Zeitschrift für deutsche Philologie (Herausgebertätigkeit von Norbert Otto Eke ab Bd. 123, 2004)

Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control - Bode, Henrik; Heid, Stefan Helmut; Weber, Daniel; Hüllermeier, Eyke; Wallscheid, Oliver (arXiv:2005.04869)
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.

ProConAR: A Tool Support for Model-based AR Product Configuration - Gottschalk, Sebastian; Yigitbas, Enes; Schmidt, Eugen; Engels, Gregor (Human-Centered Software Engineering. HCSE 2020)
Mobile shopping apps have been using Augmented Reality (AR) in the last years to place their products in the environment of the customer. While this is possible with atomic 3D objects, there is is still a lack in the runtime conﬁguration of 3D object compositions based on user needs and environmental constraints. For this, we previously developed an approach for model-based AR-assisted product conﬁguration based on the concept of Dynamic Software Product Lines. In this demonstration paper, we present the corresponding tool support ProConAR in the form of a Product Modeler and a Product Conﬁgurator. While the Product Modeler is an Angular web app that splits products (e.g. table) up into atomic parts (e.g. tabletop, table legs, funnier) and saves it within a conﬁguration model, the Product Conﬁgurator is an Android client that uses the conﬁguration model to place diﬀerent product conﬁgurations within the environment of the customer. We show technical details of our ready to use tool-chain ProConAR by describing its implementation and usage as well as pointing out future research directions.
Keywords: Product Configuration; Augmented Reality; Model-based; Tool Support

Every Node for Itself: Fully Distributed Service Coordination - Schneider, Stefan Balthasar; Klenner, Lars Dietrich; Karl, Holger (IEEE International Conference on Network and Service Management (CNSM))
Modern services consist of modular, interconnected components, e.g., microservices forming a service mesh. To dynamically adjust to ever-changing service demands, service components have to be instantiated on nodes across the network. Incoming flows requesting a service then need to be routed through the deployed instances while considering node and link capacities. Ultimately, the goal is to maximize the successfully served flows and Quality of Service (QoS) through online service coordination. Current approaches for service coordination are usually centralized, assuming up-to-date global knowledge and making global decisions for all nodes in the network. Such global knowledge and centralized decisions are not realistic in practical large-scale networks. To solve this problem, we propose two algorithms for fully distributed service coordination. The proposed algorithms can be executed individually at each node in parallel and require only very limited global knowledge. We compare and evaluate both algorithms with a state-of-the-art centralized approach in extensive simulations on a large-scale, real-world network topology. Our results indicate that the two algorithms can compete with centralized approaches in terms of solution quality but require less global knowledge and are magnitudes faster (more than 100x).
Keywords: distributed management; service coordination; network coordination; nfv; softwarization; orchestration

Self-Driving Network and Service Coordination Using Deep Reinforcement Learning - Schneider, Stefan Balthasar; Manzoor, Adnan; Qarawlus, Haydar; Schellenberg, Rafael; Karl, Holger; Khalili, Ramin; Hecker, Artur (IEEE International Conference on Network and Service Management (CNSM))
Modern services comprise interconnected components, e.g., microservices in a service mesh, that can scale and run on multiple nodes across the network on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities and changing demands into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge). We propose a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, it significantly improves flow throughput and overall network utility on real-world network topologies and traffic traces. It also learns to optimize different objectives, generalizes to scenarios with unseen, stochastic traffic patterns, and scales to large real-world networks.
Keywords: self-driving networks; self-learning; network coordination; service coordination; reinforcement learning; deep learning; nfv

Augmented and Virtual Reality Object Repository for Rapid Prototyping - Jovanovikj, Ivan; Yigitbas, Enes; Sauer, Stefan; Engels, Gregor (Proceedings of the 8th International Working Conference on Human-Centered Software Engineering (HCSE'20))

Automatic Fairness Testing of Machine Learning Models - Sharma, Arnab; Wehrheim, Heike (Proceedings of the 32th IFIP International Conference on Testing Software and Systems (ICTSS))

“On-The-Fly” Calculation of the Vibrational Sum-Frequency Generation Spectrum at the Air-Water Interface - Ojha, Deepak; Kühne, Thomas D. (Molecules)
In the present work, we provide an electronic structure based method for the “on-the-fly” determination of vibrational sum frequency generation (v-SFG) spectra. The predictive power of this scheme is demonstrated at the air-water interface. While the instantaneous fluctuations in dipole moment are obtained using the maximally localized Wannier functions, the fluctuations in polarizability are approximated to be proportional to the second moment of Wannier functions. The spectrum henceforth obtained captures the signatures of hydrogen bond stretching, bending, as well as low-frequency librational modes.

