@inproceedings{24011, author = {{Joy, Tintu David and Kullmer, Gunter and Risse, Lena}}, location = {{Hamburg}}, pages = {{207--216}}, title = {{{Vorhersage der Rissinitiierung in 3D-Strukturen mit ADAPCRACK3D}}}, volume = {{DVM-Bericht 252}}, year = {{2020}}, } @article{20372, abstract = {{A stepwise angular spectrum method (SASM) for curved interfaces is presented to calculate the wave propagation in planar lens-like integrated optical structures based on photonic slab waveguides. The method is derived and illustrated for an effective 2D setup first and then for 3D slab waveguide lenses. We employ slab waveguides of different thicknesses connected by curved surfaces to realize a lens-like structure. To simulate the wave propagation in 3D including reflection and scattering losses, the stepwise angular spectrum method is combined with full vectorial finite element computations for subproblems with lower complexity. Our SASM results show excellent agreement with rigorous numerical simulations of the full structures with a substantially lower computational effort and can be utilized for the simulation-based design and optimization of complex and large scale setups.}}, author = {{Ebers, Lena and Hammer, Manfred and Förstner, Jens}}, issn = {{1094-4087}}, journal = {{Optics Express}}, keywords = {{tet_topic_waveguides}}, number = {{24}}, pages = {{36361}}, title = {{{Light diffraction in slab waveguide lenses simulated with the stepwise angular spectrum method}}}, doi = {{10.1364/oe.409612}}, volume = {{28}}, year = {{2020}}, } @inproceedings{20512, author = {{Krüger, Stefan and Ali, Karim and Bodden, Eric}}, booktitle = {{International Symposium on Code Generation and Optimization (CGO)}}, pages = {{185--198}}, title = {{{CogniCrypt_GEN - Generating Code for the Secure Usage of Crypto APIs}}}, year = {{2020}}, } @inproceedings{20854, author = {{Camberg, Alan Adam and Tröster, Thomas}}, location = {{Seoul, South Korea}}, title = {{{A simplified method for the evaluation of the layer compression test using one 3D digital image correlation system and considering the material anisotropy by the equibiaxial Lankford parameter}}}, doi = {{10.1088/1757-899X/967/1/012077}}, year = {{2020}}, } @inbook{18014, author = {{El Mesaoudi-Paul, Adil and Weiß, Dimitri and Bengs, Viktor and Hüllermeier, Eyke and Tierney, Kevin}}, booktitle = {{Learning and Intelligent Optimization. LION 2020.}}, isbn = {{9783030535513}}, issn = {{0302-9743}}, pages = {{216 -- 232}}, publisher = {{Springer}}, title = {{{Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach}}}, doi = {{10.1007/978-3-030-53552-0_22}}, volume = {{12096}}, year = {{2020}}, } @inproceedings{18249, abstract = {{Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration. Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the configuration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product con-figuration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (e.g. tabletop, ta-ble legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be configured out of these parts, are stored in a feature model. At runtime, this feature model can be used to configure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The benefits of this approach are demonstrated by a case study of configuring modular kitchens with the help of a prototypical mobile-based implementation.}}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Schmidt, Eugen and Engels, Gregor}}, booktitle = {{Human-Centered Software Engineering. HCSE 2020}}, editor = {{Bernhaupt, Regina and Ardito, Carmelo and Sauer, Stefan}}, keywords = {{Product Configuration, Augmented Reality, Runtime Adaptation, Dynamic Software Product Lines}}, location = {{Eindhoven}}, publisher = {{Springer}}, title = {{{Model-based Product Configuration in Augmented Reality Applications}}}, doi = {{10.1007/978-3-030-64266-2_5}}, volume = {{12481}}, year = {{2020}}, } @article{22963, author = {{Biemelt, Patrick and Gausemeier, Sandra and Trächtler, Ansgar}}, journal = {{International Journal On Advances in Systems and Measurements}}, number = {{3 & 4}}, pages = {{203--219}}, title = {{{Design and Objective Evaluation of Filter- and Optimization-based Motion Cueing Strategies for a Hybrid Kinematics Driving Simulator with 5 Degrees of Freedom}}}, volume = {{13}}, year = {{2020}}, } @inproceedings{16939, author = {{Triebus, Marcel and Tröster, Thomas}}, booktitle = {{Proceedings 4th International Conference Hybrid Materials & Structures}}, location = {{Web-Conference}}, title = {{{A Holistic Approach to Optimization-Based Design of Hybrid Materials}}}, year = {{2020}}, } @inproceedings{16968, abstract = {{In this work, we initiate the research about the Gathering problem for robots with limited viewing range in the three-dimensional Euclidean space. In the Gathering problem, a set of initially scattered robots is required to gather at the same position. The robots' capabilities are very restricted -- they do not agree on any coordinate system or compass, have a limited viewing range, have no memory of the past and cannot