@article{54649, author = {{Borgert, Thomas and Nordieker, Ansgar Bernhard and Wiens, Eugen and Homberg, Werner}}, issn = {{2666-3309}}, journal = {{Journal of Advanced Joining Processes}}, publisher = {{Elsevier BV}}, title = {{{Investigations to improve the tool life during thermomechanical and incremental forming of steel auxiliary joining elements}}}, doi = {{10.1016/j.jajp.2024.100185}}, volume = {{9}}, year = {{2024}}, } @article{61413, abstract = {{Climate change has led to a large number of countries deciding to reduce carbon dioxide (CO2) emissions significantly. As the mobility sector is a major contributor to CO2, various strategies are being pursued to achieve the climate targets set. An increasingly applied lightweight design method is the use of multi-material constructions. To join these structures, mechanical joining technologies such as self-pierce riveting are being used. As a result of the currently rigid tool systems, which cannot react to changing boundary conditions, a large number of rivet–die combinations is required to join the rising number of materials as well as material thickness combinations. Thus, new, versatile joining technologies are needed that can react to the described changes. The versatile self-piercing riveting (V-SPR) process is one possible approach. In this process, different material thicknesses can be joined by using a multi-range capable rivet which is set by a joining system with extended actuator technology. In this study, the V-SPR joining process is analysed numerically according to the influence of the geometrical rivet parameters on the joints characteristics as well as the resulting material flow. The investigations showed that the shank geometry has a decisive influence on the expansion of the rivet. Furthermore, the rivet length could be proven to be an influencing factor. By changing the head radii and the protrusion height, the forming behaviour of the rivet head onto the punch-sided joining part could be improved and thus the formation of air pockets was prevented. Based on the numerical investigations, a novel rivet geometry was developed and produced by machining. Subsequently, experimentally produced joints were analysed according to their joint formation and load-bearing capacity.}}, author = {{Kappe, Fabian and Bobbert, Mathias and Meschut, Gerson}}, issn = {{0954-4089}}, journal = {{Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering}}, publisher = {{SAGE Publications}}, title = {{{Investigation of the influence of the rivet geometry on joint formation for a versatile self-piercing riveting process}}}, doi = {{10.1177/09544089241263141}}, year = {{2024}}, } @inproceedings{57898, author = {{Kruse, Simon and Elsner, Andreas and Paul, Andreas and Kasper, Tina}}, keywords = {{Haushaltskältegeräte, Energieaufnahme, Alterung}}, location = {{Dresden}}, title = {{{Anstieg der Energieaufnahme von Haushaltskältegeräten}}}, year = {{2024}}, } @article{58342, author = {{Bode, Christoph and Goetz, Stefan and Wartzack, Sandro}}, issn = {{2212-8271}}, journal = {{Procedia CIRP}}, pages = {{151--156}}, publisher = {{Elsevier BV}}, title = {{{On the transferability of nominal surrogate models to uncertainty consideration of clinch joint characteristics}}}, doi = {{10.1016/j.procir.2024.10.027}}, volume = {{129}}, year = {{2024}}, } @article{62025, abstract = {{ABSTRACTThis paper deals with micromagnetic measurements for online detection of strain‐induced α′‐martensite during plastic deformation of metastable austenitic steel AISI 304L. The operating principles of the sensors are magnetic Barkhausen noise (MBN) and eddy currents (EC), which are suitable for detection of microstructure evolution due to formation of ferromagnetic phases. The focus of this study was put on the qualification of different micromagnetic techniques and different measurement systems under conditions similar to the real ones during production, which is crucial for implementation of a property‐controlled flow forming process. The investigation was carried out on tubular specimens produced by flow forming, which have different content of α′‐martensite. To characterize the sensitivity of the sensors, different contact conditions between sensors and workpieces were reproduced. MBN sensors are suitable for detecting amount of α′‐martensite, but the measurements are affected by the surface roughness. This entails that the calibration models for MBN sensors must take account of these effects. EC sensors show a closer match with the amount of α′‐martensite without having major affectation by other effects.