Disordered crystals from first principles II: Transport coefficients - Kühne, Thomas; Heske, Julian Joachim; Prodan, Emil (Annals of Physics)
This is the second part of a project on the foundations of first-principle calculations of the electron transport in crystals at finite temperatures, aiming at a predictive first-principles platform that combines ab-initio molecular dynamics (AIMD) and a finite-temperature Kubo-formula with dissipation for thermally disordered crystalline phases. The latter are encoded in an ergodic dynamical system (Ω,G,dP), where Ω is the configuration space of the atomic degrees of freedom, G is the space group acting on Ω and dP is the ergodic Gibbs measure relative to the G-action. We first demonstrate how to pass from the continuum Kohn–Sham theory to a discrete atomic-orbitals based formalism without breaking the covariance of the physical observables w.r.t. (Ω,G,dP). Then we show how to implement the Kubo-formula, investigate its self-averaging property and derive an optimal finite-volume approximation for it. We also describe a numerical innovation that made possible AIMD simulations with longer orbits and elaborate on the details of our simulations. Lastly, we present numerical results on the transport coefficients of crystal silicon at different temperatures.

Insight from energy decomposition analysis on a hydrogen-bond-mediated mechanism for on-water catalysis - Salem, M. Alaraby; Kühne, Thomas D. (Molecular Physics)

Wann bin ich wer? Peer-Berater*innen im Spannungsverhältnis - Lebock, Sarah (Journal der Schreibberatung)
Peer-Berater*innen nehmen während eines Beratungsgespräches teilweise intuitiv, teilweise bewusst verschiedene Rollen ein. Dieser Artikel soll einen Beitrag zur Reflexion über das Spannungsverhältnis zwischen der Experten- und Prozessberatungsrolle leisten, um die Selbstprofessionalisierung in der Rolleneinnahme zu fördern. Dafür werden auf theoretischer Ebene die konträren Arbeitsweisen beleuchtet, auf denen beide Rollen basieren. Zur Betrachtung von möglichen Einflussfaktoren auf die Rolleneinnahme wird ein selbst entwickeltes Modell präsentiert, welches zum Austausch über diese Faktoren motivieren soll. Zuletzt wird eine praktische Möglichkeit zur gezielten Reflexion über die eigene Rolleneinnahme anhand eines Fragebogens vorgeschlagen.
Keywords: Expertenberatung; Prozessberatung; Rolleneinnahme; Selbstprofessionalisierung

Numerische Simulation von Gravidestillationsapparaten zur Trennung eines binären Ethanol/Wasser-Gemisches - Wende, Marc; Philippi, Kai; Kenig, Eugeny (10. ProcessNet-Jahrestagung und 34. DECHEMA-Jahrestagung der Biotechnologen)

Active Business Model Development Tools: Design Requirements - Szopinski, Daniel (Proceedings of the 15th International Conference on Design Science Research in Information Systems and Technology (DESRIST))

Exploring design principles for stimuli in business model development tools - Szopinski, Daniel (Proceedings of the 41st International Conference on Information Systems (ICIS))

Methodenentwicklung zum Entfügen von Stahl-Klebverbindungen bei tiefen Temperaturen - Ditter, Jan

Simple Determination of Fast Curing Parameters for Bonded Structures - Ditter, Jan; Aubel, Tobias; Meschut, Gerson (adhesion ADHESIVES + SEALANTS)

Toss a Coin to your Host - How Guests End up Paying for the Cost of Regulatory Policies - Müller, Michelle; Neumann, Jürgen; Gutt, Dominik; Kundisch, Dennis (Proceedings of the 41th International Conference on Information Systems (ICIS))