communicate. We study the problem in two different time models, in FSYNC (fully synchronized discrete rounds) and the continuous time model. For FSYNC, we introduce the 3D-Go-To-The-Center-strategy and prove a runtime of $\Theta(n^2)$ that matches the currently best runtime bound for the same model in the Euclidean plane [SPAA'11]. Our main result is the generalization of contracting strategies (continuous time) from [Algosensors'17] to three dimensions. In contracting strategies, every robot that is located on the global convex hull of all robots' positions moves with full speed towards the inside of the convex hull. We prove a runtime bound of $O(\Delta \cdot n^{3/2})$ for any three-dimensional contracting strategy, where $\Delta$ denotes the diameter of the initial configuration. This comes up to a factor of $\sqrt{n}$ close to the lower bound of $\Omega (\Delta \cdot n)$ which is already true in two dimensions. In general, it might be hard for robots with limited viewing range to decide whether they are located on the global convex hull and which movement maintains the connectivity of the swarm, rendering the design of concrete contracting strategies a challenging task. We prove that the continuous variant of 3D-Go-To-The-Center is contracting and keeps the swarm connected. Moreover, we give a simple design criterion for three-dimensional contracting strategies that maintains the connectivity of the swarm and introduce an exemplary strategy based on this criterion.}}, author = {{Braun, Michael and Castenow, Jannik and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 27th Conference on Structural Information and Communication Complexity (SIROCCO)}}, location = {{Paderborn}}, publisher = {{Springer}}, title = {{{Local Gathering of Mobile Robots in Three Dimensions}}}, doi = {{10.1007/978-3-030-54921-3_4}}, year = {{2020}}, } @techreport{17019, abstract = {{The scientific impact of research papers is multi-dimensional and can be determined quantitatively by means of citation analysis and qualitatively by means of content analysis. Accounting for the widely acknowledged limitations of pure citation analysis, we adopt a knowledge-based perspective on scientific impact to develop a methodology for content-based citation analysis which allows determining how papers have enabled knowledge development in subsequent research (knowledge impact). As knowledge development differs between research genres, we develop a new knowledgebased citation analysis methodology for the genre of standalone literature reviews (LRs). We apply the suggested methodology to the IS business value domain by manually coding 22 LRs and 1,228 citing papers (CPs) and show that the results challenge the assumption that citations indicate knowledge impact. We derive implications for distinguishing knowledge impact from citation impact in the LR genre. Finally, we develop recommendations for authors of LRs, scientific evaluation committees and editorial boards of journals how to apply and benefit from the suggested methodology, and we discuss its efficiency and automatization.}}, author = {{Schryen, Guido and Wagner, Gerit and Benlian, Alexander}}, keywords = {{Scientific impact, knowledge impact, content-based citation analysis, methodology}}, title = {{{Distinguishing Knowledge Impact from Citation Impact: A Methodology for Analysing Knowledge Impact for the Literature Review Genre}}}, year = {{2020}}, } @inproceedings{17082, abstract = {{Data-parallel applications run on cluster of servers in a datacenter and their communication triggers correlated resource demand on multiple links that can be abstracted as coflow. They often desire predictable network performance, which can be passed to network via coflow abstraction for application-aware network scheduling. In this paper, we propose a heuristic and an optimization algorithm for predictable network performance such that they guarantee coflows completion within their deadlines. The algorithms also ensure high network utilization, i.e., it's work-conserving, and avoids starvation of coflows. We evaluate both algorithms via trace-driven simulation and show that they admit 1.1x more coflows than the Varys scheme while meeting their deadlines.}}, author = {{Hasnain, Asif and Karl, Holger}}, booktitle = {{2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)}}, keywords = {{Coflow, Scheduling, Deadlines, Data centers}}, location = {{Melbourne, Australia}}, publisher = {{IEEE Computer Society}}, title = {{{Coflow Scheduling with Performance Guarantees for Data Center Applications}}}, doi = {{https://doi.org/10.1109/CCGrid49817.2020.00010}}, year = {{2020}}, } @article{10596, abstract = {{Multi-objective optimization is an active field of research that has many applications. Owing to its success and because decision-making processes are becoming more and more complex, there is a recent trend for incorporating many objectives into such problems. The challenge with such problems, however, is that the dimensions of the solution sets—the so-called Pareto sets and fronts—grow with the