Distributed gradient-based optimization in the presence of dependent aperiodic communication - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (arXiv:2201.11343)
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 $α$-mixing with $n^{p-1}α(n)$ 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 $α(n)$ is summable.

Du Châtelet et la tradition critique de la Bible. De la ‘philofolie’ aux Examens - Hagengruber, Ruth Edith (La Lettre clandestine n° 30: Émilie Du Châtelet et la littérature clandestine. Moreau, P.F. & Seguin, M.S. (Eds.). Paris)

ReconOS64: A Hardware Operating System for Modern Platform FPGAs with 64-Bit Support - Clausing, Lennart; Platzner, Marco (2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW))

Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (arXiv:2201.00570)
We present sufficient conditions that ensure convergence of the multi-agent Deep Deterministic Policy Gradient (DDPG) algorithm. It is an example of one of the most popular paradigms of Deep Reinforcement Learning (DeepRL) for tackling continuous action spaces: the actor-critic paradigm. In the setting considered herein, each agent observes a part of the global state space in order to take local actions, for which it receives local rewards. For every agent, DDPG trains a local actor (policy) and a local critic (Q-function). The analysis shows that multi-agent DDPG using neural networks to approximate the local policies and critics converge to limits with the following properties: The critic limits minimize the average squared Bellman loss; the actor limits parameterize a policy that maximizes the local critic's approximation of $Q_i^*$, where $i$ is the agent index. The averaging is with respect to a probability distribution over the global state-action space. It captures the asymptotics of all local training processes. Finally, we extend the analysis to a fully decentralized setting where agents communicate over a wireless network prone to delays and losses; a typical scenario in, e.g., robotic applications.

Learning Realistic Mutations: Bug Creation for Neural Bug Detectors - Richter, Cedric; Wehrheim, Heike (2022 IEEE Conference on Software Testing, Verification and Validation (ICST))

TSSB-3M: Mining single statement bugs at massive scale - Richter, Cedric; Wehrheim, Heike (2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR))

Bringing Structure to Structure-Preserving Signatures: Overview, Implementation and Comparison of Selected SPS Schemes - Siek, Hanna

On Transforming Lattice-Based Cryptography to the Ring Setting - Kramer, Paul

ADAGIO - Automated Data Augmentation of Knowledge Graphs Using Multi-expression Learning - Dreßler, Kevin; Sherif, Mohamed; Ngonga Ngomo, Axel-Cyrille (Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia)
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
Keywords: 2022 RAKI SFB901 deer dice kevin knowgraphs limes ngonga sherif simba

Practical Network Conditions for the Convergence of Distributed Optimization - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (IFAC-PapersOnLine)

XCS on Embedded Systems: An Analysis of Execution Profiles and Accelerated Classifier Deletion - Hansmeier, Tim; Brede, Mathis; Platzner, Marco (GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion)

Analyzing Culture-Specific Argument Structures in Learner Essays - Chen, Wei-Fan; Chen, Mei-Hua; Mudgal, Garima; Wachsmuth, Henning (Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022))

(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling - Maack, Marten; Pukrop, Simon; Rasmussen, Anna Rodriguez (30th Annual European Symposium on Algorithms, ESA 2022, September 5-9, 2022, Berlin/Potsdam, Germany)

Distortion through modeling asymmetric bargaining power - Haake, Claus-Jochen; Streck, Thomas
We study the consequences of modeling asymmetric bargaining power in two-person bargaining problems. Comparing application of an asymmetric version of a bargaining solution to an upfront modification of the disagreement point, the resulting distortion crucially depends on the bargaining solution concept. While for the Kalai-Smorodinsky solution weaker players benefit from modifying the disagreement point, the situation is reversed for the Nash bargaining solution. There, weaker players are better off in the asymmetric bargaining solution. When comparing application of the asymmetric versions of the Nash and the Kalai-Smorodinsky solutions, we demonstrate that there is an upper bound for the weight of a player, so that she is better off with the Nash bargaining solution. This threshold is ultimately determined by the relative utilitarian bargaining solution. From a mechanism design perspective, our results provide valuable information for a social planner, when implementing a bargaining solution for unequally powerful players.
Keywords: Asymmetric bargaining power; Nash bargaining solution; Kalai-Smorodinsky bargaining solution