Correlating facet orientation, defect-level density and dipole layer formation at the surface of polycrystalline CuInSe2 thin films - Elizabeth, Amala; Conradi, Hauke; K. Sahoo, Sudhir; Kodalle, Tim; A. Kaufmann, Christian; Kühne, Thomas; Mirhosseini, Hossein; Abou-Ras, Daniel; Mönig, Harry (Acta Materialia)
Individual grains of chalcopyrite solar cell absorbers can facet in different crystallographic directions at their surfaces. To gain a deeper understanding of the junction formation in these devices, we correlate variations in the surface facet orientation with the defect electronic properties. We use a combined analytical approach based on scanning tunneling spectroscopy (STS), scanning electron microscopy, and electron back scatter diffraction (EBSD), where we perform these experiments on identical surface areas as small as 2 × 2 µm2 with a lateral resolution well below 50 nm. The topography of the absorber surfaces indicates two main morphological features: micro-faceted, long basalt-like columns and their short nano-faceted terminations. Our STS results reveal that the long columns exhibit spectral signatures typical for the presence of pronounced oxidation-induced surface dipoles in conjunction with an increased density of electronic defect levels. In contrast, the nano-faceted terminations of the basalt-like columns are largely passivated in terms of electronic defect levels within the band gap region. Corresponding crystallographic data based on EBSD experiments show that the surface of the basalt-like columns can be assigned to intrinsically polar facet orientations, while the passivated terminations are assigned to non-polar planes. Ab-initio calculations suggest that the polar surfaces are more prone to oxidation and resulting O-induced defects, in comparison to non-polar planes. Our results emphasize the correlation between morphology, surface facet orientations and surface electronic properties. Furthermore, this work aids in gaining a fundamental understanding of oxidation induced lateral inhomogeneities in view of the p-n junction formation in chalcopyrite thin-film solar cells.
Keywords: Chalcopyrite absorber; Scanning tunneling spectroscopy; Electron backscatter diffraction; Density functional theory; Surface dipole

Research and Consulting in Data-Driven Strategic Product Planning - Meyer, Maurice; Frank, Maximilian; Massmann, Melina; Dumitrescu, Roman (Proceedings of The 11th International Multi-Conference on Complexity, Informatics and Cybernetics (IMCIC 2020))

Research and Consulting in Data-Driven Strategic Product Planning - Meyer, Maurice; Frank, Maximilian; Massmann, Melina; Dumitrescu, Roman (Journal of Systemics, Cybernetics and Informatics)

Social interactions and asset pricing bubbles - Steiger, Sören; Pelster, Matthias (Journal of Economic Behavior & Organization)

A Discrete and Continuous Study of the Max-Chain-Formation Problem – Slow Down to Speed Up - Castenow, Jannik; Kling, Peter; Knollmann, Till; Meyer auf der Heide, Friedhelm (Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings)
Most existing robot formation problems seek a target formation of a certain minimal and, thus, efficient structure. Examples include the Gathering and the Chain-Formation problem. In this work, we study formation problems that try to reach a maximal structure, supporting for example an efficient coverage in exploration scenarios. A recent example is the NASA Shapeshifter project, which describes how the robots form a relay chain along which gathered data from extraterrestrial cave explorations may be sent to a home base. As a first step towards understanding such maximization tasks, we introduce and study the Max-Chain-Formation problem, where $n$ robots are ordered along a winding, potentially self-intersecting chain and must form a connected, straight line of maximal length connecting its two endpoints. We propose and analyze strategies in a discrete and in a continuous time model. In the discrete case, we give a complete analysis if all robots are initially collinear, showing that the worst-case time to reach an $\varepsilon$-approximation is upper bounded by $\mathcal{O}(n^2 \cdot \log (n/\varepsilon))$ and lower bounded by $\Omega(n^2 \cdot~\log (1/\varepsilon))$. If one endpoint of the chain remains stationary, this result can be extended to the non-collinear case. If both endpoints move, we identify a family of instances whose runtime is unbounded. For the continuous model, we give a strategy with an optimal runtime bound of $\Theta(n)$. Avoiding an unbounded runtime similar to the discrete case relies crucially on a counter-intuitive aspect of the strategy: slowing down the endpoints while all other robots move at full speed. Surprisingly, we can show that a similar trick does not work in the discrete model.

