Tao, Y., &; Winkler, M. (2023). Small-signal solutions to a nonlocal cross-diffusion model for interaction of scroungers with rapidly diffusing foragers. Mathematical Models and Methods in Applied Sciences, 33(01), 103–138.https://doi.org/10.1142/s0218202523500045 

Schneider, S. B., Werner, S., Khalili, R., Hecker, A., &; Karl, H. (2022). mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks. IEEE/IFIP Network Operations and Management Symposium (NOMS). IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest.

Holtmann, J., Deantoni, J., &; Fockel, M. (2022). Early timing analysis based on scenario requirements and platform models. Software and Systems Modeling.https://doi.org/10.1007/s10270-022-01002-3 

Lange, S., Hedayat, C., Kuhn, H., &; Hilleringmann, U. (2022). Modeling and Characterization of a 3D Environment for the Design of an Inductively Based Locating Method by Coil Couplings. 2022 Smart Systems Integration (SSI). 2022 Smart Systems Integration (SSI), Grenoble, France.https://doi.org/10.1109/ssi56489.2022.9901416 

Bernemann, S. A., Makowiak, J., Makowiak, J., Bertling, R., Lutters, N., &; Kenig, E. (2022). Development of an innovative separation unit for nitrogen recovery from agricultural waste. ACHEMA Congress, Frankfurt am Main.

Shi, Y., Harzheim, S., Hofmann, M., &; Wallmersperger, T. (2022). A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement. In Material Modeling and Structural Mechanics. Springer International Publishing.https://doi.org/10.1007/978-3-030-97675-0_9 

Protte, M., Fahr, R., &; Quevedo, D. E. (2022). Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy. IEEE Control Systems, 40(6), 57–76.https://doi.org/10.1109/mcs.2020.3019723 

Black, T., &; Winkler, M. (2022). Global weak solutions and absorbing sets in a chemotaxis-Navier–Stokes system with prescribed signal concentration on the boundary. Mathematical Models and Methods in Applied Sciences, 32(01), 137–173.https://doi.org/10.1142/s021820252250004x 

Simo Kamga, L., Meffert, D., Magyar, B., Oehler, M., &; Sauer, B. (2022). Simulative investigation of the influence of surface texturing on the elastohydrodynamic lubrication in chain joints. Tribology International, 171, 107564.https://doi.org/10.1016/j.triboint.2022.107564 

Hein, M., Lopes Dias, N. F., Kokalj, D., Stangier, D., Hoyer, K.-P., Tillmann, W., &; Schaper, M. (2022). On the influence of physical vapor deposited thin coatings on the low-cycle fatigue behavior of additively processed Ti-6Al-7Nb alloy. International Journal of Fatigue, 166, Article 107235.https://doi.org/10.1016/j.ijfatigue.2022.107235 

Hein, M., Lopes Dias, N. F., Kokalj, D., Stangier, D., Hoyer, K.-P., Tillmann, W., &; Schaper, M. (2022). On the influence of physical vapor deposited thin coatings on the low-cycle fatigue behavior of additively processed Ti-6Al-7Nb alloy. International Journal of Fatigue, 166, Article 107235.https://doi.org/10.1016/j.ijfatigue.2022.107235 

Nikfarjam, A., Neumann, A., Bossek, J., &; Neumann, F. (2022). Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &; T. Tu\'76 sar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp. 237–249). Springer International Publishing.https://doi.org/10.1007/978-3-031-14714-2_17 

Garcke, H., Kovács, B., &; Trautwein, D. (2022). Viscoelastic Cahn–Hilliard models for tumor growth. Mathematical Models and Methods in Applied Sciences, 32(13), 2673–2758.https://doi.org/10.1142/s0218202522500634 

Bellomo, N., Outada, N., Soler, J., Tao, Y., &; Winkler, M. (2022). Chemotaxis and cross-diffusion models in complex environments: Models and analytic problems toward a multiscale vision. Mathematical Models and Methods in Applied Sciences, 32(04), 713–792.https://doi.org/10.1142/s0218202522500166 

Delfs, P. (2021). Dreidimensionale Oberflächenanalyse und Topografie-Simulation additiv hergestellter Laser-Sinter Bauteile (Vol. 22). Shaker Verlag GmbH.