Light backscattering from numerical analog of planetary regoliths - Grynko, Yevgen; Shkuratov, Yuriy; Alhaddad, Samer; Förstner, Jens
Keywords: tet_topic_scattering

Knowledge Equity and Open Science in qualitative research – Practical research considerations - Steinhardt, Isabel; Kruschick, Felicitas (Research Ideas and Outcomes)
How can Knowledge In/Equity be addressed in qualitative research by taking the idea of Open Science into account? Two projects from the Open Science Fellows Programme by Wikimedia Deutschland will be used to illustrate how Open Science practices can succeed in qualitative research, thereby reducing In/Equity. In this context, In/Equity is considered as a fair and equal representation of people, their knowledge and insights and comprehends questions about how epistemic, structural, institutional and personal biases generate and shape knowledge as guidance. Three questions guide this approach: firstly, what do we understand by In/Equity in the context of knowledge production in these projects? Secondly, who will be involved in knowledge generation and to what extent will they be valued or unvalued? Thirdly, how can data be made accessible for re-use to enable true participation and sharing?
Keywords: Open Science; Knowledge Equity; Qualitative Methods

Asymmetric parametric generation of images with nonlinear dielectric metasurfaces - Kruk, Sergey S.; Wang, Lei; Sain, Basudeb; Dong, Zhaogang; Yang, Joel; Zentgraf, Thomas; Kivshar, Yuri (Nature Photonics)
Subwavelength dielectric resonators assembled into metasurfaces have become a versatile tool for miniaturizing optical components approaching the nanoscale. An important class of metasurface functionalities is associated with asymmetry in both the generation and transmission of light with respect to reversals of the positions of emitters and receivers. The nonlinear light–matter interaction in metasurfaces offers a promising pathway towards miniaturization of the asymmetric control of light. Here we demonstrate asymmetric parametric generation of light in nonlinear metasurfaces. We assemble dissimilar nonlinear dielectric resonators into translucent metasurfaces that produce images in the visible spectral range on being illuminated by infrared radiation. By design, the metasurfaces produce different and completely independent images for the reversed direction of illumination, that is, when the positions of the infrared emitter and the visible light receiver are exchanged. Nonlinearity-enabled asymmetric control of light by subwavelength resonators paves the way towards novel nanophotonic components via dense integration of large quantities of nonlinear resonators into compact metasurface designs.
Keywords: Atomic and Molecular Physics; and Optics; Electronic; Optical and Magnetic Materials

AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development - Maalouly, Jad; Hemker, Dennis; Hedayat, Christian; Rückert, Christian; Kaufmann, Ivan; Olbrich, Marcel; Lange, Sven; Mathis, Harald (2022 Kleinheubach Conference)
In this paper, machine learning techniques will be used to classify different PCB layouts given their electromagnetic frequency spectra. These spectra result from a simulated near-field measurement of electric field strengths at different locations. Measured values consist of real and imaginary parts (amplitude and phase) in X, Y and Z directions. Training data was obtained in the time domain by varying transmission line geometries (size, distance and signaling). It was then transformed into the frequency domain and used as deep neural network input. Principal component analysis was applied to reduce the sample dimension. The results show that classifying different designs is possible with high accuracy based on synthetic data. Future work comprises measurements of real, custom-made PCB with varying parameters to adapt the simulation model and also test the neural network. Finally, the trained model could be used to give hints about the error’s cause when overshooting EMC limits.
Keywords: emc; pcb; electronic system development; machine learning; neural network

Die „dritte Wissensdimension“. Eine Epistemologie für eine neue Wissenswelt - Hagengruber, Ruth Edith (Sitzungsberichte der Leibniz-Sozietät der Wissenschaften 150/151, Jahrgang 2022: „Cyberscience – Wissenschaftsforschung und Informatik. Digitale Medien und die Zukunft der Kultur wissenschaftlicher Tätigkeit. Arbeitskreis „Emergente Systeme/Informatik und Gesellschaft“ der Leibniz-Sozietät der Wissenschaften zu Berlin in Kooperation mit der Gesellschaft für Wissenschaftsforschung“)

