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 - CHAP A1 - Lorenz, Imke-Sophie B. A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Graph-theoretic resilience analysis of a water distribution system's topology T2 - World Congress on Resilience, Reliability and Asset Management 2019 N2 - Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. In practice, the focus is set on the most beneficial maintenance measures and/or capacity adaptations of existing water distribution systems (WDS). Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of 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, metrics based on graph theory have been proposed. In this study, a promising approach is applied to assess the resilience of the WDS for a district in a major German City. The conducted analysis provides insight into the process of actively influencing the resilience of WDS KW - Resilience Assessment KW - Graph Theory KW - Water Supply System KW - Case Study Y1 - 2019 N1 - World Congress on Resilience, Reliability and Asset Management, 28-31 July 2019. Furama Riverfront Hotel, Singapore SP - 106 EP - 109 ER - TY - CHAP A1 - Leise, Philipp A1 - Breuer, Tim A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Development, validation and assessment of a resilient pumping system T2 - Proceedings of the Joint International Resilience Conference, JIRC2020 N2 - 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. KW - water supply system KW - fault detection KW - anticipation strategy Y1 - 2020 SN - 978-90-365-5095-6 N1 - Proceedings of the Joint International Resilience Conference 2020. Interconnected: Resilience Innovations for Sustainable Development Goals. 23 - 27 November, 2020 SP - 97 EP - 100 ER - TY - JOUR A1 - Leise, Philipp A1 - Eßer, Arved A1 - Eichenlaub, Tobias A1 - Schleiffer, Jean-Eric A1 - Altherr, Lena A1 - Rinderknecht, Stephan A1 - Pelz, Peter F. T1 - Sustainable system design of electric powertrains - comparison of optimization methods JF - Engineering Optimization N2 - The transition within transportation towards battery electric vehicles can lead to a more sustainable future. To account for the development goal ‘climate action’ stated by the United Nations, it is mandatory, within the conceptual design phase, to derive energy-efficient system designs. One barrier is the uncertainty of the driving behaviour within the usage phase. This uncertainty is often addressed by using a stochastic synthesis process to derive representative driving cycles and by using cycle-based optimization. To deal with this uncertainty, a new approach based on a stochastic optimization program is presented. This leads to an optimization model that is solved with an exact solver. It is compared to a system design approach based on driving cycles and a genetic algorithm solver. Both approaches are applied to find efficient electric powertrains with fixed-speed and multi-speed transmissions. Hence, the similarities, differences and respective advantages of each optimization procedure are discussed. KW - Powertrain KW - stochastic optimization KW - global optimization KW - genetic algorithm Y1 - 2021 U6 - http://dx.doi.org/10.1080/0305215X.2021.1928660 SN - 0305-215X PB - Taylor & Francis CY - London 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 - 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 - CHAP A1 - Meck, Marvin M. A1 - Müller, Tim M. A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Improving an industrial cooling system using MINLP, considering capital and operating costs T2 - Operations Research Proceedings 2019 N2 - 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. KW - Engineering optimisation KW - Mixed-integer programming KW - Industrial optimisation KW - Cooling system KW - Process engineering Y1 - 2020 SN - 978-3-030-48438-5 (Print) SN - 978-3-030-48439-2 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_61 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019. SP - 505 EP - 512 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 - 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 - Müller, Tim M. A1 - Altherr, Lena A1 - Leise, Philipp A1 - Pelz, Peter F. T1 - Optimization of pumping systems for buildings: Experimental validation of different degrees of model detail on a modular test rig T2 - Operations Research Proceedings 2019 N2 - 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. KW - Experimental validation KW - MINLP KW - Engineering optimization KW - Water supply system KW - Network design Y1 - 2020 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_58 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 481 EP - 488 PB - Springer CY - Cham ER -