@inproceedings{30003, author = {{Chudalla, Nick and Meschut, Gerson and Bartley, Aurélie and Wibbeke, Tim Michael}}, booktitle = {{22. Kolloquium: Gemeinsame Forschung in der Klebtechnik}}, title = {{{Analyse des Versagensverhaltens geklebter Stahl-Verbindungen beim werkstoffschonenden Entfügen in der Karosserieinstandsetzung}}}, year = {{2022}}, } @inproceedings{30222, author = {{Striewe, Marius and Meschut, Gerson and Schmelzle, Lars and Mergheim, Julia and Possart, Gunnar and Steinmann, Paul}}, booktitle = {{22. Kolloquium: Gemeinsame Forschung in der Klebtechnik}}, title = {{{Experimentelle und numerische Untersuchung des Einflusses variabler Betriebstemperaturen auf das Trag- und Versagensverhalten struktureller Klebverbindungen unter Crashbelastung}}}, year = {{2022}}, } @inbook{16296, abstract = {{Multiobjective optimization plays an increasingly important role in modern applications, where several objectives are often of equal importance. The task in multiobjective optimization and multiobjective optimal control is therefore to compute the set of optimal compromises (the Pareto set) between the conflicting objectives. Since the Pareto set generally consists of an infinite number of solutions, the computational effort can quickly become challenging which is particularly problematic when the objectives are costly to evaluate as is the case for models governed by partial differential equations (PDEs). To decrease the numerical effort to an affordable amount, surrogate models can be used to replace the expensive PDE evaluations. Existing multiobjective optimization methods using model reduction are limited either to low parameter dimensions or to few (ideally two) objectives. In this article, we present a combination of the reduced basis model reduction method with a continuation approach using inexact gradients. The resulting approach can handle an arbitrary number of objectives while yielding a significant reduction in computing time.}}, author = {{Banholzer, Stefan and Gebken, Bennet and Dellnitz, Michael and Peitz, Sebastian and Volkwein, Stefan}}, booktitle = {{Non-Smooth and Complementarity-Based Distributed Parameter Systems}}, editor = {{Michael, Hintermüller and Roland, Herzog and Christian, Kanzow and Michael, Ulbrich and Stefan, Ulbrich}}, isbn = {{978-3-030-79392-0}}, pages = {{43--76}}, publisher = {{Springer}}, title = {{{ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation}}}, doi = {{10.1007/978-3-030-79393-7_3}}, year = {{2022}}, } @inproceedings{30347, author = {{Schafmeister, Frank}}, booktitle = {{International Conference on Electric & Electronic in Hybrid and Electric Vehicles and Electric Energy Management (EEHE),}}, location = {{Bamberg, Germany}}, title = {{{Compensation of LF Common-Mode Noise by the internal DC/DC-Stage for transformerless On-Board Chargers at Three- and Single-Phase Operation}}}, year = {{2022}}, } @inproceedings{30349, author = {{Förster, Nikolas and Rehlaender, Philipp and Wallscheid, Oliver and Schafmeister, Frank and Böcker, Joachim}}, booktitle = {{Proc. 37th IEEE Applied Power Electronics Conference (APEC)}}, location = {{Houston, TX, USA}}, publisher = {{IEEE}}, title = {{{An Open-Source Transistor Database and Toolbox as an Unified Software Engineering Tool for Managing and Evaluating Power Transistors}}}, year = {{2022}}, } @inproceedings{30350, author = {{Keuck, Lukas and Schafmeister, Frank and Böcker, Joachim}}, booktitle = {{Proc. IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management (PCIM)}}, location = {{Nuremberg, Germany}}, publisher = {{IEEE}}, title = {{{Robust Hysteresis Control for LLC Resonant Converters Using a Fully Isolated Measurement Scheme}}}, year = {{2022}}, } @article{30861, abstract = {{AbstractWe consider the problem of maximization of metabolite production in bacterial cells formulated as a dynamical optimal control problem (DOCP). According to Pontryagin’s maximum principle, optimal solutions are concatenations of singular and bang arcs and exhibit the chattering or Fuller phenomenon, which is problematic for applications. To avoid chattering, we introduce a reduced model which is still biologically relevant and retains the important structural features of the original problem. Using a combination of analytical and numerical methods, we show that the singular arc is dominant in the studied DOCPs and exhibits the turnpike property. This property is further used in order to design simple and realistic suboptimal control strategies.