Chatbot-Enhanced Requirements Resolution for Automated Service Compositions - Kersting, Joschka; Ahmed, Mobeen; Geierhos, Michaela (HCI International 2022 Posters)
This work addresses the automatic resolution of software requirements. In the vision of On-The-Fly Computing, software services should be composed on demand, based solely on natural language input from human users. To enable this, we build a chatbot solution that works with human-in-the-loop support to receive, analyze, correct, and complete their software requirements. The chatbot is equipped with a natural language processing pipeline and a large knowledge base, as well as sophisticated dialogue management skills to enhance the user experience. Previous solutions have focused on analyzing software requirements to point out errors such as vagueness, ambiguity, or incompleteness. Our work shows how apps can collaborate with users to efficiently produce correct requirements. We developed and compared three different chatbot apps that can work with built-in knowledge. We rely on ChatterBot, DialoGPT and Rasa for this purpose. While DialoGPT provides its own knowledge base, Rasa is the best system to combine the text mining and knowledge solutions at our disposal. The evaluation shows that users accept 73% of the suggested answers from Rasa, while they accept only 63% from DialoGPT or even 36% from ChatterBot.
Keywords: On-The-Fly Computing; Chatbot; Knowledge Base

Methodenentwicklung zur Verbesserung der Schädigungsmodellierung in der numerischen 3D-Belastungssimulation mechanischer Fügeverfahren unter Berücksichtigung der fügeinduzierten Vorbeanspruchung - Otroshi, Mortaza; Meschut, Gerson

Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types - Krauter, Stefan; Bendfeld, Jörg (Proceedings of the 8th World Conference on Photovoltaik Energy Conversion)

Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER - Kakande, Josephine Nakato; Philipo, Godiana Hagile; Krauter, Stefan (Proceedings of the 8th World Conference on Photovoltaik Energy Conversion)

Schädigungsmodellierung von Hilfsfügeelementen beim mechanischen Fügen von Stahlwerkstoffen - Otroshi, Mortaza; Meschut, Gerson

Hardware Trojans in Reconfigurable Computing - Ahmed, Qazi Arbab
Wettstreit zwischen der Entwicklung neuer Hardwaretrojaner und entsprechender Gegenmaßnahmen beschreiten Widersacher immer raffiniertere Wege um Schaltungsentwürfe zu infizieren und dabei selbst fortgeschrittene Test- und Verifikationsmethoden zu überlisten. Abgesehen von den konventionellen Methoden um einen Trojaner in eine Schaltung für ein Field-programmable Gate Array (FPGA) einzuschleusen, können auch die Entwurfswerkzeuge heimlich kompromittiert werden um einen Angreifer dabei zu unterstützen einen erfolgreichen Angriff durchzuführen, der zum Beispiel Fehlfunktionen oder ungewollte Informationsabflüsse bewirken kann. Diese Dissertation beschäftigt sich hauptsächlich mit den beiden Blickwinkeln auf Hardwaretrojaner in rekonfigurierbaren Systemen, einerseits der Perspektive des Verteidigers mit einer Methode zur Erkennung von Trojanern auf der Bitstromebene, und andererseits derjenigen des Angreifers mit einer neuartigen Angriffsmethode für FPGA Trojaner. Für die Verteidigung gegen den Trojaner ``Heimtückische LUT'' stellen wir die allererste erfolgreiche Gegenmaßnahme vor, die durch Verifikation mittels Proof-carrying Hardware (PCH) auf der Bitstromebene direkt vor der Konfiguration der Hardware angewendet werden kann, und präsentieren ein vollständiges Schema für den Entwurf und die Verifikation von Schaltungen für iCE40 FPGAs. Für die Gegenseite führen wir einen neuen Angriff ein, welcher bösartiges Routing im eingefügten Trojaner ausnutzt um selbst im fertigen Bitstrom in einem inaktiven Zustand zu verbleiben: Hierdurch kann dieser neuartige Angriff zur Zeit weder von herkömmlichen Test- und Verifikationsmethoden, noch von unserer vorher vorgestellten Verifikation auf der Bitstromebene entdeckt werden.
Keywords: FPGA Security; Hardware Trojans; Bitstream-level Trojans; Bitstream Verification

