2018

  1. A

    1. B. M. Afkham, A. Bhatt, B. Haasdonk, and J. S. Hesthaven, “Symplectic Model-Reduction with a Weighted Inner Product,” 2018.
    2. Ausschuss für Wissenschaftliche Bibliotheken und Informationssysteme der Deutschen Forschungsgemeinschaft, Ed., “Stärkung des Systems wissenschaftlicher Bibliotheken in Deutschland.” 2018, [Online]. Available: /brokenurl#www.dfg.de/foerderung/info_wissenschaft/2018/info_wissenschaft_18_24/.
  2. B

    1. A. Barth and T. Stüwe, “Weak convergence of Galerkin approximations of stochastic partial  differential equations driven by additive Lévy noise,” Math. Comput. Simulation, vol. 143, pp. 215--225, 2018, [Online]. Available: https://doi.org/10.1016/j.matcom.2017.03.007.
    2. F. Bayer, M. A. Müller, and F. Allgöwer, “On optimal system operation in robust economic MPC,” Automatica, vol. 88, pp. 98--106, 2018, doi: 10.1016/j.automatica.2017.11.007.
    3. B. Becker, B. Guo, K. Bandilla, M. A. Celia, B. Flemisch, and R. Helmig, “An Adaptive Multiphysics Model Coupling Vertical Equilibrium and Full Multidimensions for Multiphase Flow in Porous Media,” WATER RESOURCES RESEARCH, vol. 54, no. 7, pp. 4347–4360, 2018, doi: 10.1029/2017WR022303.
    4. A. Bhatt, J. Fehr, and B. Haasdonk, “Model order reduction of an elastic body under large rigid motion,” Proceedings of ENUMATH 2017, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1919.
    5. A. Bhatt, J. Fehr, and B. Hassdonk, “Model Order Reduction of an Elastic Body under Large Rigid Motion,” in Proceedings of ENUMATH 2017, Voss, Norway, 2018.
    6. A. Bhatt, B. Haasdonk, and B. E. Moore, “Structure-preserving Integration and Model Order Reduction.” 2018.
    7. C. L. Borgman, “Open data, grey data, and stewardship: Universities at the privacy frontier,” Berkeley Tech. LJ, vol. 33, p. 365, 2018.
    8. J. Bosman and B. Kramer, “Open access levels: a quantitative exploration using Web of Science and oaDOI data,” PeerJ Preprints, vol. 6, p. e3520v1, 2018, doi: 10.7287/peerj.preprints.3520v1.
    9. C. Bradley et al., Towards realistic HPC models of the neuromuscular system. 2018.
    10. M. Brehler, M. Schirwon, D. Göddeke, and P. Krummrich, “Modeling the Kerr-Nonlinearity in Mode-Division Multiplexing Fiber  Transmission Systems on GPUs,” in Proceedings of Advanced Photonics 2018, 2018.
    11. W. Brems, “Querdynamische Eigenschaftsbewertung in einem Fahrsimulator,” Dissertation, Springer Vieweg, Wiesbaden, 2018.
    12. C. Brown, N. C. Hong, and M. Jackson, “Software Deposit and Preservation Policy and                    Planning Workshop Report.” 2018, doi: 10.5281/zenodo.1250310.
    13. F. D. Brunner, D. Antunes, and F. Allgöwer, “Stochastic Thresholds in Event-Triggered Control: A Consistent Policy for Quadratic Control,” Automatica, vol. 89, pp. 376--381, 2018, doi: 10.1016/j.automatica.2017.12.043.
    14. N. Brügger and I. Milligan, SAGE HANDBOOK OF WEB HISTORY. S.l.: SAGE PUBLICATIONS, 2018.
    15. T. Brünnette, G. Santin, and B. Haasdonk, “Greedy kernel methods for accelerating implicit integrators for parametric  ODEs,” 2018, vol. Proceedings of ENUMATH 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1767.
    16. P. Buchfink, “Structure-preserving Model Reduction for Elasticity,” Diploma thesis, 2018.
    17. M. Burton, L. Lyon, C. Erdmann, and B. Tijerina, “Shifting to Data Savvy: The Future of Data Science In Libraries,” Mar. 2018.
  3. C