}}, author = {{Caillau, Jean-Baptiste and Djema, Walid and Gouzé, Jean-Luc and Maslovskaya, Sofya and Pomet, Jean-Baptiste}}, issn = {{0022-3239}}, journal = {{Journal of Optimization Theory and Applications}}, keywords = {{Applied Mathematics, Management Science and Operations Research, Control and Optimization}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Turnpike Property in Optimal Microbial Metabolite Production}}}, doi = {{10.1007/s10957-022-02023-0}}, year = {{2022}}, } @article{30923, abstract = {{Additive manufacturing (AM) processes are not solely used where maximum design freedom meets low lot sizes. Direct microstructure design and topology optimization can be realized concomitantly during processing by adjusting the geometry, the material composition, and the solidification behavior of the material considered. However, when complex specific requirements have to be met, a targeted part design is highly challenging. In the field of biodegradable implant surgery, a cytocompatible material of an application-adapted shape has to be characterized by a specific degradation behavior and reliably predictable mechanical properties. For instance, small amounts of oxides can have a significant effect on microstructural development, thus likewise affecting the strength and corrosion behavior of the processed material. In the present study, biocompatible pure Fe was processed using electron powder bed fusion (E-PBF). Two different modifications of the Fe were processed by incorporating Fe oxide and Ce oxide in different proportions in order to assess their impact on the microstructural evolution, the mechanical response and the corrosion behavior. The quasistatic mechanical and chemical properties were analyzed and correlated with the final microstructural appearance.}}, author = {{Torrent, Christof J. J. and Krooß, Philipp and Huang, Jingyuan and Voigt, Markus and Ebbert, Christoph and Knust, Steffen and Grundmeier, Guido and Niendorf, Thomas}}, issn = {{2674-063X}}, journal = {{Alloys}}, number = {{1}}, pages = {{31--53}}, publisher = {{MDPI AG}}, title = {{{Oxide Modified Iron in Electron Beam Powder Bed Fusion—From Processability to Corrosion Properties}}}, doi = {{10.3390/alloys1010004}}, volume = {{1}}, year = {{2022}}, } @inproceedings{30004, author = {{Chudalla, Nick and Teutenberg, Dominik and Meschut, Gerson and Schneider, Miriam and Smart, Dominik}}, booktitle = {{22. Kolloquium: Gemeinsame Forschung in der Klebtechnik}}, title = {{{Systematisierung einer rechnergestützten Auswertemethode zur Versagensanalyse geklebter Verbindungen }}}, year = {{2022}}, } @article{32234, author = {{Wojciechowski, M}}, issn = {{2352-3409}}, journal = {{Data Brief}}, pages = {{108318}}, title = {{{Dataset for random uniform distributions of 2D circles and 3D spheres.}}}, volume = {{43}}, year = {{2022}}, } @article{32087, abstract = {{ Agility, a key component of team ball sports, describes an athlete´s ability to move fast in response to changing environments. While agility requires basic cognitive functions like processing speed, it also requires more complex cognitive processes like working memory and inhibition. Yet, most agility tests restrict an assessment of cognitive processes to simple reactive times that lack ecological validity. Our aim in this study was to assess agility performance by means of total time on two agility tests with matched motor demands but with both low and high cognitive demands. We tested 22 female team athletes on SpeedCourt, using a simple agility test (SAT) that measured only processing speed and a complex agility test (CAT) that required working memory and inhibition. We found excellent to good reliability for both our SAT (ICC = .79) and CAT (ICC =.70). Lower agility performance on the CAT was associated with increased agility total time and split times ( p < .05). These results demonstrated that agility performance depends on the complexity of cognitive demands. There may be interference-effects between motor and cognitive performances, reducing speed when environmental information becomes more complex. Future studies should consider agility training models that implement complex cognitive stimuli to challenge athletes according to competitive demands. This will also allow scientists and practitioners to tailor tests to talent identification, performance development and injury rehabilitation. }}, author = {{Büchel, Daniel and Gokeler, Alli and Heuvelmans, Pieter and Baumeister, Jochen}}, issn = {{0031-5125}}, journal = {{Perceptual and Motor Skills}}, keywords = {{Sensory Systems, Experimental and Cognitive Psychology}}, publisher = {{SAGE Publications}}, title = {{{Increased Cognitive Demands Affect Agility Performance in Female Athletes - Implications for Testing and Training of Agility in Team Ball Sports}}}, doi = {{10.1177/00315125221108698}}, year = {{2022}}, } @unpublished{30790, abstract = {{Iterative distributed optimization algorithms involve multiple