Evaluation Criteria in Product Idea Selection Decisions - Gräßler, Iris; Koch, Anna-Sophie (XXXIII Proceedings of the ISPIM Innovation Conference)
Within innovation management, choosing the best fitting product idea is the most important decision point. The future existence and success of the organization is depending on selected product ideas. To find the best fitting idea for an organization, it needs evaluation criteria representing the organizations mission Therefore, this study focuses on a holistic overview about evaluation criteria and on supporting organizations in the process to select its individual evaluation criteria. Based on a literature study, existing approaches regarding evaluation criteria in product idea selection are identified and a list of evaluation criteria is reworked. Using the list of evaluation criteria, a prioritization method is created. Within an interview with experts in innovation management, the method is discussed regarding usability and the level of assistance in product idea selection. The developed criteria can be used directly by innovation manager and industrial practitioners to evaluate potential product ideas.
Keywords: innovation management; evaluation criteria; idea selection; idea evaluation; meta-study

Proaktives Management von Anforderungsänderungen in der Entwicklung komplexer technischer Systeme - Oleff, Christian
Anforderungsänderungen sind ein wesentlicher Grund für Ineffizienzen und Projektfehlschläge in der Entwicklung komplexer technischer Systeme. Proaktives Management von Anforderungsänderungen hat das Potenzial, den Umgang mit Anforderungsänderungen effizienter zu gestalten. Dafür ist ein systematischer Ansatz erforderlich, der eine ganzheitliche Bewertung und Handhabung des Änderungsrisikos im industriellen Entwicklungskontext ermöglicht. Im Rahmen dieser Dissertation wird mit der ProMaRC-Methodik ein neuartiger Ansatz für das proaktive Management von Anforderungsänderungen vorgestellt. Die Methodik wurde in enger Zusammenarbeit mit Industrieanwender:innen aus der Automobilindustrie entwickelt und anhand von fünf Fallstudien validiert. Mittels automatisierter Abhängigkeitsanalyse auf Grundlage künstlicher Intelligenz wird der Anwendungsaufwand gegenüber bestehenden Ansätzen reduziert. Die teilautomatisierte Bewertung und Handhabung der Änderungswahrscheinlichkeit und -auswirkung erfolgt anhand eines modifizierten PageRank-Algorithmus und umfasst erstmalig alle für die Risikoanalyse relevanten Einflussfaktoren. Die Validierung belegt, dass durch die ProMaRC-Methodik eine überzeugende Kombination aus praxistauglichem Anwendungsaufwand und Vollständigkeit der Analyse erzielt wird. Damit erschließt diese Dissertation das bisher kaum beachtete Forschungsfeld des proaktiven Managements von Anforderungsänderungen und fördert eine effizientere Produktentwicklung.

Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis - Kersting, Joschka; Bäumer, Frederik Simon (Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications)
This paper aims at discussing past limitations set in sentiment analysis research regarding explicit and implicit mentions of opinions. Previous studies have regularly neglected this question in favor of methodical research on standard-datasets. Furthermore, they were limited to linguistically less-diverse domains, such as commercial product reviews. We face this issue by annotating a German-language physician review dataset that contains numerous implicit, long, and complex statements that indicate aspect ratings, such as the physician’s friendliness. We discuss the nature of implicit statements and present various samples to illustrate the challenge described.
Keywords: Sentiment analysis; Natural language processing; Aspect phrase extraction

Network Disruption and the Common-Enemy Effect - Hoyer, Britta; De Jaegher, Kris (International Journal of Game Theory)