}}, author = {{Rozo Vasquez, Julian and Kanagarajah, Hanigah and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, issn = {{2577-8196}}, journal = {{Engineering Reports}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Barkhausen Noise‐ and Eddy Current‐Based Measurements for Online Detection of Deformation‐Induced Martensite During Flow Forming of Metastable Austenitic Steel AISI 304L}}}, doi = {{10.1002/eng2.13070}}, volume = {{7}}, year = {{2024}}, } @article{62053, abstract = {{ABSTRACTThis paper deals with micromagnetic measurements for online detection of strain‐induced α′‐martensite during plastic deformation of metastable austenitic steel AISI 304L. The operating principles of the sensors are magnetic Barkhausen noise (MBN) and eddy currents (EC), which are suitable for detection of microstructure evolution due to formation of ferromagnetic phases. The focus of this study was put on the qualification of different micromagnetic techniques and different measurement systems under conditions similar to the real ones during production, which is crucial for implementation of a property‐controlled flow forming process. The investigation was carried out on tubular specimens produced by flow forming, which have different content of α′‐martensite. To characterize the sensitivity of the sensors, different contact conditions between sensors and workpieces were reproduced. MBN sensors are suitable for detecting amount of α′‐martensite, but the measurements are affected by the surface roughness. This entails that the calibration models for MBN sensors must take account of these effects. EC sensors show a closer match with the amount of α′‐martensite without having major affectation by other effects.}}, author = {{Rozo Vasquez, Julian and Kanagarajah, Hanigah and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, issn = {{2577-8196}}, journal = {{Engineering Reports}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Barkhausen Noise‐ and Eddy Current‐Based Measurements for Online Detection of Deformation‐Induced Martensite During Flow Forming of Metastable Austenitic Steel AISI 304L}}}, doi = {{10.1002/eng2.13070}}, volume = {{7}}, year = {{2024}}, } @article{56604, abstract = {{This manuscript makes the claim of having computed the 9th Dedekind number, D(9). This was done by accelerating the core operation of the process with an efficient FPGA design that outperforms an optimized 64-core CPU reference by 95x. The FPGA execution was parallelized on the Noctua 2 supercomputer at Paderborn University. The resulting value for D(9) is 286386577668298411128469151667598498812366. This value can be verified in two steps. We have made the data file containing the 490 M results available, each of which can be verified separately on CPU, and the whole file sums to our proposed value. The paper explains the mathematical approach in the first part, before putting the focus on a deep dive into the FPGA accelerator implementation followed by a performance analysis. The FPGA implementation was done in Register-Transfer Level using a dual-clock architecture and shows how we achieved an impressive FMax of 450 MHz on the targeted Stratix 10 GX 2,800 FPGAs. The total compute time used was 47,000 FPGA hours.}}, author = {{Van Hirtum, Lennart and De Causmaecker, Patrick and Goemaere, Jens and Kenter, Tobias and Riebler, Heinrich and Lass, Michael and Plessl, Christian}}, issn = {{1936-7406}}, journal = {{ACM Transactions on Reconfigurable Technology and Systems}}, number = {{3}}, pages = {{1--28}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{A Computation of the Ninth Dedekind Number Using FPGA Supercomputing}}}, doi = {{10.1145/3674147}}, volume = {{17}}, year = {{2024}}, } @article{57311, author = {{Yang, Keke and Sowada, Matthias and Olfert, Viktoria and Seitz, Georg and Schreiber, Vincent and Heitmann, Marcel and Hein, David and Biegler, Max and Jüttner, Sven and Rethmeier, Michael and Meschut, Gerson}}, issn = {{2238-7854}}, journal = {{Journal of Materials Research and Technology}}, publisher = {{Elsevier BV}}, title = {{{Influence of liquid metal embrittlement on the failure behavior of dissimilar spot welds with advanced high-strength steel: A component study}}}, doi = {{10.1016/j.jmrt.2024.11.166}}, year = {{2024}}, } @inproceedings{56670, abstract = {{Systems Engineering is becoming increasingly important in the engineering of complex technical systems. Its introduction is forcing companies to undertake major transformation initiatives. As established change management approaches show, the corporate culture is an important key criterion for success of transformation. Therefore, when introducing Systems Engineering into an organization, transformation initiatives must be tailored to an existing corporate culture or the corporate culture itself must be changed in order to enable Systems Engineering. In literature and in industrial practice, different approaches for assessment of corporate culture exist. Within this research, a systematic literature review on methods and models for corporate culture assessment is conducted. Core elements are collected and combined with the fundamentals and success factors of Systems Engineering to develop a model for corporate culture assessment. The developed model is applied to the industrial practice of an ongoing Systems Engineering transformation of a large car manufacturer. The results of the assessment are compared with the emerging project challenges. Based on this model and its supporting tool and templates, organizations and transformation leaders are enabled to rapidly obtain an orientation of hindering or supporting currently established cultural aspects with regard to Systems Engineering transformation and to provide a decision basis for further measures.}}, author = {{Graessler, Iris and Grewe, Benedikt}}, booktitle = {{AHFE International}}, issn = {{2771-0718}}, publisher = {{AHFE International}}, title = {{{Importance of cultural change in Systems Engineering Transformation: A model for cultural assessment}}}, doi = {{10.54941/ahfe1005551}}, volume = {{158}}, year = {{2024}}, } @inproceedings{56346, author = {{Gräßler, Iris and Özcan, Deniz}}, booktitle = {{AHFE International}}, location = {{Split}}, publisher = {{AHFE International}}, title = {{{Quality Key Figures for Developing Future Scenarios}}}, doi = {{10.54941/ahfe1005553}}, volume = {{158}}, year = {{2024}}, } @article{62767, abstract = {{Abstract In this study, we develop a novel multi-fidelity deep learning approach that transforms low-fidelity solution maps into high-fidelity ones by incorporating parametric space information into an autoencoder architecture. This method’s integration of parametric space information significantly reduces the amount of training data needed to effectively predict high-fidelity solutions from low-fidelity ones. In this study, we examine a two-dimensional steady-state heat transfer analysis within a heterogeneous materials microstructure. The heat conductivity coefficients for two different materials are condensed from a 101  $$\times $$ ×  101 grid to smaller grids. We then solve the boundary value problem on the coarsest grid using a pre-trained physics-informed neural operator network known as Finite Operator Learning (FOL). The resulting low-fidelity solution is subsequently upscaled back to a 101  $$\times $$ ×  101 grid using a newly designed enhanced autoencoder. The novelty of the developed enhanced autoencoder lies in the concatenation of heat conductivity maps of different resolutions to the decoder segment in distinct steps. Hence the developed algorithm is named microstructure-embedded autoencoder (MEA). We compare the MEA outcomes with those from finite element methods, the standard U-Net, and an interpolation approach as an upscaling technique. Our analysis shows that MEA outperforms these methods in terms of computational efficiency and error on representative test cases. As a result, the MEA serves as a potential supplement to neural operator networks, effectively upscaling low-fidelity solutions to high-fidelity while preserving critical details often lost in traditional upscaling methods, such as sharp interfaces features lost in the context of interpolation approaches.