number of objectives. It is thus no longer possible to compute or to approximate the entire solution set of a given problem that contains many (e.g. more than three) objectives. On the other hand, the computation of single solutions (e.g. via scalarization methods) leads to unsatisfying results in many cases, even if user preferences are incorporated. In this article, the Pareto Explorer tool is presented—a global/local exploration tool for the treatment of many-objective optimization problems (MaOPs). In the first step, a solution of the problem is computed via a global search algorithm that ideally already includes user preferences. In the second step, a local search along the Pareto set/front of the given MaOP is performed in user specified directions. For this, several continuation-like procedures are proposed that can incorporate preferences defined in decision, objective, or in weight space. The applicability and usefulness of Pareto Explorer is demonstrated on benchmark problems as well as on an application from industrial laundry design.}}, author = {{Schütze, Oliver and Cuate, Oliver and Martín, Adanay and Peitz, Sebastian and Dellnitz, Michael}}, issn = {{0305-215X}}, journal = {{Engineering Optimization}}, number = {{5}}, pages = {{832--855}}, title = {{{Pareto Explorer: a global/local exploration tool for many-objective optimization problems}}}, doi = {{10.1080/0305215x.2019.1617286}}, volume = {{52}}, year = {{2020}}, } @article{15628, abstract = {{The three-dimensional (3D) crystal structures of the GAF3 domain of cyanobacteriochrome Slr1393 (Synechocystis PCC6803) carrying a phycocyanobilin chromophore could be solved in both 15-Z dark-adapted state, Pr, λmax = 649 nm, and 15-E photoproduct, Pg, λmax = 536 nm (resolution, 1.6 and 1.86 Å, respectively). The structural data allowed identifying the large spectral shift of the Pr-to-Pg conversion as resulting from an out-of-plane rotation of the chromophore’s peripheral rings and an outward movement of a short helix formed from a formerly unstructured loop. In addition, a third structure (2.1-Å resolution) starting from the photoproduct crystals allowed identification of elements that regulate the absorption maxima. In this peculiar form, generated during X-ray exposition, protein and chromophore conformation still resemble the photoproduct state, except for the D-ring already in 15-Z configuration and tilted out of plane akin the dark state. Due to its formation from the photoproduct, it might be considered an early conformational change initiating the parental state-recovering photocycle. The high quality and the distinct features of the three forms allowed for applying quantum-chemical calculations in the framework of multiscale modeling to rationalize the absorption maxima changes. A systematic analysis of the PCB chromophore in the presence and absence of the protein environment showed that the direct electrostatic effect is negligible on the spectral tuning. However, the protein forces the outer pyrrole rings of the chromophore to deviate from coplanarity, which is identified as the dominating factor for the color regulation.}}, author = {{Xu, Xiuling and Port, Astrid and Wiebeler, Christian and Zhao, Kai-Hong and Schapiro, Igor and Gärtner, Wolfgang}}, issn = {{0027-8424}}, journal = {{Proceedings of the National Academy of Sciences}}, title = {{{Structural Elements Regulating the Photochromicity in a Cyanobacteriochrome}}}, doi = {{10.1073/pnas.1910208117}}, year = {{2020}}, } @article{15022, author = {{Schryen, Guido}}, journal = {{European Journal of Operational Research}}, number = {{1}}, pages = {{1 -- 18}}, publisher = {{Elsevier}}, title = {{{Parallel computational optimization in operations research: A new integrative framework, literature review and research directions}}}, volume = {{287}}, year = {{2020}}, } @inproceedings{16213, abstract = {{Automated synthesis of approximate circuits via functional approximations is of prominent importance to provide efficiency in energy, runtime, and chip area required to execute an application. Approximate circuits are usually obtained either through analytical approximation methods leveraging approximate transformations such as bit-width scaling or via iterative search-based optimization methods when a library of approximate components, e.g., approximate adders and multipliers, is available. For the latter, exploring the extremely large design space is challenging in terms of both computations and quality of results. While the combination of both methods can create more room for further approximations, the \textit{Design Space Exploration}~(DSE) becomes a crucial issue. In this paper, we present such a hybrid synthesis methodology that applies a low-cost analytical method followed by parallel stochastic search-based optimization. We address the DSE challenge through efficient pruning of the design space and skipping unnecessary expensive testing and/or verification steps. The experimental results reveal up to 10.57x area savings in comparison with both purely analytical or