Blogpost "Von der Grundstimmung als philosophischer Ausgangspunkt" - Lebock, Sarah
BloKK-Beitrag für das ZeKK, 03.12.2022

End-to-End Dereverberation, Beamforming, and Speech Recognition in A Cocktail Party - Zhang, Wangyou; Chang, Xuankai; Boeddeker, Christoph; Nakatani, Tomohiro; Watanabe, Shinji; Qian, Yanmin (IEEE/ACM Transactions on Audio, Speech, and Language Processing)
Far-field multi-speaker automatic speech recognition (ASR) has drawn increasing attention in recent years. Most existing methods feature a signal processing frontend and an ASR backend. In realistic scenarios, these modules are usually trained separately or progressively, which suffers from either inter-module mismatch or a complicated training process. In this paper, we propose an end-to-end multi-channel model that jointly optimizes the speech enhancement (including speech dereverberation, denoising, and separation) frontend and the ASR backend as a single system. To the best of our knowledge, this is the first work that proposes to optimize dereverberation, beamforming, and multi-speaker ASR in a fully end-to-end manner. The frontend module consists of a weighted prediction error (WPE) based submodule for dereverberation and a neural beamformer for denoising and speech separation. For the backend, we adopt a widely used end-to-end (E2E) ASR architecture. It is worth noting that the entire model is differentiable and can be optimized in a fully end-to-end manner using only the ASR criterion, without the need of parallel signal-level labels. We evaluate the proposed model on several multi-speaker benchmark datasets, and experimental results show that the fully E2E ASR model can achieve competitive performance on both noisy and reverberant conditions, with over 30% relative word error rate (WER) reduction over the single-channel baseline systems.

Characterization of Usage Data with the Help of Data Classifications - Panzner, Melina; von Enzberg, Sebastian; Meyer, Maurice; Dumitrescu, Roman (Journal of the Knowledge Economy)
Abstract Comprehensive data understanding is a key success driver for data analytics projects. Knowing the characteristics of the data helps a lot in selecting the appropriate data analysis techniques. Especially in data-driven product planning, knowledge about the data is a necessary prerequisite because data of the use phase is very heterogeneous. However, companies often do not have the necessary know-how or time to build up solid data understanding in connection with data analysis. In this paper, we develop a methodology to organize and categorize and thus understand use phase data in a way that makes it accessible to general data analytics workflows, following a design science research approach. We first present a knowledge base that lists typical use phase data from a product planning view. Second, we develop a taxonomy based on standard literature and real data objects, which covers the diversity of the data considered. The taxonomy provides 8 dimensions that support classification of use phase data and allows to capture data characteristics from a data analytics view. Finally, we combine both views by clustering the objects of the knowledge base according to the taxonomy. Each of the resulting clusters covers a typical combination of analytics relevant characteristics occurring in practice. By abstracting from the diversity of use phase data into artifacts with manageable complexity, our approach provides guidance to choose appropriate data analysis and AI techniques.
Keywords: Economics and Econometrics

Using vibration data to classify conditions in disk stack separators - Merkelbach, Silke; Afroze, Lameya; Janssen, Nils; von Enzberg, Sebastian; Kühn, Arno; Dumitrescu, Roman (Vibroengineering PROCEDIA)
Mounting sensors in disk stack separators is often a major challenge due to the operating conditions. However, a process cannot be optimally monitored without sensors. Virtual sensors can be a solution to calculate the sought parameters from measurable values. We measured the vibrations of disk stack separators and applied machine learning (ML) to detect whether the separator contains only water or whether particles are also present. We combined seven ML classification algorithms with three feature engineering strategies and evaluated our model successfully on vibration data of an experimental disk stack separator. Our experimental results demonstrate that random forest in combination with manual feature engineering using domain specific knowledge about suitable features outperforms all other models with an accuracy of 91.27 %.
Keywords: General Medicine

Soziotechnische Herausforderungen bei der Einführung von RPA managen - Hobscheidt, Daniela; Menzefricke, Jörn Steffen; Gabriel, Stefan; Kühn, Arno; Dumitrescu, Roman (Praxishandbuch Robotic Process Automation (RPA))