    1. K. Carlberg, L. Brencher, B. Haasdonk, and A. Barth, “Data-driven time parallelism via forecasting,” SIAM J. of Sci. Comp., 2018, [Online]. Available: http://arxiv.org/abs/1610.09049.
  4. D

    1. S. De Marchi, A. Iske, and G. Santin, “Image reconstruction from scattered Radon data by weighted positive  definite kernel functions,” Calcolo, vol. 55, no. 1, p. 2, 2018, doi: 10.1007/s10092-018-0247-6.
    2. C. Dibak, B. Haasdonk, A. Schmidt, F. Dürr, and K. Rothermel, “Enabling Interactive Mobile Simulations Through Distributed Reduced Models,” Pervasive and Mobile Computing, 2018, doi: 10.1016/j.pmcj.2018.02.002.
    3. N.-A. Dreier, M. Altenbernd, C. Engwer, and D. Göddeke, “A high-level C++ approach to manage local errors, asynchrony and  faults in an MPI application,” in Proceedings of 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2018), 2018.
    4. D. Driess et al., “Learning to Control Redundant Musculoskeletal Systems with Neural Networks and SQP: Exploiting Muscle Properties,” in Proc. of the International Conference on Robotics and Automation, 2018.
  5. E

    1. C. Engwer, M. Altenbernd, N.-A. Dreier, and D. G�ddeke, “A high-level C++ approach to manage local errors, asynchrony and  faults in an MPI application,” in Proceedings of the 26th Euromicro International Conference on Parallel,  Distributed and Network-Based Processing (PDP 2018), 2018.
    2. C. Engwer, M. Altenbernd, N.-A. Dreier, and D. Göddeke, “A high-level C++ approach to manage local errors, asynchrony and  faults in an MPI application,” in Proceedings of the 26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2018), 2018.
  6. F

    1. S. Fechter, C.-D. Munz, C. Rohde, and C. Zeiler, “Approximate Riemann solver for compressible liquid vapor flow with  phase transition and surface tension,” Comput. & Fluids, vol. 169, pp. 169–185, 2018, doi: http://dx.doi.org/10.1016/j.compfluid.2017.03.026.
    2. J. Fehr, D. Grunert, A. Bhatt, and B. Haasdonk, “A sensitivity study of error estimation in reduced elastic multibody systems,” Proceedings of MATHMOD 2018, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1920.
    3. J. Fehr, D. Grunert, P. Holzwarth, B. Fröhlich, N. Walker, and P. Eberhard, “Morembs---A Model Order Reduction Package for Elastic Multibody Systems and Beyond,” in Reduced-Order Modeling (ROM) for Simulation and Optimization: Powerful Algorithms as Key Enablers for Scientific Computing, W. Keiper, A. Milde, and S. Volkwein, Eds. Cham: Springer International Publishing, 2018, pp. 141--166.
    4. V. Ferrario, N. Hansen, and J. Pleiss, “Interpretation of cytochrome P450 monooxygenase kinetics by modeling of thermodynamic activity,” J Inorg Biochem, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1764.
    5. T. Fitschen, A. Schlemmer, D. Hornung, H. tom Wörden, U. Parlitz, and S. Luther, “CaosDB - Research Data Management for Complex, Changing, and Automated  Research Workflows.” 2018, [Online]. Available: http://arxiv.org/abs/1801.07653.
    6. B. Flemisch et al., “Benchmarks for single-phase flow in fractured porous media,” Advances in Water Resources, vol. 111, pp. 239--258, 2018, doi: 10.1016/j.advwatres.2017.10.036.
    7. D. Fowler, J. Barratt, and P. Walsh, “Frictionless Data: Making Research Data Quality Visible,” International Journal of Digital Curation, vol. 12, no. 2, pp. 274--285, 2018, doi: 10.2218/ijdc.v12i2.577.
    8. F. Fritzen, B. Haasdonk, D. Ryckelynck, and S. Schöps, “An algorithmic comparison of the Hyper-Reduction and the Discrete  Empirical Interpolation Method for a nonlinear thermal problem,” Math. Comput. Appl. 2018, vol. 23, no. 1, 2018, doi: doi:10.3390/mca23010008.
  7. G

