 U6 - http://dx.doi.org/10.4028/www.scientific.net/AMM.885.102 SN - 1662-7482 VL - 885 SP - 102 EP - 115 PB - Trans Tech Publications CY - Bäch ER - TY - CHAP A1 - Müller, Tim M. A1 - Altherr, Lena A1 - Ahola, Marja A1 - Schabel, Samuel A1 - Pelz, Peter F. T1 - Optimizing pressure screen systems in paper recycling: optimal system layout, component selection and operation N2 - Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield. KW - Mixed-integer nonlinear problem KW - MINLP KW - Process engineering KW - Paper recycling KW - Multi-criteria optimization Y1 - 2018 SN - 978-3-030-18499-5 U6 - http://dx.doi.org/10.1007/978-3-030-18500-8_44 SP - 355 EP - 361 PB - Springer CY - Cham ER -