Transfer von Arbeit 4.0-Anwendungsszenarien - Bansmann, Michael; Dumitrescu, Roman; Fechtelpeter, Christian (Gestaltung digitalisierter Arbeitswelten)

Nutzung von Process Mining in RPA-Projekten - Brock, Jonathan; von Enzberg, Sebastian; Kühn, Arno; Dumitrescu, Roman (Praxishandbuch Robotic Process Automation (RPA))

Rekonstruktive Evaluationsforschung im Kontext praxeologischer Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen Evaluationsforschung - Bloh, Thiemo (Zeitschrift für Evaluation)
Praxeologische Kompetenzansätze verstehen Kompetenz als sozial erlernt und folglich als relativ zum sozialen Kontext. Damit einher geht die Frage, wie solche praxeologisch gerahmten Kompetenzen eigentlich unabhängig von der sie hervorbringenden Praxis evaluiert werden können – und eben dadurch erst für einen breiteren Kompetenzdiskurs fruchtbar sind. Die Dokumentarische Evaluationsforschung bietet hierzu erste Anhaltspunkte, offenbart aber auch Grenzen, die mit dem Evaluationsverständnis zusammenhängen, sich jedoch in der Forschungspraxis so nicht finden lassen. Aus der Differenz zwischen Methode und Praxis dokumentarischer Evaluation lässt sich formulieren, wie eine praxeologische Evaluation gestaltet werden könnte. Dabei spielt die Formulierung von Referenzrahmen eine zentrale Rolle, welche einerseits der zu evaluierenden Praktik external sein, andererseits praktisch formuliert werden müssen, damit sie soziale Praktiken jenseits ihrer eigenen Sinnhaftigkeit evaluativ (er-)fassen können.
Keywords: Strategy and Management; Applied Psychology; Social Sciences (miscellaneous); Education; Communication; Statistics and Probability

Ein kritisch-multiperspektivischer Blick auf Forschendes Lernen in der Lehrkräftebildung. Fragen, Erwägungen und Rekonstruktionen. - Bloh, Thiemo; Caruso, Carina (die hochschullehre)

Grundlagentheoretische Differenzen in der Lehrkräftekooperationsforschung - Bloh, Thiemo (Zeitschrift für Pädagogik)

Mechanical Properties and Joinability of AlSi9 Alloy Manufactured by Twin‐Roll Casting - Neuser, Moritz; Kappe, Fabian; Ostermeier, Jakob; Krüger, Jan Tobias; Bobbert, Mathias; Meschut, Gerson; Schaper, Mirko; Grydin, Olexandr (Advanced Engineering Materials)
AlSi casting alloys combine excellent castability with high strength. Hence, this group of alloys is often used in the automotive sector. The challenge for this application is the brittle character of these alloys which leads to cracks during joint formation when mechanical joining technologies are used. A rise in ductility can be achieved by a considerable increase in the solidification rate which results in grain refinement. High solidification rates can be realized in twin–roll casting (TRC) by water-cooled rolls. Therefore, a hypoeutectic EN AC–AlSi9 (for European Norm - aluminum cast product) is manufactured by the TRC process and analyzed. Subsequently, joining investigations are performed on castings in as-cast and heat-treated condition using the self-piercing riveting process considering the joint formation and the load-bearing capacity. Due to the fine microstructure, the crack initiation can be avoided during joining, while maintaining the joining parameters, especially by specimens in heat treatment conditions. Furthermore, due to the extremely fine microstructure, the load-bearing capacity of the joint can be significantly increased in terms of the maximum load-bearing force and the energy absorbed.
Keywords: Condensed Matter Physics; General Materials Science

Was bedeutet Post-Digitalität? – Universitäre Lehrpraktiken zwischen situativer Anforderung und habitueller Prägung - Bloh, Thiemo

AussteigerInnen – Fluchtbewegungen in der LehrerInnenbiographie - Bloh, Thiemo

„Referenzrahmen“ als gewinnbringendes Konstrukt im Kontext Dokumentarischer Evaluationsforschung!? - Bloh, Thiemo