search-based approaches. }}, author = {{Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}}, booktitle = {{Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020}}, location = {{Beijing, China}}, pages = {{421--426}}, publisher = {{ACM}}, title = {{{A Hybrid Synthesis Methodology for Approximate Circuits}}}, doi = {{10.1145/3386263.3406952}}, year = {{2020}}, } @inproceedings{16219, abstract = {{Network function virtualization (NFV) proposes to replace physical middleboxes with more flexible virtual network functions (VNFs). To dynamically adjust to everchanging traffic demands, VNFs have to be instantiated and their allocated resources have to be adjusted on demand. Deciding the amount of allocated resources is non-trivial. Existing optimization approaches often assume fixed resource requirements for each VNF instance. However, this can easily lead to either waste of resources or bad service quality if too many or too few resources are allocated. To solve this problem, we train machine learning models on real VNF data, containing measurements of performance and resource requirements. For each VNF, the trained models can then accurately predict the required resources to handle a certain traffic load. We integrate these machine learning models into an algorithm for joint VNF scaling and placement and evaluate their impact on resulting VNF placements. Our evaluation based on real-world data shows that using suitable machine learning models effectively avoids over- and underallocation of resources, leading to up to 12 times lower resource consumption and better service quality with up to 4.5 times lower total delay than using standard fixed resource allocation.}}, author = {{Schneider, Stefan Balthasar and Satheeschandran, Narayanan Puthenpurayil and Peuster, Manuel and Karl, Holger}}, booktitle = {{IEEE Conference on Network Softwarization (NetSoft)}}, location = {{Ghent, Belgium}}, publisher = {{IEEE}}, title = {{{Machine Learning for Dynamic Resource Allocation in Network Function Virtualization}}}, year = {{2020}}, } @inbook{16289, abstract = {{In the development of model predictive controllers for PDE-constrained problems, the use of reduced order models is essential to enable real-time applicability. Besides local linearization approaches, proper orthogonal decomposition (POD) has been most widely used in the past in order to derive such models. Due to the huge advances concerning both theory as well as the numerical approximation, a very promising alternative based on the Koopman operator has recently emerged. In this chapter, we present two control strategies for model predictive control of nonlinear PDEs using data-efficient approximations of the Koopman operator. In the first one, the dynamic control system is replaced by a small number of autonomous systems with different yet constant inputs. The control problem is consequently transformed into a switching problem. In the second approach, a bilinear surrogate model is obtained via a convex combination of these autonomous systems. Using a recent convergence result for extended dynamic mode decomposition (EDMD), convergence of the reduced objective function can be shown. We study the properties of these two strategies with respect to solution quality, data requirements, and complexity of the resulting optimization problem using the 1-dimensional Burgers equation and the 2-dimensional Navier–Stokes equations as examples. Finally, an extension for online adaptivity is presented.}}, author = {{Peitz, Sebastian and Klus, Stefan}}, booktitle = {{Lecture Notes in Control and Information Sciences}}, isbn = {{9783030357122}}, issn = {{0170-8643}}, pages = {{257--282}}, publisher = {{Springer}}, title = {{{Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator}}}, doi = {{10.1007/978-3-030-35713-9_10}}, volume = {{484}}, year = {{2020}}, } @inproceedings{29939, abstract = {{In this paper, a full-bridge modular multilevel converter (MMC) and two half-bridge-based MMCs are evaluated for high-current low-voltage e.g. 100 - 400V DC-applications such as electrolysis, arc welding or datacenters with DC-power distribution. Usually, modular multilevel converters are used in high-voltage DC-applications (HVDC) in the multiple kV-range, but to meet the needs of a high-current demand at low output voltage levels, the modular converter concept requires adaptations. In the proposed concept, the MMC is used to step-down the three-phase medium-voltage of 10kV, and provide up to 1 MW to the load. Therefore, each module is extended by an LLC resonant converter to adapt to the specific electrolyzers DC-voltage range of 142 - 220V and to provide galvanic isolation. The six-arm MMC converter with half-bridge modules can be simplified and optimized by removing three arms, and thus halving the number of modules. In addition, the module voltage ripple and capacitor losses are decreased by 22% and 30% respectively. By rearranging the components of the half-bridge MMC to build a MMC consisting of grid-side full-bridge modules, the voltage ripple is further reduced by 78% and capacitor losses by 64%, while ensuring identical costs and volume for all MMCs. Finally, the LLC resonant converter is designed for the most efficient full-bridge MMC. The LLC can not operate at resonance with a fixed nominal module voltage of 770V because the output voltage is varying between 142 - 220V. By decreasing the module voltage down to 600V, additional points of operation can be operated in resonance, and the remaining are closer to resonance. The option to decrease the module voltage down to 600V, increases the number of required modules per arm from 12 to 15, which requires to balance the losses of the LLCs and the grid-side stages.