Preservation of Bifurcations of Hamiltonian Boundary Value Problems Under Discretisation - McLachlan, Robert I; Offen, Christian (Foundations of Computational Mathematics)
We show that symplectic integrators preserve bifurcations of Hamiltonian boundary value problems and that nonsymplectic integrators do not. We provide a universal description of the breaking of umbilic bifurcations by nonysmplectic integrators. We discover extra structure induced from certain types of boundary value problems, including classical Dirichlet problems, that is useful to locate bifurcations. Geodesics connecting two points are an example of a Hamiltonian boundary value problem, and we introduce the jet-RATTLE method, a symplectic integrator that easily computes geodesics and their bifurcations. Finally, we study the periodic pitchfork bifurcation, a codimension-1 bifurcation arising in integrable Hamiltonian systems. It is not preserved by either symplectic on nonsymplectic integrators, but in some circumstances symplecticity greatly reduces the error.

Detection of high codimensional bifurcations in variational PDEs - Kreusser, Lisa Maria; McLachlan, Robert I; Offen, Christian (Nonlinearity)

Analysis of Hamiltonian boundary value problems and symplectic integration - Offen, Christian
Ordinary differential equations (ODEs) and partial differential equations (PDEs) arise in most scientific disciplines that make use of mathematical techniques. As exact solutions are in general not computable, numerical methods are used to obtain approximate solutions. In order to draw valid conclusions from numerical computations, it is crucial to understand which qualitative aspects numerical solutions have in common with the exact solution. Symplecticity is a subtle notion that is related to a rich family of geometric properties of Hamiltonian systems. While the effects of preserving symplecticity under discretisation on long-term behaviour of motions is classically well known, in this thesis (a) the role of symplecticity for the bifurcation behaviour of solutions to Hamiltonian boundary value problems is explained. In parameter dependent systems at a bifurcation point the solution set to a boundary value problem changes qualitatively. Bifurcation problems are systematically translated into the framework of classical catastrophe theory. It is proved that existing classification results in catastrophe theory apply to persistent bifurcations of Hamiltonian boundary value problems. Further results for symmetric settings are derived. (b) It is proved that to preserve generic bifurcations under discretisation it is necessary and sufficient to preserve the symplectic structure of the problem. (c) The catastrophe theory framework for Hamiltonian ODEs is extended to PDEs with variational structure. Recognition equations for A-series singularities for functionals on Banach spaces are derived and used in a numerical example to locate high-codimensional bifurcations. (d) The potential of symplectic integration for infinite-dimensional Lie-Poisson systems (Burgers’ equation, KdV, fluid equations, . . . ) using Clebsch variables is analysed. It is shown that the advantages of symplectic integration can outweigh the disadvantages of integrating over a larger phase space introduced by a Clebsch representation. (e) Finally, the preservation of variational structure of symmetric solutions in multisymplectic PDEs by multisymplectic integrators on the example of (phase-rotating) travelling waves in the nonlinear wave equation is discussed.

A Novel Higher-order Weisfeiler-Lehman Graph Convolution - Damke, Clemens; Melnikov, Vitaly; Hüllermeier, Eyke (Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020))
Current GNN architectures use a vertex neighborhood aggregation scheme, which limits their discriminative power to that of the 1-dimensional Weisfeiler-Lehman (WL) graph isomorphism test. Here, we propose a novel graph convolution operator that is based on the 2-dimensional WL test. We formally show that the resulting 2-WL-GNN architecture is more discriminative than existing GNN approaches. This theoretical result is complemented by experimental studies using synthetic and real data. On multiple common graph classification benchmarks, we demonstrate that the proposed model is competitive with state-of-the-art graph kernels and GNNs.
Keywords: graph neural networks; Weisfeiler-Lehman test; cycle detection