Kessler, J., Calcavecchia, F., &; Kühne, T. (2021). Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo. Advanced Theory and Simulations, 4(4), Article 2000269.https://doi.org/10.1002/adts.202000269 

Schulze Darup, M., Alexandru, A. B., Quevedo, D. E., &; Pappas, G. J. (2021). Encrypted Control for Networked Systems: An Illustrative Introduction and Current Challenges. IEEE Control Systems, 41(3), 58–78.https://doi.org/10.1109/mcs.2021.3062956 

Cheng, C., Wang, Z., Jin, Z., Ju, X., Schweizer, S., Tröster, T., &; Mahnken, R. (2021). Non-linear mean-field modelling of UD composite laminates accounting for average asymmetric plasticity of the matrix, debonding and progressive failure. Composites Part B: Engineering, 224, Article 109209.https://doi.org/10.1016/j.compositesb.2021.109209 

Malena, K., Link, C., Mertin, S., Gausemeier, S., &; Trächtler, A. (2021). Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*. VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, 7, 386–395.

Pramanik, S., Andreiev, A., Hoyer, K.-P., &; Schaper, M. (2021). Quasi in-situ analysis of fracture path during cyclic loading of double-edged U notched additively manufactured FeCo alloy. International Journal of Fatigue, 153, Article 106498.https://doi.org/10.1016/j.ijfatigue.2021.106498 

Schemmel, R., Krieger, V., Hemsel, T., &; Sextro, W. (2021). Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization. Microelectronics Reliability, 119, 114077.https://doi.org/10.1016/j.microrel.2021.114077 

Han, D., Yang, K., &; Meschut, G. (2021). Mechanical joining of glass fibre reinforced polymer (GFRP) through an innovative solid self-piercing rivet. Journal of Materials Processing Technology, 296, Article 117182.https://doi.org/10.1016/j.jmatprotec.2021.117182 

Rossel, M. S., Böhnke, M., Bielak, C. R., Bobbert, M., &; Meschut, G. (2021). Development of a Method for the Identification of Friction Coefficients in Sheet Metal Materials for the Numerical Simulation of Clinching Processes. Sheet Metal 2021, 883, 81–88.https://doi.org/10.4028/www.scientific.net/KEM.883.81 

Schroder, D., Lange, S., Hangmann, C., &; Hedayat, C. (2020). Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs. In Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis (1st ed., pp. 315-346 (32)). Croyton, UK:https://doi.org/10.1049/pbcs072e_ch14__The Institution of Engineering and Technology (IET).https://doi.org/10.1049/pbcs072e_ch14 

Bielak, C. R., Böhnke, M., Beck, R., Bobbert, M., &; Meschut, G. (2020). Numerical analysis of the robustness of clinching process considering the pre-forming of the parts . Journal of Advanced Joining Processes. .https://doi.org/10.1016/j.jajp.2020.100038 

Krauter, S., Rustemovic, D., &; Khatibi, A. (2020). Reduction of required storage capacities for a 100% renewable energy supply in Germany, if new PV systems are installed with east-west tracking systems at increased elevation angles. Proceedings of the 37th European Photovoltaic Solar Energy Conference, 07 - 11 September 2020, 1818–1819.https://doi.org/10.4229/EUPVSEC20202020-6BV.5.10 

Yigitbas, E., Jovanovikj, I., Biermeier, K., Sauer, S., &; Engels, G. (2020). Integrated model-driven development of self-adaptive user interfaces. Software and Systems Modeling, 19(5), 1057–1081.https://doi.org/10.1007/s10270-020-00777-7 

Nijholt, E., Rink, B. W., &; Schwenker, S. (2020). Quiver Representations and Dimension Reduction in Dynamical Systems. SIAM Journal on Applied Dynamical Systems, 19(4), 2428–2468.https://doi.org/10.1137/20m1345670 

Black, T. (2020). Global generalized solutions to a forager–exploiter model with superlinear degradation and their eventual regularity properties. Mathematical Models and Methods in Applied Sciences, 30(06), 1075–1117.https://doi.org/10.1142/s0218202520400072 

Schlichtig, M., Opel, S. A., Budde, L., &; Schulte, C. (2019). Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material. In E. Jasut &; S. Pozdniakov (Eds.), ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives, Local Proceedings (Vol. 12, pp. 65–73).