    1. E. Ghobadi et al., “The Influence of Water and Solvent Uptake on Functional Properties of Shape-Memory Polymers,” International Journal of Polymer Science, vol. 2018, p. 7819353, 2018, [Online]. Available: https://doi.org/10.1155/2018/7819353.
    2. E. Ghobadi, M. Elsayed, R. Krause-Rehberg, and H. Steeb, “Demonstrating the Influence of Physical Aging on the Functional Properties of Shape-Memory Polymers,” Polymers, vol. 10, no. 2, p. 107, 2018, doi: 10.3390/polym10020107.
    3. J. Giesselmann, N. Kolbe, M. Lukacova-Medvidova, and N. Sfakianakis, “Existence and uniqueness of global classical solutions to a two species  cancer invasion haptotaxis model,” Accepted for publication in Discrete Contin. Dyn. Syst. Ser. B., 2018, [Online]. Available: https://arxiv.org/abs/1704.08208.
    4. H. Gimperlein, F. Meyer, C. �zdemir, and E. P. Stephan, “Time domain boundary elements for dynamic contact problems,” Computer Methods in Applied Mechanics and Engineering, vol. 333, pp. 147–175, 2018, doi: https://doi.org/10.1016/j.cma.2018.01.025.
    5. H. Gimperlein, F. Meyer, C. �zdemir, D. Stark, and E. P. Stephan, “Boundary elements with mesh refinements for the wave equation.,” Numer. Math., p. (accepted), 2018, [Online]. Available: https://arxiv.org/abs/1801.09736.
    6. S. Glagla-Dietz, “Orcid Als Metadaten-Aggregation Für Die Gnd,” 2018, doi: 10.5281/zenodo.1219071.
    7. K. Gregory, S. J. Khalsa, W. K. Michener, F. E. Psomopoulos, A. de Waard, and M. Wu, “Eleven quick tips for finding research data,” PLOS Computational Biology, vol. 14, no. 4, p. e1006038, 2018, doi: 10.1371/journal.pcbi.1006038.
    8. C. Y. Guo, “Robust Gain-Scheduled Controller Design with a Hierarchical Structure,” 9th IFAC Symposium on Robust Control Design, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1953.
    9. M. Gärtner, U. Hahn, and S. Hermann, “Supporting Sustainable Process Documentation,” in Language Technologies for the Challenges of the Digital Age: 27th International Conference, GSCL 2017, Berlin, Germany, September 13-14, 2017, Proceedings, Cham, 2018, pp. 284--291, doi: 10.1007/978-3-319-73706-5_24.
    10. M. Gärtner, U. Hahn, and S. Hermann, “Preserving Workflow Reproducibility: The RePlay-DH Client as a Tool for Process Documentation,” in Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan, 2018.
    11. M. Günther, D. Häufle, and S. Schmitt, “The basic mechanical structure of the skeletal muscle machinery: One model for linking microscopic and macroscopic scales,” 2018.
    12. M. Günther, D. F. Haeufle, and S. Schmitt, “The basic mechanical structure of the skeletal muscle machinery: One model for linking microscopic and macroscopic scales,” Journal of Theoretical Biology, vol. 456, pp. 137--167, 2018.
  8. H