}}, author = {{Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}}, issn = {{0178-7675}}, journal = {{Computational Mechanics}}, number = {{4}}, pages = {{1377--1406}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space}}}, doi = {{10.1007/s00466-024-02568-z}}, volume = {{75}}, year = {{2024}}, } @article{62770, abstract = {{AbstractThe open-source parameter identification tool ADAPT (A diversely applicable parameter identification Tool) is integrated with a machine learning-based approach for start value prediction in order to calibrate a Gurson–Tvergaard–Needleman (GTN) and a Lemaitre damage model. As representative example case-hardened steel 16MnCrS5 is elaborated. An artificial neural network (ANN) is initially trained by using load–displacement curves derived from simulations of a boundary value problem—instead of using data generated for homogeneous states of deformation at material point or one-element level—with varying material parameter combinations. The ANN is then employed so as to predict sets of material parameters that already provide close solutions to the experiment. These predicted parameter sets serve as starting values for a subsequent multi-objective parameter identification by using ADAPT. ADAPT allows for the consideration of input data from multiple scales, including integral data such as load–displacement curves, full-field data such as displacement and strain fields, and high-resolution experimental void data at the micro-scale. The influence of each data set on prediction quality is analyzed. Using various types of input data introduces additional information, enhancing prediction accuracy. The validation is carried out with respect to experimental void measurements of forward rod extruded parts. The results demonstrate, by incorporating void measurements in the optimization process, that it is possible to improve the quantitative prediction of ductile damage in the sense of void area fractions by factor 28 in forward rod extrusion.}}, author = {{Gerlach, Jan and Schulte, Robin and Schowtjak, Alexander and Clausmeyer, Till and Ostwald, Richard and Tekkaya, A. Erman and Menzel, Andreas}}, issn = {{0939-1533}}, journal = {{Archive of Applied Mechanics}}, number = {{8}}, pages = {{2217--2242}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification}}}, doi = {{10.1007/s00419-024-02634-1}}, volume = {{94}}, year = {{2024}}, } @article{62768, author = {{Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}}, issn = {{0013-7944}}, journal = {{Engineering Fracture Mechanics}}, publisher = {{Elsevier BV}}, title = {{{A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties}}}, doi = {{10.1016/j.engfracmech.2024.110675}}, volume = {{314}}, year = {{2024}}, } @article{62999, abstract = {{PurposeAcademic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.Design/methodology/approachUsing data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.FindingsOur analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.Originality/valueOur results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.}}, author = {{Herwald, Sarah and Voigt, Simone and Uhde, André}}, issn = {{1526-5943}}, journal = {{The Journal of Risk Finance}}, number = {{3}}, pages = {{510--536}}, publisher = {{Emerald}}, title = {{{The impact of market concentration and market power on banking stability – evidence from Europe}}}, doi = {{10.1108/jrf-03-2023-0075}}, volume = {{25}}, year = {{2024}}, } @article{63262, abstract = {{AbstractRadially symmetric global unbounded solutions of the chemotaxis system $$\left\{ {\matrix{{{u_t} = \nabla \cdot (D(u)\nabla u) - \nabla \cdot (uS(u)\nabla v),} \hfill & {} \hfill \cr {0 = \Delta v - \mu + u,} \hfill & {\mu = {1 \over {|\Omega |}}\int_\Omega {u,} } \hfill \cr } } \right.