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  - Hüning, Felix
T1  - Sustainable changes beyond covid-19 for a second semester physics course for electrical engineering students
T2  - Blended Learning in Engineering Education: challenging, enlightening – and lasting?
N2  - 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.
Y1  - 2021
SN  - 978-2-87352-023-6
N1  - SEFI 49th Annual Conference
Technische Universität Berlin (online),
13 – 16 September 2021
SP  - 1405
EP  - 1409
ER  - 
TY  - CHAP
A1  - Ulmer, Jessica
A1  - Braun, Sebastian
A1  - Cheng, Chi-Tsun
A1  - Dowey, Steve
A1  - Wollert, Jörg
T1  - Adapting Augmented Reality Systems to the users’ needs using Gamification and error solving methods
T2  - Procedia CIRP
N2  - Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.
KW  - Augmented Reality
KW  - Adaptive Systems
KW  - Gamification
KW  - Error Recovery
Y1  - 2021
U6  - http://dx.doi.org/10.1016/j.procir.2021.11.024
SN  - 2212-8271
N1  - Part of special issue: 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0
VL  - 104
SP  - 140
EP  - 145
PB  - Elsevier
CY  - Amsterdam
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  - 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  - 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  - 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  - http://dx.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  - 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  - 
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  - Grundmann, Jan Thimo
A1  - Bauer, Waldemar
A1  - Boden, Ralf
A1  - Ceriotti, Matteo
A1  - Chand, Suditi
A1  - Cordero, Federico
A1  - Dachwald, Bernd
A1  - Dumont, Etienne
A1  - Grimm, Christian D.
A1  - Heiligers, Jeannette
A1  - Herčík, David
A1  - Hérique, Alain
A1  - Ho, Tra-Mi
A1  - Jahnke, Rico
A1  - Kofman, Wlodek
A1  - Lange, Caroline
A1  - Lichtenheldt, Roy
A1  - McInnes, Colin
A1  - Meß, Jan-Gerd
A1  - Mikschl, Tobias
A1  - Mikulz, Eugen
A1  - Montenegro, Sergio
A1  - Moore, Iain
A1  - Pelivan, Ivanka
A1  - Peloni, Alessandro
A1  - Plettemeier, Dirk
A1  - Quantius, Dominik
A1  - Reershemius, Siebo
A1  - Renger, Thomas
A1  - Riemann, Johannes
A1  - Rogez, Yves
A1  - Ruffer, Michael
A1  - Sasaki, Kaname
A1  - Schmitz, Nicole
A1  - Seboldt, Wolfgang
A1  - Seefeldt, Patric
A1  - Spietz, Peter
A1  - Spröwitz, Tom
A1  - Sznajder, Maciej
A1  - Tóth, Norbert
A1  - Vergaaij, Merel
A1  - Viavattene, Giulia
A1  - Wejmo, Elisabet
A1  - Wiedemann, Carsten
A1  - Wolff, Friederike
A1  - Ziach, Christian
T1  - Flights are ten a sail – Re-use and commonality in the design and system engineering of small spacecraft solar sail missions with modular hardware for responsive and adaptive exploration
T2  - 70th International Astronautical Congress (IAC)
KW  - system engineering
KW  - small solar system body characterisation
KW  - small spacecraft solar sail
KW  - small spacecraft asteroid lander
KW  - responsive space
Y1  - 2019
SN  - 9781713814856
N1  - 70th International Astronautical Congress (IAC), Washington D.C., United States, 21-25 October 2019
SP  - 1
EP  - 7
ER  - 
TY  - JOUR
A1  - Hein, Andreas M.
A1  - Eubanks, T. Marshall
A1  - Lingam, Manasvi
A1  - Hibberd, Adam
A1  - Fries, Dan
A1  - Schneider, Jean
A1  - Kervella, Pierre
A1  - Kennedy, Robert
A1  - Perakis, Nikolaos
A1  - Dachwald, Bernd
T1  - Interstellar now! Missions to explore nearby interstellar objects
JF  - Advances in Space Research
N2  - The recently discovered first hyperbolic objects passing through the Solar System, 1I/’Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects. In situ spacecraft exploration of these objects will allow the direct determination of both their structure and their chemical and isotopic composition, enabling an entirely new way of studying small bodies from outside our solar system. In this paper, we map various Interstellar Object classes to mission types, demonstrating that missions to a range of Interstellar Object classes are feasible, using existing or near-term technology. We describe flyby, rendezvous and sample return missions to interstellar objects, showing various ways to explore these bodies characterizing their surface, dynamics, structure and composition. Their direct exploration will constrain their formation and history, situating them within the dynamical and chemical evolution of the Galaxy. These mission types also provide the opportunity to explore solar system bodies and perform measurements in the far outer solar system.
KW  - Interstellar objects
KW  - Trajectories
KW  - Missions
Y1  - 2022
U6  - http://dx.doi.org/10.1016/j.asr.2021.06.052
SN  - 0273-1177
VL  - 69
IS  - 1
SP  - 402
EP  - 414
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Kezerashvili, Roman Ya
A1  - Dachwald, Bernd
T1  - Preface: Solar sailing: Concepts, technology, and missions II
JF  - Advances in Space Research
Y1  - 2021
U6  - http://dx.doi.org/10.1016/j.asr.2021.01.037
SN  - 0273-1177
VL  - 67
IS  - 9
SP  - 2559
EP  - 2560
PB  - Elsevier
CY  - Amsterdam
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  - JOUR
A1  - Spietz, Peter
A1  - Spröwitz, Tom
A1  - Seefeldt, Patric
A1  - Grundmann, Jan Thimo
A1  - Jahnke, Rico
A1  - Mikschl, Tobias
A1  - Mikulz, Eugen
A1  - Montenegro, Sergio
A1  - Reershemius, Siebo
A1  - Renger, Thomas
A1  - Ruffer, Michael
A1  - Sasaki, Kaname
A1  - Sznajder, Maciej
A1  - Tóth, Norbert
A1  - Ceriotti, Matteo
A1  - Dachwald, Bernd
A1  - Macdonald, Malcolm
A1  - McInnes, Colin
A1  - Seboldt, Wolfgang
A1  - Quantius, Dominik
A1  - Bauer, Waldemar
A1  - Wiedemann, Carsten
A1  - Grimm, Christian D.
A1  - Hercik, David
A1  - Ho, Tra-Mi
A1  - Lange, Caroline
A1  - Schmitz, Nicole
T1  - Paths not taken – The Gossamer roadmap’s other options
JF  - Advances in Space Research
KW  - Solar sail
KW  - Small spacecraft
KW  - DLR-ESTEC GOSSAMER roadmap for solar sailing
KW  - GOSSAMER-1
Y1  - 2021
U6  - http://dx.doi.org/10.1016/j.asr.2021.01.044
SN  - 0273-1177
VL  - 67
IS  - 9
SP  - 2912
EP  - 2956
PB  - Elsevier
CY  - Amsterdam
ER  -