Process design for the forming of semi-tubular self-piercing rivets made of high nitrogen steel
The aim to reduce pollutant emission has led to a trend towards lightweight construction in car body development during the last years. As a consequence of the resulting need for multi-material design, mechanical joining technologies become increasingly important. Mechanical joining allows for the combination of dissimilar materials, while thermic joining techniques reach their limits. Self-piercing riveting enables the joining of dissimilar materials by using semi-tubular rivets as mechanical fasteners. The rivet production, however, is costly and time-consuming, as the rivets generally have to be hardened, tempered and coated after forming, in order to achieve an adequate strength and corrosion resistance. A promising approach to improve the efficiency of the rivet manufacturing is the use of high-strength high nitrogen steel as rivet material because these additional process steps would not be necessary anymore. As a result of the comparatively high nitrogen content, such steels have various beneficial properties like higher strength, good ductility and improved corrosion resistance. By cold bulk forming of high nitrogen steels high-strength parts can be manufactured due to the strengthening which is caused by the high strain hardening. However, high tool loads thereby have to be expected and are a major challenge during the production process. Consequently, there is a need for appropriate forming strategies. This paper presents key aspects concerning the process design for the manufacturing of semi-tubular self-piercing rivets made of high-strength steel. The aim is to produce the rivets in several forming stages without intermediate heat treatment between the single stages. Due to the high strain hardening of the material, a two stage forming concept will be investigated. Cup-backward extrusion is chosen as the first process step in order to form the rivet shank without forming the rivet foot. Thus, the strain hardening effects in the area of the rivet foot are minimized and the tool loads during the following process step can be reduced. During the second and final forming stage the detailed geometry of the rivet foot and the rivet head is formed. In this context, the effect of different variations, for example concerning the final geometry of the rivet foot, on the tool load is investigated using multistage numerical analysis. Furthermore, the influence of the process temperature on occurring stresses is analysed. Based on the results of the investigations, an adequate forming strategy and a tool concept for the manufacturing of semi-tubular self-piercing rivets made of high-strength steel are presented.
Keywords: high nitrogen steel; self-piercing riveting; joining by forming; bulk forming; tool design

Optimierung von JMCTest beim Testen von Inter Method Contracts - Mayer, Stefan

Mining Crowdsourcing Problems from Discussion Forums of Workers - Nouri, Zahra; Wachsmuth, Henning; Engels, Gregor (Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics)

Persuasiveness of News Editorials depending on Ideology and Personality - El Baff, Roxanne; Al-Khatib, Khalid; Stein, Benno; Wachsmuth, Henning (Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES 2020))

Mobile Medien – Medienpädagogische und technische Grundlagen, Potential für den Deutschunterricht und Beispiele. - Herzig, Bardo; Martin, Alexander; Klar, Tilman-Mathies (Deutsch Digital. Band 1 Theorie (2. Aufl.))

Als Wirtschaftsinformatiker die digitale Transformation in Organisationen gestalten - Kundisch, Dennis; Beverungen, Daniel

Argument from Old Man's View: Assessing Social Bias in Argumentation - Spliethöver, Maximilian; Wachsmuth, Henning (Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020))

Semi-Supervised Cleansing of Web Argument Corpora - Dorsch, Jonas; Wachsmuth, Henning (Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020))