    1. B. Haasdonk and G. Santin, “Greedy Kernel Approximation for Sparse Surrogate Modeling,” in Reduced-Order Modeling (ROM) for Simulation and Optimization: Powerful  Algorithms as Key Enablers for Scientific Computing, W. Keiper, A. Milde, and S. Volkwein, Eds. Cham: Springer International Publishing, 2018, pp. 21--45.
    2. S. Haesaert, S. Weiland, and C. W. Scherer, A separation theorem for guaranteed $H_2$ performance through matrix inequalities. Automatica, 2018.
    3. D. F. Haeufle, B. Schmortte, H. Geyer, R. Müller, and S. Schmitt, “The benefit of combining neuronal feedback and feed-forward control for robustness in step down perturbations of simulated human walking depends on the muscle function,” Frontiers in Computational Neuroscience, vol. 12, p. 80, 2018.
    4. S. Hallé, R. Khoury, and M. Awesso, “Streamlining the Inclusion of Computer Experiments In a Research Paper.,” IEEE Computer, vol. 51, no. 11, pp. 78–89, 2018, [Online]. Available: http://dblp.uni-trier.de/db/journals/computer/computer51.html#HalleKA18.
    5. T. Holicki and C. W. Scherer, “A Swapping Lemma for Switched Systems,” 9th IFAC Symposium on Robust Control Design, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1955.
    6. T. Holicki and C. W. Scherer, “An IQC theorem for relations: Towards stability analysis of data-integrated systems,” 9th IFAC Symposium on Robust Control Design, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1956.
    7. G. Hübbers, J. Steinberg, A. Gebert, and S. Jakowatz, “Document Deposit Assistant (DDA): Broker-Software zwischen Content-Lieferanten und Open-Access-Repositiorien,” BIT online: Bibliothek, Information, Technologie, vol. 21, no. 5, pp. 405--414, 2018.
  9. I

    1. D. Iglezakis and B. Schembera, “Anforderungen der Ingenieurwissenschaften an das Forschungsdatenmanagement der Universität Stuttgart - Ergebnisse der Bedarfsanalyse des Projektes DIPL-ING,” o-bib. Das offene Bibliotheksjournal, vol. 3, 2018, doi: 10.5282/o-bib/2018H3S46-60.
  10. J

    1. A. Jensch et al., “The tumor suppressor protein DLC1 maintains protein kinase D activity and Golgi secretory function,” Journal of Biological Chemistry, vol. 293, no. 37, pp. 14407–14416, 2018, doi: 14407-14416.
  11. K