}}, author = {{Unruh, Roland and Schafmeister, Frank and Böcker, Joachim}}, booktitle = {{2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe)}}, keywords = {{Multilevel converters, Resonant converter, High voltage power converters, ZVS Converters, Combination MMC LLC}}, location = {{Lyon, France}}, publisher = {{IEEE}}, title = {{{Evaluation of MMCs for High-Power Low-Voltage DC-Applications in Combination with the Module LLC-Design}}}, doi = {{10.23919/epe20ecceeurope43536.2020.9215687}}, year = {{2020}}, } @unpublished{21623, abstract = {{Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in conventional electricity grids and for providing power supply in remote areas. Modern MSGs are largely driven by power electronic converters due to their high efficiency and flexibility. Nevertheless, controlling MSGs is a challenging task due to highest requirements on energy availability, safety and voltage quality within a wide range of different MSG topologies. This results in a high demand for comprehensive testing of new control concepts during their development phase and comparisons with the state of the art in order to ensure their feasibility. This applies in particular to data-driven control approaches from the field of reinforcement learning (RL), whose stability and operating behavior can hardly be evaluated a priori. Therefore, the OpenModelica Microgrid Gym (OMG) package, an open-source software toolbox for the simulation and control optimization of MSGs, is proposed. It is capable of modeling and simulating arbitrary MSG topologies and offers a Python-based interface for plug \& play controller testing. In particular, the standardized OpenAI Gym interface allows for easy RL-based controller integration. Besides the presentation of the OMG toolbox, application examples are highlighted including safe Bayesian optimization for low-level controller tuning.}}, author = {{Bode, Henrik and Heid, Stefan and Weber, Daniel and Hüllermeier, Eyke and Wallscheid, Oliver}}, booktitle = {{arXiv:2005.04869}}, title = {{{Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control}}}, year = {{2020}}, } @article{16297, abstract = {{In real-world problems, uncertainties (e.g., errors in the measurement, precision errors) often lead to poor performance of numerical algorithms when not explicitly taken into account. This is also the case for control problems, where optimal solutions can degrade in quality or even become infeasible. Thus, there is the need to design methods that can handle uncertainty. In this work, we consider nonlinear multi-objective optimal control problems with uncertainty on the initial conditions, and in particular their incorporation into a feedback loop via model predictive control (MPC). In multi-objective optimal control, an optimal compromise between multiple conflicting criteria has to be found. For such problems, not much has been reported in terms of uncertainties. To address this problem class, we design an offline/online framework to compute an approximation of efficient control strategies. This approach is closely related to explicit MPC for nonlinear systems, where the potentially expensive optimization problem is solved in an offline phase in order to enable fast solutions in the online phase. In order to reduce the numerical cost of the offline phase, we exploit symmetries in the control problems. Furthermore, in order to ensure optimality of the solutions, we include an additional online optimization step, which is considerably cheaper than the original multi-objective optimization problem. We test our framework on a car maneuvering problem where safety and speed are the objectives. The multi-objective framework allows for online adaptations of the desired objective. Alternatively, an automatic scalarizing procedure yields very efficient feedback controls. Our results show that the method is capable of designing driving strategies that deal better with uncertainties in the initial conditions, which translates into potentially safer and faster driving strategies.}}, author = {{Hernández Castellanos, Carlos Ignacio and Ober-Blöbaum, Sina and Peitz, Sebastian}}, journal = {{International Journal of Robust and Nonlinear Control}}, pages = {{7593--7618}}, title = {{{Explicit Multi-objective Model Predictive Control for Nonlinear Systems Under Uncertainty}}}, doi = {{10.1002/rnc.5197}}, volume = {{30(17)}}, year = {{2020}}, }