Methodenentwicklung zur Schädigungsmodellierung für die numerische Prozesssimulation mechanischer Fügeverfahren - Otroshi, Mortaza; Meschut, Gerson
Der Karosseriebau ist zunehmend durch die Verwendung unterschiedlicher Werkstoffe in Mischbauweise gekennzeichnet, was zu einem Einsatz von mechanischen Fügeverfahren geführt hat. Hieraus resultieren die Zielsetzungen, die mechanischen Fügeverfahren in ihrer Effizienz und ihren Einsatzbereichen zu erweitern, sowie die Anzahl der Experimente zu reduzieren und Entwicklungszyklen zu verkürzen. Dies erfolgt mit Unterstützung der numerischen Simulation. Neben der Beschreibung des plastischen Verhaltens gilt es auch, das Schädigungsverhalten abzubilden. Der Fügeprozess bzw. die Fügerichtung erfolgt senkrecht zur Blechoberfläche und führt somit zu einem dreidimensionalen Zustand der Fügelemente. Hieraus leitet sich die Herausforderung ab, das Werkstoffversagen in Abhängigkeit der Beanspruchungssituation zu beschreiben. Ein einfacher Ansatz zur Abbildung des Durchdringens ist ein geometrisches Trennkriterium. Ein solches Kriterium basiert i.d.R. auf einem experimentell beobachteten Verhalten und ist somit nicht prognosefähig für Variationen bzgl. Werkzeugkonfigurationen, Blechdicken- und Werkstoffgüten-Kombinationen. In diesem Projekt wird das Schädigungsmodell GISSMO (Generalized Incremental Stress State dependent damage Model) verwendet, um die Entwicklung der duktilen Schädigung zu beschreiben und den Bruchbeginn während des Stanzniet- und Schneidclinchens vorherzusagen. Der Spannungszustand während der Prozesssimulation wird untersucht und die verschiedenen Schädigungsproben werden experimentell erprobt, um die Versagenskurven zu charakterisieren. Die Versagenskurven werden im Schädigungsmodell GISSMO definiert. Um die Genauigkeit des Modells zu gewährleisten, wird die Verifizierung des Modells durch die Simulation von Schädigungsproben mit dem Schädigungsmodell durchgeführt. Zur Validierung des Modells wird die Simulation des Fügeprozesses mit dem Schädigungsmodell durchgeführt und die Ergebnisse von Simulation und Experiment verglichen. Darüber hinaus werden Sensitivitätsanalysen durchgeführt, um die Einflüsse der Fertigungsprozesse, der Lackierung und des Diskretisierungsgrades auf das Schädigungsverhalten des Materials zu identifizieren. Das IGF-Vorhaben „Methodenentwicklung zur Schädigungsmodellierung für die numerische Prozesssimulation mechanischer Fügeverfahren" der Forschungsvereinigung EFB e.V. wurde unter der Fördernummer AiF 19452N über die Arbeitsgemeinschaft industrieller Forschungsvereinigungen (AiF) im Rahmen des Programms zur Förderung der Industriellen Gemeinschaftsforschung (IGF) vom Bundesministerium für Wirtschaft und Energie aufgrund eines Beschlusses des Deutschen Bundestages gefördert. Der Abschlussbericht ist als EFB-Forschungsbericht Nr. 527 erschienen und bei der EFB-Geschäftsstelle und im Buchhandel erhältlich.

Linear damage accumulation of self-pierce riveted joints - Masendorf, Lukas; Wächter, Michael; Horstmann, Stephan; Otroshi, Mortaza; Esderts, Alfons; Meschut, Gerson
Joining technology is regarded as a key technology for reducing energy consumption and CO2 imitation as well as the use of innovative materials and development of new, resource-saving products. Punch riveting is a widely used and established joining process in many sectors. The white and brown goods, electrical engineering, construction and, in particular, the automotive industry are some of the sectors mentioned here. Since the design and assessment of punch rivet components with regard to structural durability can only be carried out experimentally using prototypes due to a lack of experience and calculation concepts, the improvement of this uneconomical and time-consuming procedure is the goal of this contribution. Therefore, a numerical simulation and design method for cyclically loads punched riveted joints shall be introduced. This concept shall be based on the notch strain concept. The following steps are necessary to achieve the goal shown above: Tensile tests on all materials involved in the joint for determination of tensile strength and quasi-static stress-strain curves Estimation of the cyclic material properties from the tensile strength in order to obtain the strain-life curve and the cyclic stress-strain curve Estimation of mean stress sensitivity from the tensile strength to conduct an amplitude transformation for variable amplitude loadings. Execution of a 2D forming simulation of the joining process to determine the geometry and the stresses and degrees of deformation present in the connection Transferring the results of the forming simulation into a static-mechanical load simulation for determining the relation between the external load and the elastic-plastic strain at the critical point Estimation of the service life by means of the damage parameter Wöhler curves calculated from the strain-life curve In order to verify the simulation and calculation method, service life investigations have been carried out on punched riveted components under constant and variable amplitude load. The test results, as well as the workflow through the fatigue assessment and its accuracy in estimation the fatigue life will be shown in this contribution.
Keywords: punch rivet; notch strain conept; structural durability