    1. B. Kane, R. Kloefkorn, and A. Dedner, “Adaptive Discontinuous Galerkin Methods for flow in porous media,” Proceedings of ENUMATH 2017, the 12th European conference on numerical mathematics and advanced applications, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1928.
    2. M. Katerbow and G. Feulner, “Handreichung Zum Umgang Mit Forschungssoftware.” Zenodo, 2018, doi: 10.5281/zenodo.1172970.
    3. B. Klein, Einführung in Python 3 : für Ein- und Umsteiger, 3., überarbeitete Auflage. München: Hanser, 2018, pp. XVI, 537 Seiten : Diagramme, Illustrationen.
    4. T. Kuhn, J. Dürrwächter, A. Beck, C.-D. Munz, F. Meyer, and C. Rohde, “Uncertainty Quantification for Direct Aeroacoustic Simulations of  Cavity Flows,” 2018. [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1891.
    5. T. Kuhn, J. Dürrwächter, F. Meyer, A. Beck, C. Rohde, and C.-D. Munz, Uncertainty Quantification for Direct Aeroacoustic Simulations of Cavity Flows. 2018.
    6. K. Kuritz and F. Allgöwer, “Broadcast control of oscillating cell populations.” 2018.
    7. K. Kuritz and F. Allgöwer, “Therapy design by broadcast control of oscillating cell populations.” 2018.
    8. K. Kuritz, W. Halter, and F. Allgöwer, “Passivity-based ensemble control for cell cycle synchronization,” Lecture Notes in Control and Information Sciences - Proceedings, 2018, [Online]. Available: http://www.springer.com/de/book/9783319670676.
    9. K. Kuritz, D. Imig, M. Dyck, and F. Allgöwer, “Ensemble control for cell cycle synchronization of heterogeneous cell populations,” IFAC-PapersOnLine, vol. 51, no. 19, pp. 44–47, 2018, doi: https://doi.org/10.1016/j.ifacol.2018.09.034.
    10. K. Kuritz, W. Halter, and F. Allgöwer, “Passivity-based ensemble control for cell cycle synchronization,” in Emerg. Appl. Control Syst. Theory, 1st ed., R. Tempo, S. Yurkovich, and P. Misra, Eds. Springer International Publishing, 2018.
    11. J. Köhler, M. A. Müller, and F. Allgöwer, “Nonlinear reference tracking: An economic model predictive control perspective,” IEEE Transactions on Automatic Control, 2018, doi: 10.1109/TAC.2018.2800789.
    12. J. Köhler, M. A. Müller, and F. Allgöwer, A nonlinear tracking model predictive control scheme using reference generic terminal ingredients. 2018.
    13. M. Köppel, V. Martin, J. Jaffre, and J. E. Roberts, A Lagrange multiplier method for a discrete fracture model for flow in porous media. 2018.
    14. M. Köppel, V. Martin, and J. E. Roberts, A stabilized Lagrange multiplier finite-element method for flow in porous media with fractures. 2018.
    15. T. Köppl, G. Santin, B. Haasdonk, and R. Helmig, “Numerical modelling of a peripheral arterial stenosis using dimensionally  reduced models and kernel methods,” International Journal for Numerical Methods in Biomedical Engineering, vol. 0, no. ja, p. e3095, 2018, doi: 10.1002/cnm.3095.
    16. M. K�ppel, V. Martin, J. Jaffré, and J. E. Roberts, “A Lagrange multiplier method for a discrete fracture model for flow  in porous media,” (submitted), 2018, [Online]. Available: https://hal.archives-ouvertes.fr/hal-01700663v2.
    17. M. K�ppel, V. Martin, and J. E. Roberts, “A stabilized Lagrange multiplier finite-element method for flow in  porous media with fractures,” (submitted), 2018, [Online]. Available: https://hal.archives-ouvertes.fr/hal-01761591.
  12. L

    1. A. Langer, “Investigating the influence of box-constraints on the solution of  a total variation model via an efficient primal-dual method,” Journal of Imaging, vol. 4, p. 1, 2018, [Online]. Available: http://www.mdpi.com/2313-433X/4/1/12.
    2. A. Langer, “Locally adaptive total variation for removing mixed Gaussian-impulse  noise,” International Journal of Computer Mathematics, p. 19, 2018, [Online]. Available: https://www.tandfonline.com/doi/abs/10.1080/00207160.2018.1438603.
    3. A. Langer, “Overlapping domain decomposition methods for total variation denoising,” 2018.
    4. B. D. Lee, “Ten simple rules for documenting scientific software,” PLOS Computational Biology, vol. 14, no. 12, p. e1006561, 2018, doi: 10.1371/journal.pcbi.1006561.
    5. S. Linsenmayer, H. Ishii, and F. Allgöwer, “Containability With Event-Based Sampling for Scalar Systems With Time-Varying Delay and Uncertainty,” IEEE Control Systems Letters, 2018, doi: 10.1109/LCSYS.2018.2847449.
    6. S. Linsenmayer and F. Allgöwer, “Performance oriented triggering mechanisms with guaranteed traffic characterization for linear discrete-time systems,” in Proc. European Control Conf. (ECC), Limassol, Cyprus, 2018, pp. 1474–1479, doi: 10.23919/ECC.2018.8550568.
    7. M. Lotti, J. Pleiss, F. Valero, and P. Ferrer, “Enzymatic production of biodiesel: strategies to overcome methanol inactivation,” Biotechnol J, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1809.
  13. M

