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 - 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 - http://dx.doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham 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 - 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 - 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 - http://dx.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 - Stenger, David A1 - Altherr, Lena A1 - Müller, Tankred A1 - Pelz, Peter F. T1 - Product family design optimization using model-based engineering techniques T2 - Operations Research Proceedings 2017 N2 - Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products. Y1 - 2018 SN - 978-3-319-89919-0 U6 - http://dx.doi.org/10.1007/978-3-319-89920-6_66 SP - 495 EP - 502 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Dörig, Bastian A1 - Ederer, Thorsten A1 - Pelz, Peter Franz A1 - Pfetsch, Marc A1 - Wolf, Jan T1 - A mixed-integer nonlinear program for the design of gearboxes T2 - Operations Research Proceedings 2016 N2 - Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution. Y1 - 2017 SN - 978-3-319-55701-4 U6 - http://dx.doi.org/10.1007/978-3-319-55702-1_31 SP - 227 EP - 233 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Energy-Efficient design of a water supply system for skyscrapers by mixed-integer nonlinear programming T2 - Operations Research Proceedings 2017 N2 - The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design. KW - Engineering optimization KW - Global optimization KW - Energy efficiency KW - Water KW - Network Y1 - 2018 SN - 978-3-319-89919-0 U6 - http://dx.doi.org/10.1007/978-3-319-89920-6_63 PB - Springer CY - Cham ER - TY - CHAP A1 - Rausch, Lea A1 - Friesen, John A1 - Altherr, Lena A1 - Pelz, Peter F. ED - Kliewer, Natalia ED - Ehmke, Jan Fabian ED - Borndörfer, Ralf T1 - Using mixed-integer programming for the optimal design of water supply networks for slums T2 - Operations Research Proceedings 2017 N2 - 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. Y1 - 2018 SN - 978-3-319-89919-0 (Print) SN - 978-3-319-89920-6 (Online) U6 - http://dx.doi.org/10.1007/978-3-319-89920-6_68 N1 - International Conference of the German Operations Research Society (GOR), Freie Universiät Berlin, Germany, September 6-8, 2017. SP - 509 EP - 516 PB - Springer CY - Cham ER - TY - JOUR A1 - Lenz, Maximilian A1 - Kahmann, Stephanie Lucina A1 - Behbahani, Mehdi A1 - Pennig, Lenhard A1 - Hackl, Michael A1 - Leschinger, Tim A1 - Müller, Lars Peter A1 - Wegmann, Kilian T1 - Influence of rotator cuff preload on fracture configuration in proximal humerus fractures: a proof of concept for fracture simulation JF - Archives of Orthopaedic and Trauma Surgery N2 - Introduction In regard of surgical training, the reproducible simulation of life-like proximal humerus fractures in human cadaveric specimens is desirable. The aim of the present study was to develop a technique that allows simulation of realistic proximal humerus fractures and to analyse the influence of rotator cuff preload on the generated lesions in regards of fracture configuration. Materials and methods Ten cadaveric specimens (6 left, 4 right) were fractured using a custom-made drop-test bench, in two groups. Five specimens were fractured without rotator cuff preload, while the other five were fractured with the tendons of the rotator cuff preloaded with 2 kg each. The humeral shaft and the shortened scapula were potted. The humerus was positioned at 90° of abduction and 10° of internal rotation to simulate a fall on the elevated arm. In two specimens of each group, the emergence of the fractures was documented with high-speed video imaging. Pre-fracture radiographs were taken to evaluate the deltoid-tuberosity index as a measure of bone density. Post-fracture X-rays and CT scans were performed to define the exact fracture configurations. Neer’s classification was used to analyse the fractures. Results In all ten cadaveric specimens life-like proximal humerus fractures were achieved. Two III-part and three IV-part fractures resulted in each group. The preloading of the rotator cuff muscles had no further influence on the fracture configuration. High-speed videos of the fracture simulation revealed identical fracture mechanisms for both groups. We observed a two-step fracture mechanism, with initial impaction of the head segment against the glenoid followed by fracturing of the head and the tuberosities and then with further impaction of the shaft against the acromion, which lead to separation of the tuberosities. Conclusion A high energetic axial impulse can reliably induce realistic proximal humerus fractures in cadaveric specimens. The preload of the rotator cuff muscles had no influence on initial fracture configuration. Therefore, fracture simulation in the proximal humerus is less elaborate. Using the presented technique, pre-fractured specimens are available for real-life surgical education. KW - Proximal humerus fracture KW - Biomechanical simulation KW - Fracture configuration KW - Fracture simulation KW - Rotator cuff Y1 - 2022 U6 - http://dx.doi.org/10.1007/s00402-022-04471-9 SN - 1434-3916 PB - Springer CY - Berlin, Heidelberg ER -