Mincut Sensitivity Data Structures for the Insertion of an Edge - Baswana, Surender; Gupta, Shiv; Knollmann, Till (28th Annual European Symposium on Algorithms (ESA 2020))
Let G = (V,E) be an undirected graph on n vertices with non-negative capacities on its edges. The mincut sensitivity problem for the insertion of an edge is defined as follows. Build a compact data structure for G and a given set S ⊆ V of vertices that, on receiving any edge (x,y) ∈ S×S of positive capacity as query input, can efficiently report the set of all pairs from S× S whose mincut value increases upon insertion of the edge (x,y) to G. The only result that exists for this problem is for a single pair of vertices (Picard and Queyranne, Mathematical Programming Study, 13 (1980), 8-16). We present the following results for the single source and the all-pairs versions of this problem. 1) Single source: Given any designated source vertex s, there exists a data structure of size 𝒪(|S|) that can output all those vertices from S whose mincut value to s increases upon insertion of any given edge. The time taken by the data structure to answer any query is 𝒪(|S|). 2) All-pairs: There exists an 𝒪(|S|²) size data structure that can output all those pairs of vertices from S× S whose mincut value gets increased upon insertion of any given edge. The time taken by the data structure to answer any query is 𝒪(k), where k is the number of pairs of vertices whose mincut increases. For both these versions, we also address the problem of reporting the values of the mincuts upon insertion of any given edge. To derive our results, we use interesting insights into the nearest and the farthest mincuts for a pair of vertices. In addition, a crucial result, that we establish and use in our data structures, is that there exists a directed acyclic graph of 𝒪(n) size that compactly stores the farthest mincuts from all vertices of V to a designated vertex s in the graph. We believe that this result is of independent interest, especially, because it also complements a previously existing result by Hariharan et al. (STOC 2007) that the nearest mincuts from all vertices of V to s is a laminar family, and hence, can be stored compactly in a tree of 𝒪(n) size.
Keywords: Mincut; Sensitivity; Data Structure

Reinforcement Learning for Virtual Network Embedding in Wireless Sensor Networks - Afifi, Haitham; Karl, Holger (2020 Thirteenth International Workshop on Selected Topics in Mobile and Wireless Computing (STWiMob'2020))
Upcoming sensing applications (acoustic or video) will have high processing requirements not satisfiable by a single node or need input from multiple sources (e.g., speaker localization). Offloading these applications to cloud or mobile edge is an option, but when running in a wireless senor network (WSN), it might entail needlessly high data rate and latency. An alternative is to spread processing inside the WSN, which is particularly attractive if the application comprises individual components. This scenario is typical for applications like acoustic signal processing. Mapping components to nodes can be formulated as wireless version of the NP-hard Virtual Network Embedding (VNE) problem, for which various heuristics exist. We propose a Reinforcement Learning (RL) framework, which relies on Q-Learning and uses either Greedy Epsilon or Epsilon Decay for exploration. We compare both exploration methods to the result of an optimization approach and show empirically that the RL framework achieves good results in terms of network delay within few number of steps.

Overview of Touché 2020: Argument Retrieval - Bondarenko, Alexander; Fröbe, Maik; Beloucif, Meriem; Gienapp, Lukas; Ajjour, Yamen; Panchenko, Alexander; Biemann, Chris; Stein, Benno; Wachsmuth, Henning; Potthast, Martin; Hagen, Matthias (CEUR Workshop Proceedings)

Spannungszustandsabhängige Schädigungsmodellierung zum Halbhohlstanznieten - Otroshi, Mortaza; Meschut, Gerson (Umformtechnik Blech Rohre Profile)

Brief Announcement: Gathering in Linear Time: A Closed Chain of Disoriented & Luminous Robots with Limited Visibility - Castenow, Jannik; Harbig, Jonas; Jung, Daniel; Knollmann, Till; Meyer auf der Heide, Friedhelm (Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings)

Hybrid coupled mode modelling of the evanescent excitation of a dielectric tube by semi-guided waves at oblique angles - Hammer, Manfred; Ebers, Lena; Förstner, Jens (Optical and Quantum Electronics)
A dielectric step-index optical fiber with tube-like profile is considered, being positioned with a small gap on top of a dielectric slab waveguide. We propose a 2.5-D hybrid analytical/numerical coupled mode model for the evanescent excitation of the tube through semi-guided waves propagating in the slab at oblique angles. The model combines the directional polarized modes supported by the slab with analytic solutions for the TE-, TM-, and orbital-angular-momentum (OAM) modes of the tube-shaped fiber. Implementational details of the scheme are discussed, complemented by finite-element simulations for verification purposes. Our results include configurations with resonant in-fiber excitation of OAM modes with large orbital angular momentum and strong field enhancement.
Keywords: tet_topic_waveguides