agents that communicate with each other, over time, in order to minimize/maximize a global objective. In the presence of unreliable communication networks, the Age-of-Information (AoI), which measures the freshness of data received, may be large and hence hinder algorithmic convergence. In this paper, we study the convergence of general distributed gradient-based optimization algorithms in the presence of communication that neither happens periodically nor at stochastically independent points in time. We show that convergence is guaranteed provided the random variables associated with the AoI processes are stochastically dominated by a random variable with finite first moment. This improves on previous requirements of boundedness of more than the first moment. We then introduce stochastically strongly connected (SSC) networks, a new stochastic form of strong connectedness for time-varying networks. We show: If for any $p \ge0$ the processes that describe the success of communication between agents in a SSC network are $\alpha$-mixing with $n^{p-1}\alpha(n)$ summable, then the associated AoI processes are stochastically dominated by a random variable with finite $p$-th moment. In combination with our first contribution, this implies that distributed stochastic gradient descend converges in the presence of AoI, if $\alpha(n)$ is summable.}}, author = {{Redder, Adrian and Ramaswamy, Arunselvan and Karl, Holger}}, booktitle = {{arXiv:2201.11343}}, title = {{{Distributed gradient-based optimization in the presence of dependent aperiodic communication}}}, year = {{2022}}, } @inproceedings{31806, abstract = {{The creation of an RDF knowledge graph for a particular application commonly involves a pipeline of tools that transform a set ofinput data sources into an RDF knowledge graph in a process called dataset augmentation. The components of such augmentation pipelines often require extensive configuration to lead to satisfactory results. Thus, non-experts are often unable to use them. Wepresent an efficient supervised algorithm based on genetic programming for learning knowledge graph augmentation pipelines of arbitrary length. Our approach uses multi-expression learning to learn augmentation pipelines able to achieve a high F-measure on the training data. Our evaluation suggests that our approach can efficiently learn a larger class of RDF dataset augmentation tasks than the state of the art while using only a single training example. Even on the most complex augmentation problem we posed, our approach consistently achieves an average F1-measure of 99% in under 500 iterations with an average runtime of 16 seconds}}, author = {{Dreßler, Kevin and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia}}, keywords = {{2022 RAKI SFB901 deer dice kevin knowgraphs limes ngonga sherif simba}}, location = {{Barcelona (Spain)}}, title = {{{ADAGIO - Automated Data Augmentation of Knowledge Graphs Using Multi-expression Learning}}}, doi = {{10.1145/3511095.3531287}}, year = {{2022}}, } @article{32854, author = {{Redder, Adrian and Ramaswamy, Arunselvan and Karl, Holger}}, journal = {{IFAC-PapersOnLine}}, number = {{13}}, pages = {{133–138}}, publisher = {{Elsevier}}, title = {{{Practical Network Conditions for the Convergence of Distributed Optimization}}}, volume = {{55}}, year = {{2022}}, } @inproceedings{33253, author = {{Hansmeier, Tim and Brede, Mathis and Platzner, Marco}}, booktitle = {{GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion}}, location = {{Boston, MA, USA}}, pages = {{2071--2079}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{XCS on Embedded Systems: An Analysis of Execution Profiles and Accelerated Classifier Deletion}}}, doi = {{10.1145/3520304.3533977}}, year = {{2022}}, } @inproceedings{34152, author = {{Otroshi, Mortaza and Meschut, Gerson}}, location = {{Rostock}}, publisher = {{Europäische Forschungsgesellschaft für Blechverarbeitung e.V. }}, title = {{{Methodenentwicklung zur Verbesserung der Schädigungsmodellierung in der numerischen 3D-Belastungssimulation mechanischer Fügeverfahren unter Berücksichtigung der fügeinduzierten Vorbeanspruchung}}}, year = {{2022}}, } @article{34417, abstract = {{Given strict emission targets and legal requirements, especially in the automotive industry, environmentally friendly and simultaneously versatile applicable production technologies are gaining importance. In this regard, the use of mechanical joining processes, such as clinching, enable assembly sheet metals to achieve strength properties similar to those of established thermal joining technologies. However, to guarantee a high reliability of the generated joint connection, the selection of a best-fitting joining technology as well as the