The Deconstruction of Professionalism - Bloh, Thiemo

Influence of Kinematic Hardening on Clinch Joining of Dual-Phase Steel HCT590X Sheet Metal - Friedlein, Johannes; Mergheim, Julia; Steinmann, Paul (The Minerals, Metals & Materials Series)
Nowadays, clinching is a widely used joining technique, where sheets are joined by pure deformation to create an interlock without the need for auxiliary parts. This leads to advantages such as reduced joining time and manufacturing costs. On the other hand, the joint strength solely relies on directed material deformation, which renders an accurate material modelling essential to reliably predict the joint forming. The formation of the joint locally involves large plastic strains and possibly complex non-proportional loading paths, as typical of many metal forming applications. Consequently, a finite plasticity formulation is utilised incorporating a Chaboche–Rousselier kinematic hardening law to capture the Bauschinger effect. Material parameters are identified from tension–compression tests on miniature spec- imens for the dual-phase steel HCT590X. The resulting material model is implemented in LS-Dyna to study the locally diverse loading paths and give a quantitative statement on the importance of kinematic hardening for clinching. It turns out that the Bauschinger effect mainly affects the springback of the sheets and has a smaller effect on the joint forming itself.
Keywords: Clinching; Material modelling; Kinematic hardening; Parameter identification; Bauschinger effect

Numerical and experimental identification of fatigue crack initiation sites in clinched joints - Ewenz, L.; Bielak, Christian Roman; Otroshi, Mortaza; Bobbert, Mathias; Meschut, Gerson; Zimmermann, M. (Production Engineering)
In this paper, a study based on experimental and numerical simulations is performed to analyze fatigue cracks in clinched joints. An experimental investigation is conducted to determine the failure modes of clinched joints under cyclic loading at different load amplitudes with single-lap shear tests. In addition, numerical FEM simulations of clinching process and subsequent shear loading are performed to support the experimental investigations by analyzing the state of stresses at the location of failure. An attempt is made to explain the location of crack initiation in the experiments using evaluation variables such as contact shear stress and maximum principal stress.
Keywords: Industrial and Manufacturing Engineering; Mechanical Engineering

Clinching in In Situ CT—A Novel Validation Method for Mechanical Joining Processes - Köhler, Daniel; Kupfer, Robert; Troschitz, Juliane; Gude, Maik (The Minerals, Metals & Materials Series)
Force–displacement measurements and micrograph analyses are commonly used methods to validate numerical models of clinching processes. However, these methods often lead to resetting of elastic deformations and crack- closing after unloading. In contrast, the in situ computed tomography (CT) can provide three-dimensional images of the clinch point under loading conditions. In this paper, the potential of the in situ investigation of a clinching process as validation method is analyzed. For the in situ testing, a tailored test set-up featuring a beryllium cylinder for load-bearing and clinching tools made from ultra-high-strength titanium and Si3N4 are used. In the experiments, the clinching of two aluminum sheets is interrupted at specific process steps in order to perform the CT scans. It is shown that in situ CT visualizes the inner geometry of the joint at high precision and that this method is suitable to validate numerical models.
Keywords: Clinching; Non-destructive testing; Computed tomography; In situ CT