Opdemom, H. (2019). Experimentelle Untersuchung einse modifzierten Nasspressverfahrens für die Herstellung von hybriden Metall-Faserverbundkunststoff-Bauteilen: Vol. 2019,35. Shaker Verlag.

Bornmann, P. (2019). Modellierung und experimentelle Charakterisierung der Wechselwirkung zwischen Ultraschallwandler und Flüssigkeit in kavitationsbasierten Prozessen. Shaker.

Awais, M., Ghasemzadeh Mohammadi, H., &; Platzner, M. (2018). An MCTS-based Framework for Synthesis of Approximate Circuits. In 26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC) (pp. 219–224).https://doi.org/10.1109/VLSI-SoC.2018.8645026 

Anderski, J., Mahlert, L., Sun, J., Birnbaum, W., Mulac, D., Schreiber, S., Herrmann, F., Kuckling, D., &; Langer, K. (2018). Light-responsive nanoparticles based on new polycarbonate polymers as innovative drug delivery systems for photosensitizers in PDT. International Journal of Pharmaceutics, 557, 182–191.https://doi.org/10.1016/j.ijpharm.2018.12.040 

Sievers, S., Klobucnik, J., &; Miersch, D. (2017). Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence.https://doi.org/10.2139/ssrn.2237757 

Dunst, P., Hemsel, T., &; Sextro, W. (2017). Analysis of pipe vibration in an ultrasonic powder transportationsystem. Elsevier, Sensors and Actuators A 263, 733–736.

Klobucnik, J., Miersch, D., &; Sievers, S. (2017). Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence. SSRN Electronic Journal.

Althoff, S., Meyer, T., Unger, A., Sextro, W., &; Eacock, F. (2016). Shape-Dependent Transmittable Tangential Force of Wire Bond Tools. In IEEE 66th Electronic Components and Technology Conference (pp. 2103–2110).https://doi.org/10.1109/ECTC.2016.234 

Polevoy, G., Trajanovski, S., &; de Weerdt, M. M. (2014). Nash Equilibria in Shared Effort Games. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems (pp. 861–868). Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems.

King, T. C., Liu, Q., Polevoy, G., de Weerdt, M., Dignum, V., van Riemsdijk, M. B., &; Warnier, M. (2014). Request Driven Social Sensing. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems (pp. 1651–1652). Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems.

Frölich, D., Magyar, B., &; Sauer, B. (2014). A comprehensive model of wear, friction and contact temperature in radial shaft seals. Wear, 311(1), 71–80.https://doi.org/10.1016/j.wear.2013.12.030 

Vollmer, A.-L., Grizou, J., Lopes, M., Rohlfing, K., &; Oudeyer, P.-Y. (2014). Studying the Co-Construction of Interaction Protocols in Collaborative Tasks with Humans. 2014 Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, 208–215.

Schumann, J. H., Wünderlich, N., &; Zimmer, M. S. (2012). Culture’s Impact on Customer Motivation to Engage in Professional Service Enactments. Schmalenbach Business Review, 64(2), 141–165.

Hunstig, M., Hemsel, T., &; Sextro, W. (2012). An efficient simulation technique for high-frequency piezoelectric inertia motors. In Ultrasonics Symposium (IUS), 2012 IEEE International (pp. 277–280).https://doi.org/10.1109/ULTSYM.2012.0068 

Karátson, J., &; Kovács, B. (2012). Variable preconditioning in complex Hilbert space and its application to the nonlinear Schrödinger equation. Computers &;amp; Mathematics with Applications, 65(3), 449–459.https://doi.org/10.1016/j.camwa.2012.04.021 

Kretzschmar, N., &; Schöppner, V. (2010). Simulating Tightly Intermeshing, Co-Rotating Twin Screw Extruders with SIGMA. In Proceedings of the 2010 Summer Computer Simulation Conference (pp. 133–140). San Diego, CA, USA: Society for Computer Simulation International.