$$ { u t = ∇ ⋅ ( D ( u ) ∇ u ) − ∇ ⋅ ( u S ( u ) ∇ v ) , 0 = Δ v − μ + u , μ = 1 | Ω | ∫ Ω u , are considered in a ball Ω = BR(0) ⊂ ℝn, where n ≥ 3 and R > 0.Under the assumption that D and S suitably generalize the prototypes given by D(ξ) = (ξ + ι)m−1 and S(ξ) = (ξ + 1)−λ−1 for all ξ > 0 and some m ∈ ℝ, λ >0 and ι ≥ 0 fulfilling $$m + \lambda < 1 - {2 \over n}$$ m + λ < 1 − 2 n , a considerably large set of initial data u0 is found to enforce a complete mass aggregation in infinite time in the sense that for any such u0, an associated Neumann type initial-boundary value problem admits a global classical solution (u, v) satisfying $${1 \over C} \cdot {(t + 1)^{{1 \over \lambda }}} \le ||u( \cdot ,t)|{|_{{L^\infty }(\Omega )}} \le C \cdot {(t + 1)^{{1 \over \lambda }}}\,\,\,{\rm{for}}\,\,{\rm{all}}\,\,t > 0$$ 1 C ⋅ ( t + 1 ) 1 λ ≤ | | u ( ⋅ , t ) | | L ∞ ( Ω ) ≤ C ⋅ ( t + 1 ) 1 λ f o r a l l t > 0 as well as $$||u( \cdot \,,t)|{|_{{L^1}(\Omega \backslash {B_{{r_0}}}(0))}} \to 0\,\,\,{\rm{as}}\,\,t \to \infty \,\,\,{\rm{for}}\,\,{\rm{all}}\,\,{r_0} \in (0,R)$$ | | u ( ⋅ , t ) | | L 1 ( Ω \ B r 0 ( 0 ) ) → 0 as t → ∞ for all r 0 ∈ ( 0 , R ) with some C > 0.}}, author = {{Winkler, Michael}}, issn = {{0021-2172}}, journal = {{Israel Journal of Mathematics}}, number = {{1}}, pages = {{93--127}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Complete infinite-time mass aggregation in a quasilinear Keller–Segel system}}}, doi = {{10.1007/s11856-024-2618-9}}, volume = {{263}}, year = {{2024}}, } @article{63346, abstract = {{ Lightweight design by using low-density and load-adapted materials can reduce the weight of vehicles and the emissions generated during operation. However, the usage of different materials requires innovative joining technologies with increased versatility. In this investigation, the focus is on describing and characterising the failure behaviour of connections manufactured by an innovative thermomechanical joining process with adaptable auxiliary joining elements in single-lap tensile-shear tests. In order to analyse the failure development in detail, the specimens are investigated using in-situ computed tomography (in-situ CT). Here, the tensile-shear test is interrupted at points of interest and CT scans are conducted under load. In addition, the interrupted in-situ testing procedure is validated by comparing the loading behaviour with conventional continuous tensile-shear tests. The results of the in-situ investigations of joints with varying material combinations clearly describe the cause of failure, allowing conclusions towards an improved joint design. }}, author = {{Borgert, Thomas and Köhler, D and Wiens, Eugen and Kupfer, R and Troschitz, J and Homberg, Werner and Gude, M}}, issn = {{1464-4207}}, journal = {{Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications}}, number = {{12}}, pages = {{2299--2306}}, publisher = {{SAGE Publications}}, title = {{{In-situ computed tomography analysis of the failure mechanisms of thermomechanically manufactured joints with auxiliary joining element}}}, doi = {{10.1177/14644207241232233}}, volume = {{238}}, year = {{2024}}, } @unpublished{56289, author = {{Seeger, Karl and Genovese, Matteo and Schlüter, Alexander and Kockel, Christina and Corigliano, Orlando and Díaz Canales, Edith Benjamina and Fragiacomo, Petronilla and Praktiknjo, Aaron}}, booktitle = {{United States Association for Energy Economics (USAEE) & International Association for Energy Economics (IAEE) Research Paper Series}}, publisher = {{Elsevier BV}}, title = {{{Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment}}}, year = {{2024}}, } @inproceedings{56357, author = {{Díaz Canales, Edith Benjamina and Avila , Alfredo and Schlüter, Sabine and Lacayo, Erick and Schlüter, Alexander}}, booktitle = {{19th Conference on Sustainable Development of Energy, Water and Environment Systems}}, location = {{Rome}}, publisher = {{ Faculty of Mechanical Engineering and Naval Architecture, Zagreb}}, title = {{{Implementing Strategic Environmental Assessment (SEA) in the Global South, a challenge: Nicaragua as a case study.}}}, year = {{2024}}, } @misc{64977, author = {{Mersch, Katharina Ulrike}}, booktitle = {{Deutsches Archiv für Erforschung des Mittelalters}}, number = {{2}}, pages = {{722}}, title = {{{Brown, Warren: Beyond the Monastery Walls. 2023, xiv, 385 S.: Illustrationen, Karten. - ISBN 978-1-108-47958-5}}}, volume = {{80}}, year = {{2024}}, } @inproceedings{65052, author = {{Albrecht, Mirko and Bialaschik, Max Oliver and Gehde, Michael and Schöppner, Volker}}, booktitle = {{AIP Conference Proceedings}}, issn = {{0094-243X}}, publisher = {{AIP Publishing}}, title = {{{Serial hot gas welding - Heating and welding behaviour of a slot nozzle}}}, doi = {{10.1063/5.0192316}}, volume = {{3181}}, year = {{2024}}, }