meaningful description of individual joint properties is essential. In the context of clinching, few contributions have to date investigated the metamodel-based estimation and optimization of joint characteristics, such as neck or interlock thickness, by applying machine learning and genetic algorithms. Therefore, several regression models have been trained on varying databases and amounts of input parameters. However, if product engineers can only provide limited data for a new joining task, such as incomplete information on applied joining tool dimensions, previously trained metamodels often reach their limits. This often results in a significant loss of prediction quality and leads to increasing uncertainties and inaccuracies within the metamodel-based design of a clinch joint connection. Motivated by this, the presented contribution investigates different machine learning algorithms regarding their ability to achieve a satisfying estimation accuracy on limited input data applying a statistically based feature selection method. Through this, it is possible to identify which regression models are suitable to predict clinch joint characteristics considering only a minimum set of required input features. Thus, in addition to the opportunity to decrease the training effort as well as the model complexity, the subsequent formulation of design equations can pave the way to a more versatile application and reuse of pretrained metamodels on varying tool configurations for a given clinch joining task.}}, author = {{Zirngibl, Christoph and Schleich, Benjamin and Wartzack, Sandro}}, issn = {{2673-2688}}, journal = {{AI}}, keywords = {{Industrial and Manufacturing Engineering}}, number = {{4}}, pages = {{990--1006}}, publisher = {{MDPI AG}}, title = {{{Estimation of Clinch Joint Characteristics Based on Limited Input Data Using Pre-Trained Metamodels}}}, doi = {{10.3390/ai3040059}}, volume = {{3}}, year = {{2022}}, } @unpublished{34618, abstract = {{In this article, we show how second-order derivative information can be incorporated into gradient sampling methods for nonsmooth optimization. The second-order information we consider is essentially the set of coefficients of all second-order Taylor expansions of the objective in a closed ball around a given point. Based on this concept, we define a model of the objective as the maximum of these Taylor expansions. Iteratively minimizing this model (constrained to the closed ball) results in a simple descent method, for which we prove convergence to minimal points in case the objective is convex. To obtain an implementable method, we construct an approximation scheme for the second-order information based on sampling objective values, gradients and Hessian matrices at finitely many points. Using a set of test problems, we compare the resulting method to five other available solvers. Considering the number of function evaluations, the results suggest that the method we propose is superior to the standard gradient sampling method, and competitive compared to other methods.}}, author = {{Gebken, Bennet}}, booktitle = {{arXiv:2210.04579}}, title = {{{Using second-order information in gradient sampling methods for nonsmooth optimization}}}, year = {{2022}}, } @inproceedings{29342, author = {{Sander, Sascha and Teutenberg, Dominik and Meschut, Gerson and Kötz, Fabian and Matzenmiller, Anton and Kasper, Yann and Ummenhofer, Thomas}}, booktitle = {{22. Kolloquium Gemeinsame Forschung in der Klebtechnik}}, location = {{Online Konferenz}}, title = {{{Methodenentwicklung zur rechnerischen Auslegung geklebter Stahlverbindungen unter Alterungsbeanspruchung im Stahl- und Anlagenbau }}}, year = {{2022}}, } @inproceedings{29302, abstract = {{This paper introduces the project Scale4Edge. The project is focused on enabling an effective RISC-V ecosystem for optimization of edge applications. We describe the basic components of this ecosystem and introduce the envisioned demonstrators, which will be used in their evaluation.}}, author = {{Ecker, Wolfgang and Adelt, Peer and Müller, Wolfgang and Heckmann, Reinhold and Krstic, Milos and Herdt, Vladimir and Drechsler, Rolf and Angst, Gerhard and Wimmer, Ralf and Mauderer, Andreas and Stahl, Rafael and Emrich, Karsten and Mueller-Gritschneder, Daniel and Becker, Bernd and Scholl, Philipp and Jentzsch, Eyck and Schlamelcher, Jan and Grüttner, Kim and Bernardo, Paul Palomero and Brinkmann, Oliver and Damian, Mihaela and Oppermann, Julian and Koch, Andreas and Bormann, Jörg and Partzsch, Johannes and Mayr, Christian and Kunz, Wolfgang}}, booktitle = {{In Proceedings of the Design Automation and Test Conference and Exhibition (DATE 2022)}}, title = {{{The Scale4Edge RISC-V Ecosystem}}}, year = {{2022}}, }