Maiterth, R., Houben, H., Broekelschen, W., Müller, J., &; Sureth-Sloane, C. (2009). Mikroanalytische Begleitung der Steuerpolitik am Beispiel der Erbschaftsteuerreform. Statistik Und Wissenschaft, 163--183.

Zabel, H., Müller, W., &; Gerstlauer, A. (2009). Accurate RTOS Modelling and Analysis with SystemC. In W. Ecker, W. Müller, &; R. Dömer (Eds.), Hardware Dependent Software - Principles and Practice (pp. 233–260). Springer Verlag.https://doi.org/10.1007/978-1-4020-9436-1_9 

Vollmer, A.-L., Lohan, K. S., Fischer, K., Nagai, Y., Pitsch, K., Fritsch, J., Rohlfing, K., &; Wrede, B. (2009). People modify their tutoring behavior in robot-directed interaction for action learning. Development and Learning, 2009. ICDL 2009. IEEE 8th International Conference on Development and Learning, 1–6.https://doi.org/10.1109/DEVLRN.2009.5175516 

Zabel, H., &; Müller, W. (2008). An Efficient Time Annotation Technique in Abstract RTOS Simulations for Multiprocessor Task Migration (L. Kleinjohann &; B. Kleinjohann, Eds.; Vol. 271). Springer Verlag.https://doi.org/10.1007/978-0-387-09661-2_18 

Enzler, R., Plessl, C., &; Platzner, M. (2005). System-level performance evaluation of reconfigurable processors. Microprocessors and Microsystems, 29(2–3), 63–73.https://doi.org/10.1016/j.micpro.2004.06.004 

Schattkowsky, T., &; Müller, W. (2005). A UML Virtual Machine for Embedded Systems. Proceedings of ISNG 05.

Enzler, R., Plessl, C., &; Platzner, M. (2003). Co-simulation of a Hybrid Multi-Context Architecture. In Proc. Int. Conf. on Engineering of Reconfigurable Systems and Algorithms (ERSA) (pp. 174–180). CSREA Press.

Mahnken, R., Tikhomirov, D., &; Stein, E. (2002). Implicit integration scheme and its consistent linearization for an elastoplastic-damage model with application to concrete. Computers &;amp; Structures, 75(2), 135–143.https://doi.org/10.1016/s0045-7949(99)00089-9 

Mahnken, R. (2002). Improved implementation of an algorithm for non-linear isotropic/kinematic hardening in elastoplasticity. Communications in Numerical Methods in Engineering, 15(10), 745–754.https://doi.org/10.1002/(sici)1099-0887(199910)15:10&#60;745::aid-cnm288&#62;3.0.co;2-r 

Mahnken, R. (2002). A comprehensive study of a multiplicative elastoplasticity model coupled to damage including parameter identification. Computers &;amp; Structures, 74(2), 179–200.https://doi.org/10.1016/s0045-7949(98)00296-x 

Mahnken, R., &; Stein, E. (2002). The identification of parameters for visco-plastic models via finite-element methods and gradient methods. Modelling and Simulation in Materials Science and Engineering, 2(3A), 597–616.https://doi.org/10.1088/0965-0393/2/3a/013 

Plessl, C., &; Maurer, S. (2000). Hardware/Software Codesign in Speech Compression Applications. Computer Engineering and Networks Lab, ETH Zurich, Switzerland.

Börger, E., Glässer, U., &; Müller, W. (1995). A Formal Definition of an Abstract VHDL’93 Simulator by EA-Machines. In C. Delgado Kloos &; P. T. Breuer (Eds.), Semantics of VHDL (pp. 107–139). Kluwer Academic Publishers.https://doi.org/10.1007/978-1-4615-2237-9_5 

Lasser, R., &; Rösler, M. (1991). Linear mean estimation of weakly stationary stochastic processes under the aspects of optimality and asymptotic optimality. Stochastic Processes and Their Applications, 38(2), 279–293.https://doi.org/10.1016/0304-4149(91)90095-t