    1. B. Maboudi Afkham and J. S. Hesthaven, “Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems,” Journal of Scientific Computing, pp. 1–19, 2018, doi: 10.1007/s10915-018-0653-6.
    2. R. McClatchey, “Data provenance tracking as the basis for a biomedical virtual research environment,” Proceedings of Science, vol. 293, 2018, [Online]. Available: http://eprints.uwe.ac.uk/33527/.
    3. J. Meisner, J. Karwounopoulos, P. Walther, J. Kästner, and S. Naumann, “The Lewis Pair Polymerization of Lactones Using Metal Halides and N-Heterocyclic Olefins: Theoretical Insights,” Molecules, vol. 23, no. 2, 2018, doi: 10.3390/molecules23020432.
    4. F. Meyer, L. Schlachter, and F. Schneider, “A hyperbolicity-preserving discontinuous stochastic Galerkin scheme  for uncertain hyperbolic systems of equations,” 2018. [Online]. Available: https://arxiv.org/abs/1805.10177.
    5. M. Mustermann, “ORCID Test,” Zeitschrift für Autorenidentifikation, vol. 4, pp. 10–31, 2018.
  14. N

    1. A. Nateghi, H. Dal, M.-A. Keip, and C. Miehe, “An affine microsphere approach to modeling strain-induced crystallization in rubbery polymers,” Continuum Mechanics and Thermodynamics, pp. 1--23, 2018, doi: 10.1007/s00161-017-0612-8.
    2. K. Nguyen and M.-A. Keip, “A data-driven approach to nonlinear elasticity,” Computers & Structures, vol. 194, pp. 97--115, 2018, doi: 10.1016/j.compstruc.2017.07.031.
    3. no author, “Choose an open source license | Choose a License,” 15.02.2018. https://choosealicense.com/.
  15. O

    1. E. S. F. on Research Infrastructures, Ed., “ESFRI Roadmap 2018 - Strategy Report on Research Infrastructures,” 2018.
  16. P

    1. D. Paul and N. Radde, “The role of stochastic sequestration dynamics for intrinsic noise filtering in signaling network motifs,” Journal of Theoretical Biology, vol. 455, pp. 86–96, 2018, doi: https://doi.org/10.1016/j.jtbi.2018.07.012.
    2. G. Peng et al., “A Conceptual Enterprise Framework for Managing Scientific Data                          Stewardship,” Data Science Journal, vol. 17, no. 0, p. 15, 2018, doi: 10.5334/dsj-2018-015.
    3. D. Pfander, M. Brunn, and D. Pflüger, “AutoTuneTMP: Auto-Tuning in C++ With Runtime Template Metaprogramming,” 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1892.
    4. D. Pfander, G. Daiß, D. Pflüger, D. Marcello, and H. Kaiser, “Accelerating Octo-Tiger: Stellar Mergers on Intel Knights Landing with HPX,” Proceedings of the 6th International Workshop on OpenCL, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1893.
    5. J. Preskill, “Quantum Computing in the NISQ era and beyond.” 2018, [Online]. Available: http://arxiv.org/abs/1801.00862.
  17. R

    1. G. P. Raja Sekhar, V. Sharanya, and C. Rohde, “Effect of surfactant concentration and interfacial slip on the flow  past a viscous drop at low surface P�clet number,” erscheint bei Int. J. Multiph. Flow, 2018, [Online]. Available: http://arxiv.org/abs/1609.03410.
    2. P. Rehner and J. Gross, “Surface tension of droplets and Tolman lengths of real substances and mixtures from density functional theory,” THE JOURNAL OF CHEMICAL PHYSICS, vol. 148, p. 164703, 2018, doi: 10.1063/1.5020421.
    3. C. Rohde and C. Zeiler, “On Riemann Solvers and Kinetic Relations for Isothermal Two-Phase  Flows with Surface Tension,” Z. Angew. Math. Phys., p. 69:76, 2018, [Online]. Available: https://doi.org/10.1007/s00033-018-0958-1.
    4. P. H. Russell, R. L. Johnson, S. Ananthan, B. Harnke, and N. E. Carlson, “A large-scale analysis of bioinformatics code on GitHub,” PLOS ONE, vol. 13, no. 10, pp. 1–19, Oct. 2018, doi: 10.1371/journal.pone.0205898.
    5. U. Rüde, K. Willcox, L. C. McInnes, and H. D. Sterck, “Research and Education in Computational Science and Engineering.,” SIAM Review, vol. 60, no. 3, pp. 707–754, 2018, [Online]. Available: http://dblp.uni-trier.de/db/journals/siamrev/siamrev60.html#RudeWMS18.
  18. S

