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 - https://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 - https://doi.org/10.1007/s35148-018-0131-3 VL - 120 IS - 10 SP - 72 EP - 77 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Altherr, Lena A1 - Joggerst, Laura A1 - Leise, Philipp A1 - Pfetsch, Marc E. A1 - Schmitt, Andreas A1 - Wendt, Janine T1 - On obligations in the development process of resilient systems with algorithmic design methods JF - Applied Mechanics and Materials N2 - Advanced computational methods are needed both for the design of large systems and to compute high accuracy solutions. Such methods are efficient in computation, but the validation of results is very complex, and highly skilled auditors are needed to verify them. We investigate legal questions concerning obligations in the development phase, especially for technical systems developed using advanced methods. In particular, we consider methods of resilient and robust optimization. With these techniques, high performance solutions can be found, despite a high variety of input parameters. However, given the novelty of these methods, it is uncertain whether legal obligations are being met. The aim of this paper is to discuss if and how the choice of a specific computational method affects the developer’s product liability. The review of legal obligations in this paper is based on German law and focuses on the requirements that must be met during the design and development process. KW - legal obligations KW - product liability KW - design of technical systems KW - optimization KW - resilience Y1 - 2018 SN - 1662-7482 U6 - https://doi.org/10.4028/www.scientific.net/AMM.885.240 VL - 885 IS - 885 SP - 240 EP - 252 PB - Trans Tech Publications CY - Bäch ER - TY - JOUR A1 - Altherr, Lena A1 - Leise, Philipp A1 - Pfetsch, Marc E. A1 - Schmitt, Andreas T1 - Algorithmic design and resilience assessment of energy efficient high-rise water supply systems JF - Applied Mechanics and Materials N2 - High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building. KW - MINLP KW - Buffering Capacity KW - Uncertainty KW - Water Supply Networks KW - Booster Stations Y1 - 2018 U6 - https://doi.org/10.4028/www.scientific.net/AMM.885.211 SN - 1662-7482 VL - 885 SP - 211 EP - 223 PB - Trans Tech Publications CY - Bäch 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 - 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 - https://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 - 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 - https://doi.org/10.1007/978-3-030-21803-4_91 SP - 916 EP - 925 PB - Springer CY - Cham ER - TY - CHAP A1 - Stenger, David A1 - Altherr, Lena A1 - Abel, Dirk T1 - Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead T2 - Operations Research Proceedings 2018 N2 - In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead. KW - Product family optimization KW - Mixed-integer nonlinear black-box optimization KW - Engineering optimization KW - Machine learning Y1 - 2019 SN - 978-3-030-18499-5 (Print) SN - 978-3-030-18500-8 (Online) U6 - https://doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham 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 - Joint International Resilience Conference 2020. Interconnected: Resilience Innovations for Sustainable Development Goals. 23 - 27 November, 2020, Singapore SP - 97 EP - 100 ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Resilience enhancement of critical infrastructure – graph-theoretical resilience analysis of the water distribution system in the German city of Darmstadt T2 - 14th WCEAM Proceedings N2 - 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. KW - Resilient infrastructure KW - Resilience assessment KW - Resilience metric graph theory KW - Water distribution system KW - Case study Y1 - 2020 SN - 978-3-030-64228-0 SN - 978-3-030-64227-3 U6 - https://doi.org/10.1007/978-3-030-64228-0_13 N1 - 14th WCEAM Proceedings. World Congress on Engineering Asset Management, 28-31 July 2019, Singapore Part of the Lecture Notes in Mechanical Engineering book series (LNME) SP - 137 EP - 149 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 - https://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 - Leise, Philipp A1 - Simon, Nicolai A1 - Altherr, Lena T1 - Comparison of Piecewise Linearization Techniques to Model Electric Motor Efficiency Maps: A Computational Study T2 - Operations Research Proceedings 2019 N2 - 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. KW - MINLP KW - Powertrain KW - Piecewise linearization KW - Efficiency optimization Y1 - 2020 SN - 978-3-030-48439-2 SN - 978-3-030-48438-5 U6 - https://doi.org/10.1007/978-3-030-48439-2_55 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 457 EP - 463 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 - https://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 - JOUR A1 - Müller, Tim M. A1 - Leise, Philipp A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Optimization and validation of pumping system design and operation for water supply in high-rise buildings JF - Optimization and Engineering N2 - The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs. KW - Technical Operations Research KW - MINLP KW - MILP KW - Experimental validation KW - Pumping systems Y1 - 2020 U6 - https://doi.org/10.1007/s11081-020-09553-4 SN - 1573-2924 VL - 2021 IS - 22 SP - 643 EP - 686 PB - Springer 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 - https://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 - 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 - https://doi.org/10.1080/0305215X.2021.1928660 SN - 0305-215X PB - Taylor & Francis CY - London ER - TY - CHAP A1 - Altherr, Lena A1 - Leise, Philipp T1 - Resilience as a concept for mastering uncertainty T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78353-2 U6 - https://doi.org/10.1007/978-3-030-78354-9 N1 - Unterkapitel 6.3.1 des Kapitels "Strategies for Mastering Uncertainty" SP - 412 EP - 417 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Leise, Philipp A1 - Pfetsch, Marc E. A1 - Schmitt, Andreas T1 - Optimal design of resilient technical systems on the example of water supply systems T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78356-3 N1 - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty" SP - 429 EP - 433 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena T1 - Experimental evaluation of resilience metrics in a fluid system T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78356-3 N1 - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty" SP - 442 EP - 447 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 - https://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 -