Platform-independent Reputation and Qualification System for Crowdwork - Hemsen, Paul; Hesse, Marc; Löken, Nils; Nouri, Zahra (2nd Crowdworking Symposium)

Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model - Lienen, Julian; Hüllermeier, Eyke (arXiv:2010.13118)
In many real-world applications, the relative depth of objects in an image is crucial for scene understanding, e.g., to calculate occlusions in augmented reality scenes. Predicting depth in monocular images has recently been tackled using machine learning methods, mainly by treating the problem as a regression task. Yet, being interested in an order relation in the first place, ranking methods suggest themselves as a natural alternative to regression, and indeed, ranking approaches leveraging pairwise comparisons as training information ("object A is closer to the camera than B") have shown promising performance on this problem. In this paper, we elaborate on the use of so-called listwise ranking as a generalization of the pairwise approach. Listwise ranking goes beyond pairwise comparisons between objects and considers rankings of arbitrary length as training information. Our approach is based on the Plackett-Luce model, a probability distribution on rankings, which we combine with a state-of-the-art neural network architecture and a sampling strategy to reduce training complexity. An empirical evaluation on benchmark data in a "zero-shot" setting demonstrates the effectiveness of our proposal compared to existing ranking and regression methods.

Plurality Consensus in Hybrid Networks - Yeole, Paresh Kishor

Nonlinear dielectric properties of random paraelectric-dielectric composites - Myroshnychenko, Viktor; Smirnov, Stanislav; Jose, Pious Mathews Mulavarickal; Brosseau, Christian; Förstner, Jens (Acta Materialia)
The challenge of designing new tunable nonlinear dielectric materials with tailored properties has attracted an increasing amount of interest recently. Herein, we study the effective nonlinear dielectric response of a stochastic paraelectric-dielectric composite consisting of equilibrium distributions of circular and partially penetrable disks (or parallel, infinitely long, identical, partially penetrable, circular cylinders) of a dielectric phase randomly dispersed in a continuous matrix of a paraelectric phase. The random microstructures were generated using the Metropolis Monte Carlo algorithm. The evaluation of the effective permittivity and tunability were carried out by employing either a Landau thermodynamic model or its Johnson’s approximation to describe the field-dependent permittivity of the paraelectric phase and solving continuum-electrostatics equations using finite element calculations. We reveal that the percolation threshold in this composite governs the critical behavior of the effective permittivity and tunability. For microstructures below the percolation threshold, our simulations demonstrate a strong nonlinear behaviour of the field-dependent effective permittivity and very high tunability that increases as a function of dielectric phase concentration. Above the percolation threshold, the effective permittivity shows the tendency to linearization and the tunability dramatically drops down. The highly reduced permittivity and extraordinarily high tunability are obtained for the composites with dielectric impenetrable disks at high concentrations, in which the triggering of the percolation transition is avoided. The reported results cast light on distinct nonlinear behaviour of 2D and 3D stochastic composites and can guide the design of novel composites with the controlled morphology and tailored permittivity and tunability.

Increased load bearing capacity of mechanically joined FRP/metal joints using a pin structured auxiliary joining element - Heyser, Per; Sartisson, Vadim; Meschut, Gerson; Droß, Marcel; Dröder, Klaus (Materials Testing)

Essays on Cooperation in Differential Games - Hoof, Simon

Avoidance of liquid metal embrittlement during resistance spot welding by heat input dependent hold time adaption - Böhne, Christoph; Meschut, Gerson; Biegler, Max; Rethmeier, Michael (Science and Technology of Welding and Joining)

Resistance spot welding simulation can determine the critical stress- and strain-conditions leading to liquid metal embrittlement formation - Biegler, Max; Rethmeier, Michael; Böhne, Christoph; Meschut, Gerson (Joining in Car Body Engineering)