Investigation of the influence of formed, non-rotationally symmetrical pin geometries and their effect on the joint quality of steel and aluminium sheets by direct pin pressing - Römisch, David; Kraus, Martin; Merklein, Marion (Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications)
Resource-saving and sustainable production is becoming increasingly important regarding social, political and economic aspects, thus making the use of lightweight-construction technologies a current trend. For this reason, multi-material-systems made of high-strength steel and aluminium as well as metal and fibre-reinforced plastics gain in importance. However, different material properties, e.g. stiffness, thermal expansion coefficients or chemical incompatibilities, are challenging for conventional joining technologies. Joining by cold formed pin structures has shown to have high potential for joining multi-material-systems. These pins can be joined either by direct pin pressing into an unperforated joining partner or by caulking, where the pins are inserted through a pre-punched joining partner and the pin head is upset, resulting in a form-fit joint. Usually, cylindrical pins are used for joining. However, non-rotationally symmetrical pin geometries offer the possibility of introducing a predetermined breaking point or reinforcing a connection in the principal force direction. In this work, cylindrical pins as well as non-rotationally symmetrical pin geometries, such as polygonal and oval pin structures, are cold extruded from the sheet metal plane of an HCT590X+Z dual phase steel and joined in the next step with an EN AW-6014 aluminium using direct pin pressing. Since the formation of an undercut has an crucial influence on the joint strength, the investigations will be focused on the resulting joint geometry. In addition, the effect of different pin heights will be examined to analyse the joint formation at different levels of compression of the pin structures. Finally, the joints are evaluated regarding their joint strength in tensile shear tests and cross tension tests. Here the flow resistance of the geometry used as well as the pin height and thus the strain hardening of the pin base during the extrusion of the pins play a decisive role for the shear strength.
Keywords: Mechanical Engineering; General Materials Science

Joining of CFRT/Steel Hybrid Parts via Direct Pressing of Cold Formed Non-Rotational Symmetric Pin Structures - Popp, Julian; Römisch, David; Merklein, Marion; Drummer, Dietmar (Applied Sciences)
In this study, quasi-unidirectional continuous fiber reinforced thermoplastics (CFRTs) are joined with metal sheets via cold formed cylindrical, elliptical and polygonal pin structures which are directly pressed into the CFRT component after local infrared heating. In comparison to already available studies, the unique novelty is the use of non-rotational symmetric pin structures for the CFRT/metal hybrid joining. Thus, a variation in the fiber orientation in the CFRT component as well as a variation in the non-rotational symmetric pins’ orientation in relation to the sample orientation is conducted. The created samples are consequently mechanically tested via single lap shear experiments in a quasi-static state. Finally, the failure behavior of the single lap shear samples is investigated with the help of microscopic images and detailed photographs. In the single lap shear tests, it could be shown that non-rotational symmetric pin structures lead to an increase in maximum testing forces of up to 74% when compared to cylindrical pins. However, when normalized to the pin foot print related joint strength, only one polygonal pin variation showed increased joint strength in comparison to cylindrical pin structures. The investigation of the failure behavior showed two distinct failure modes. The first failure mode was failure of the CFRT component due to an exceedance of the maximum bearing strength of the pin-hole leading to significant damage in the CFRT component. The second failure mode was pin-deflection due to the applied testing load and a subsequent pin extraction from the CFRT component resulting in significantly less visible damage in the CFRT component. Generally, CFRT failure is more likely with a fiber orientation of 0° in relation to the load direction while pin extraction typically occurs with a fiber orientation of 90°. It is assumed that for future investigations, pin structures with an undercutting shape that creates an interlocking joint could counteract the tendency for pin-extraction and consequently lead to increased maximum joint strengths.
Keywords: Fluid Flow and Transfer Processes; Computer Science Applications; Process Chemistry and Technology; General Engineering; Instrumentation; General Materials Science

Joining Processes for Fibre-Reinforced Thermoplastics: Phenomena and Characterisation - Troschitz, Juliane; Gröger, Benjamin; Würfel, Veit; Kupfer, Robert; Gude, Maik (Materials)
Thermoplastic composites (TPCs) are predestined for use in lightweight structures, especially for high-volume applications. In many cases, joining is a key factor for the successful application of TPCs in multi-material systems. Many joining processes for this material group are based on warm forming the joining zone. This results in a change of the local material structure characterised by modified fibre paths, as well as varying fibre contents, which significantly influences the load-bearing behaviour. During the forming process, many different phenomena occur simultaneously at different scales. In this paper, the deformation modes and flow mechanisms of TPCs during forming described in the literature are first analysed. Based on this, three different joining processes are investigated: embedding of inserts, moulding of contour joints, and hotclinching. In order to identify the phenomena occurring in each process and to describe the characteristic resulting material structure in the joining zones, micrographs as well as computed tomography (CT) analyses are performed for both individual process stages and final joining zones.