    1. M. Sauerwein and H. Steeb, “A modified effective stress principle for chemical active multiphase materials with internal mass exchange,” Geomechanics for Energy and the Environment, vol. 15, pp. 19--34, 2018, doi: 10.1016/j.gete.2018.02.001.
    2. C. W. Scherer and J. Veenman, “Stability analysis by dynamic dissipation inequalities: On merging frequency-domain techniques with time-domain conditions,” Syst. Contr. Letters, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1958.
    3. C. W. Scherer and T. Holicki, “Output-Feedback Gain-Scheduling for a Class of Switched Systems via Dynamic Resetting D-Scalings,” 57th IEEE Conf. Decision and Control, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1957.
    4. T. Schlauch, M. Meinel, and C. Haupt, “DLR Software Engineering Guidelines,” 2018, doi: 10.5281/zenodo.1344612.
    5. A. Schmidt and B. Haasdonk, “Data-driven surrogates of value functions and applications to feedback control for dynamical systems,” MathMod 2018, 2018, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1766.
    6. A. Schmidt, D. Wittwar, and B. Haasdonk, “Rigorous and effective a-posteriori error bounds for nonlinear problems - Application to RB methods,” University of Stuttgart, 2018. [Online]. Available: https://www.ians.uni-stuttgart.de/anm/publications/files_publication_anm/ADH18_preprint.pdf.
    7. M. Schneider, B. Flemisch, R. Helmig, K. Terekhov, and H. Tchelepi, “Monotone nonlinear finite-volume method for challenging grids,” Computational Geosciences, 2018, doi: 10.1007/s10596-017-9710-8.
    8. M. Schneider, T. Koeppl, R. Helmig, R. Steinle, and R. Hilfer, “Stable Propagation of Saturation Overshoots for Two-Phase Flow in Porous Media,” Transport in Porous Media, vol. 121, pp. 621--641, 2018, doi: 10.1007/s11242-017-0977-y.
    9. M. Schneider et al., “Modelling the microstructure and computing effective elastic properties of sand core materials,” International Journal of Solids and Structures, vol. 143, pp. 1--17, 2018, doi: 10.1016/j.ijsolstr.2018.02.008.
    10. D. Seus, K. Mitra, I. S. Pop, F. A. Radu, and C. Rohde, “A linear domain decomposition method for partially saturated flow  in porous media,” Comp. Methods in Appl. Mech. Eng, vol. 333, pp. 331--355, 2018, doi: https://doi.org/10.1016/j.cma.2018.01.029.
    11. D. Suissa, M. Günther, A. Shapiro, I. Melzer, and S. Schmitt, “On Laterally Perturbed Human Stance: Experiment, Model, and Control,” Applied Bionics and Biomechanics, vol. 2018, p. 20, 2018, doi: 10.1155/2018/4767624.
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    1. P. Tempel, F. Trautwein, and A. Pott, Experimental Validation of Cable Strain Dynamics Models of UHMWPE Dyneema Fibers for Improving Cable Tension Control Strategies. Springer Verlag; Springer International Publishing, 2018.
    2. P. Tempel, D. Lee, and A. Pott, Elastic-Flexible Cable Models with Time-Varying Length for Cable-Driven Parallel Robots - A Rayleigh-Ritz Approach. IEEE, 2018.
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