@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} } @incollection{LeiseAltherrSimonetal.2019, author = {Leise, Philipp and Altherr, Lena and Simon, Nicolai and Pelz, Peter F.}, title = {Finding global-optimal gearbox designs for battery electric vehicles}, series = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, booktitle = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-21802-7}, doi = {10.1007/978-3-030-21803-4_91}, pages = {916 -- 925}, year = {2019}, abstract = {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.}, language = {en} } @incollection{StengerAltherrAbel2019, author = {Stenger, David and Altherr, Lena and Abel, Dirk}, title = {Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead}, series = {Operations Research Proceedings 2018}, booktitle = {Operations Research Proceedings 2018}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-18499-5 (Print)}, doi = {10.1007/978-3-030-18500-8_47}, pages = {379 -- 385}, year = {2019}, abstract = {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.}, language = {en} } @article{RauschFriesenAltherretal.2018, author = {Rausch, Lea and Friesen, John and Altherr, Lena and Meck, Marvin and Pelz, Peter F.}, title = {A holistic concept to design optimal water supply infrastructures for informal settlements using remote sensing data}, series = {Remote Sensing}, volume = {10}, journal = {Remote Sensing}, number = {2}, publisher = {MDPI}, address = {Basel}, isbn = {2072-4292}, doi = {10.3390/rs10020216}, pages = {1 -- 23}, year = {2018}, abstract = {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.}, language = {en} } @article{AltherrEdererPfetschetal.2018, author = {Altherr, Lena and Ederer, Thorsten and Pfetsch, Marc E. and Pelz, Peter F.}, title = {Maschinelles Design eines optimalen Getriebes}, series = {ATZ - Automobiltechnische Zeitschrift}, volume = {120}, journal = {ATZ - Automobiltechnische Zeitschrift}, number = {10}, publisher = {Springer Nature}, address = {Cham}, isbn = {2192-8800}, doi = {10.1007/s35148-018-0131-3}, pages = {72 -- 77}, year = {2018}, abstract = {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, k{\"o}nnen leicht innovative und vor allem kostenminimale L{\"o}sungen {\"u}bersehen werden. Im Rahmen eines Forschungsprojekts hat die TU Darmstadt spezielle Optimierungsmethoden angewendet, um auch bei großen L{\"o}sungsr{\"a}umen zielsicher ein f{\"u}r die individuellen Zielstellungen optimales Layout zu finden.}, language = {de} } @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} } @article{AltherrJoggerstLeiseetal.2018, author = {Altherr, Lena and Joggerst, Laura and Leise, Philipp and Pfetsch, Marc E. and Schmitt, Andreas and Wendt, Janine}, title = {On obligations in the development process of resilient systems with algorithmic design methods}, series = {Applied Mechanics and Materials}, volume = {885}, journal = {Applied Mechanics and Materials}, number = {885}, publisher = {Trans Tech Publications}, address = {B{\"a}ch}, isbn = {1662-7482}, doi = {10.4028/www.scientific.net/AMM.885.240}, pages = {240 -- 252}, year = {2018}, abstract = {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.}, language = {en} } @article{SunAltherrPeietal.2018, author = {Sun, Hui and Altherr, Lena and Pei, Ji and Pelz, Peter F. and Yuan, Shouqi}, title = {Optimal booster station design and operation under uncertain load}, series = {Applied Mechanics and Materials}, volume = {885}, journal = {Applied Mechanics and Materials}, publisher = {Trans Tech Publications}, address = {B{\"a}ch}, issn = {1662-7482}, doi = {10.4028/www.scientific.net/AMM.885.102}, pages = {102 -- 115}, year = {2018}, abstract = {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}, language = {en} } @incollection{MuellerAltherrAholaetal.2018, author = {M{\"u}ller, Tim M. and Altherr, Lena and Ahola, Marja and Schabel, Samuel and Pelz, Peter F.}, title = {Optimizing pressure screen systems in paper recycling: optimal system layout, component selection and operation}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-18499-5}, doi = {10.1007/978-3-030-18500-8_44}, pages = {355 -- 361}, year = {2018}, abstract = {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.}, language = {en} } @inproceedings{Huening2021, author = {H{\"u}ning, Felix}, title = {Sustainable changes beyond covid-19 for a second semester physics course for electrical engineering students}, series = {Blended Learning in Engineering Education: challenging, enlightening - and lasting?}, booktitle = {Blended Learning in Engineering Education: challenging, enlightening - and lasting?}, isbn = {978-2-87352-023-6}, pages = {1405 -- 1409}, year = {2021}, abstract = {The course Physics for Electrical Engineering is part of the curriculum of the bachelor program Electrical Engineering at University of Applied Science Aachen. Before covid-19 the course was conducted in a rather traditional way with all parts (lecture, exercise and lab) face-to-face. This teaching approach changed fundamentally within a week when the covid-19 limitations forced all courses to distance learning. All parts of the course were transformed to pure distance learning including synchronous and asynchronous parts for the lecture, live online-sessions for the exercises and self-paced labs at home. Using these methods, the course was able to impart the required knowledge and competencies. Taking the teacher's observations of the student's learning behaviour and engagement, the formal and informal feedback of the students and the results of the exams into account, the new methods are evaluated with respect to effectiveness, sustainability and suitability for competence transfer. Based on this analysis strong and weak points of the concept and countermeasures to solve the weak points were identified. The analysis further leads to a sustainable teaching approach combining synchronous and asynchronous parts with self-paced learning times that can be used in a very flexible manner for different learning scenarios, pure online, hybrid (mixture of online and presence times) and pure presence teaching.}, language = {en} }