A. Baier, und D. Frank. Software, (2023)Related to: Baier, Alexandra, Boukhers, Zeyd, & Staab, Steffen (2021). Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction. ArXiv, abs/2103.06727. arXiv: abs/2103.06727.
J. Kneifl, und J. Fehr. Software, (2020)Related to: Jonas Kneifl, Dennis Grunert, and Joerg Fehr (2021). A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning. In: International Journal for Numerical Methods in Engineering, 122:4774-4786. doi: 10.1002/nme.6712.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Cristancho, D., Delgado, D., Martínez, F., Abolghassemi Fakhree, M. A., & Jouyban, A. (2011). Volumetric properties of glycerol + water mixtures at several temperatures and correlation with the Jouyban-Acree model. Revista Colombiana de Ciencias Químico Farmacéuticas, 40. 92-115.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Mikhail, S. Z., & Kimel, W. R. (1961). Densities and Viscosities of Methanol-Water Mixtures. Journal of Chemical & Engineering Data, 6(4), 533-537. doi: 10.1021/je60011a015.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
L. Schepp, B. Ahrens, M. Balcewicz, M. Duda, M. Nehler, M. Osorno, D. Uribe, H. Steeb, B. Nigon, F. Stöckhert und 5 andere Autor(en). Dataset, (2020)Related to: Schepp, L.L., Ahrens, B., Balcewicz, M., Duda, M., Nehler, M., Osorno, M., Uribe, D., Steeb, S., Nigon, B., Stöckhert, F., Swanson, D.A., Siegert, M., Gurris, M. & Saenger, E.H. (2020). Digital rock physics and laboratory considerations on a high-porosity volcanic rock. Scientific Reports, 10, 5840. doi: 10.1038/s41598-020-62741-1.
M. Ruf, M. Balcewicz, E. Saenger, und H. Steeb. Dataset, (2021)Related to: Balcewicz, M., Siegert, M., Gurris, M., Ruf, M., Krach, D., Steeb, H., & Saenger, E.H. (2021). Digital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone. Frontiers in Earth Science (under review).
M. Balcewicz, M. Ruf, H. Steeb, und E. Saenger. Dataset, (2021)Related to: Balcewicz, M., Siegert, M., Gurris, M., Ruf, M., Krach, D., Steeb, H., & Saenger, E.H. (2021). Digital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone. Frontiers in Earth Science (under review).
M. Balcewicz, M. Ruf, H. Steeb, und E. Saenger. Dataset, (2021)Related to: Balcewicz, M., Siegert, M., Gurris, M., Ruf, M., Krach, D., Steeb, H., & Saenger, E.H. (2021). Digital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone. Frontiers in Earth Science (under review).
M. Ruf, und H. Steeb. Dataset, (2021)Related to: Ruf, M., & Steeb, H. (2022). Effects of thermal treatment on acoustic waves in Carrara marble. International Journal of Rock Mechanics and Mining Sciences, 159, 105205. doi: 10.1016/j.ijrmms.2022.105205.
L. Nölle, P. Lerge, O. Martynenko, I. Wochner, F. Kempter, C. Kleinbach, S. Schmitt, und J. Fehr. Dataset, (2022)Related to: Kleinbach, C., Martynenko, O., Promies, J., Haeufle, D.F., Fehr, J., Schmitt, S., 2017. Implementation and validation of the extended hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models. Biomedical engineering online 16, 109. doi: 10.1186/s12938-017-0399-7.
M. Ruf, J. Hommel, und H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Ruf, J. Hommel, und H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Ruf, J. Hommel, und H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Rosenfelder, H. Ebel, und P. Eberhard. Dataset, (2023)Related to: Rosenfelder, M., Ebel, H., Eberhard, P. (2023). Force-based organization and control scheme for the non-prehensile cooperative transportation of objects. Robotica, pp. 1-14, 2023. doi: 10.1017/S0263574723001704.
M. Rosenfelder, H. Ebel, und P. Eberhard. Dataset, (2023)Related to: Rosenfelder, M., Ebel, H., Eberhard, P. (2023). A Force-Based Formation Synthesis Approach for the Cooperative Transportation of Objects. In: Petrič, T., Ude, A., Žlajpah, L. (eds) Advances in Service and Industrial Robotics. RAAD 2023. Mechanisms and Machine Science, vol 135. Springer, Cham. doi: 10.1007/978-3-031-32606-6_37.
F. Huber, P. Bürkner, D. Göddeke, und M. Schulte. Dataset, (2023)Related to: Huber, Felix; Bürkner, Paul-Christian; Göddeke, Dominik; Schulte, MiriamKnowledge-Based Modeling of Simulation Behavior for Bayesian OptimizationComputational Mechanics (submitted).