2016

  1. M. Abbaszadeh Shakarab, J. Kadkhodapour, S. Schmauder, and M. Hoseinpour, “A study on the effect of grain dimension on the deformation of stent    struts in tension, bending and unbending loading modes,” INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, vol. 118, pp. 36–44, 2016, doi: 10.1016/j.ijmecsci.2016.09.010.
  2. E. Afgan et al., “The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update,” Nucleic Acids Res., vol. 44, no. W1, pp. W3–W10, 2016.
  3. SS. Agada, S. Geiger, H. ElSheikh, and S. Oladyshkin, “Data-driven surrogates for rapid simulation and optimisation of WAG injection in fractured carbonate reservoirs,” Petroleum Geoscience, 2016, doi: 10.1144/petgeo2016-068.
  4. M. Alkämper, A. Dedner, R. Klöfkorn, and M. Nolte, “The DUNE-ALUGrid Module,” Archive of Numerical Software, vol. 4, pp. 1--28, 2016, doi: 10.11588/ans.2016.1.23252.
  5. M. Alk�mper, A. Dedner, R. Kl�fkorn, and M. Nolte, “The DUNE-ALUGrid Module.,” Archive of Numerical Software, vol. 4, no. 1, pp. 1--28, 2016, doi: 10.11588/ans.2016.1.23252.
  6. F. Allgöwer, “A Sixty-Year-Old Congratulates a Fifty-Year-Old,” AT-AUTOMATISIERUNGSTECHNIK, vol. 64, no. 2, pp. 162–163, 2016, doi: 10.1515/auto-2016-0008.
  7. E. Altan, A. Zöllner, O. Avci, and O. Röhrle, “Towards modelling skeletal muscle growth and adaptation,” Proceedings in Applied Mathematics and Mechanics, vol. 16, pp. 921--924, 2016, doi: 10.1002/pamm.201610448.
  8. M. Altenbernd and D. Göddeke, “Soft fault detection and correction for multigrid,” The International Journal of High Performance Computing Applications, 2016, doi: 10.1177/1094342016684006.
  9. S. Alvarez Barcia, M. Russ, J. Meisner, and J. Kästner, “Atom tunnelling in the reaction NH3+ + H2 --> NH4+ + H and its astrochemical relevance,” Faraday Discuss., 2016, doi: 10.1039/C6FD00096G.
  10. D. Amsallem and B. Haasdonk, “PEBL-ROM: Projection-Error Based Local Reduced-Order Models,” AMSES, Advanced Modeling and Simulation in Engineering Sciences, vol. 3, no. 6, 2016, doi: 10.1186/s40323-016-0059-7.
  11. A. C. Antoulas, B. Haasdonk, and B. Peherstorfer, MORML 2016 Book of Abstracts. University of Stuttgart, 2016.
  12. Y. A. Aoto and A. Köhn, “Revisiting the F plus HCl -> HF plus Cl reaction using a multireference    coupled-cluster method,” PHYSICAL CHEMISTRY CHEMICAL PHYSICS, vol. 18, no. 44, pp. 30241–30253, 2016, doi: 10.1039/c6cp05782a.
  13. Y. A. Aoto and A. Köhn, “Internally contracted multireference coupled-cluster theory in a    multistate framework,” JOURNAL OF CHEMICAL PHYSICS, vol. 144, no. 7, 2016, doi: 10.1063/1.4941604.
  14. H. Artaza et al., “Top 10 metrics for life science software good practices version 1; referees: 2 approved,” F1000Research, vol. 5, no. 2000, 2016, doi: 10.12688/f1000research.9206.1.
  15. S. Bagheri, N. Strohfeldt, F. Sterl, A. Berrier, A. Tittl, and H. Gießen, “Large-Area Low-Cost Plasmonic Perfect Absorber Chemical Sensor    Fabricated by Laser Interference Lithography,” ACS SENSORS, vol. 1, no. 9, pp. 1148–1154, 2016, doi: 10.1021/acssensors.6b00444.
  16. D. S. Banks, C. Tressler, R. D. Peters, F. Höfling, and C. Fradin, “Characterizing anomalous diffusion in crowded polymer solutions and gels    over five decades in time with variable-lengthscale fluorescence    correlation spectroscopy,” SOFT MATTER, vol. 12, no. 18, pp. 4190–4203, 2016, doi: 10.1039/c5sm01213a.
  17. A. Barth, R. Bürger, I. Kröker, and C. Rohde, “Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: a hybrid stochastic Galerkin approach,” Computers & Chemical Engineering, vol. 89, pp. 11--26, 2016, doi: 10.1016/j.compchemeng.2016.02.016.
  18. A. Barth and T. Stüwe, “Weak convergence of Galerkin approximations of stochastic partial differential equations driven by additive Levy noise,” Mathematics and Computers in Simulation, 2016, [Online]. Available: http://arxiv.org/abs/1603.02422.
  19. A. Barth and F. Fuchs, “Uncertainty quantification for hyperbolic conservation laws with flux coefficients given by spatiotemporal random fields,” SISC: Meth. and Alg. for Scientific Computing, 2016, [Online]. Available: http://arxiv.org/abs/1402.2156.
  20. A. Barth, S. Moreno-Bromberg, and O. Reichmann, “A Non-Stationary Model of Dividend Distribution in A Stochastic Interest-Rate Setting,” Computational Economics, vol. 47, no. 3, pp. 447--472, 2016, doi: 10.1007/s10614-015-9502-y.
  21. A. Barth and A. Stein, “Approximation and simulation of infinite-dimensional Lévy processes,” 2016.
  22. A. Barth, C. Schwab, and J. Sukys, “Multilevel Monte Carlo Simulation of Statistical Solutions to the Navier--Stokes Equations,” in Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, April 2014, R. Cools and D. Nuyens, Eds. Cham: Springer International Publishing, 2016, pp. 209--227.
  23. A. Barth, R. B�rger, I. Kröker, and C. Rohde, “Computational uncertainty quantification for a clarifier-thickener  model with several random perturbations: A hybrid stochastic Galerkin  approach,” Computers & Chemical Engineering, vol. 89, pp. 11-- 26, 2016, doi: http://dx.doi.org/10.1016/j.compchemeng.2016.02.016.
  24. A. Barth, R. Burger, I. Kröker, and C. Rohde, “Computational uncertainty quantification for a clarifier-thickener model    with several random perturbations: A hybrid stochastic Galerkin approach,” COMPUTERS & CHEMICAL ENGINEERING, vol. 89, pp. 11–26, 2016, doi: 10.1016/j.compchemeng.2016.02.016.
  25. A. Barth and I. Kröker, “Finite volume methods for hyperbolic partial differential equations  with spatial noise,” in Springer Proceedings in Mathematics and Statistics, vol. submitted, Springer International Publishing, 2016.
  26. A. Barth, R. Burger, I. Kr�ker, and C. Rohde, “Computational uncertainty quantification for a clarifier-thickener model    with several random perturbations: A hybrid stochastic Galerkin approach,” COMPUTERS & CHEMICAL ENGINEERING, vol. 89, pp. 11–26, 2016, doi: 10.1016/j.compchemeng.2016.02.016.
  27. P. Bastian et al., Advances Concerning Multiscale Methods and Uncertainty Quantification in “EXA-DUNE in Software for Exascale Computing -- SPPEXA 2013--2015.” Springer, 2016.
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  29. P. Bastian et al., “Advances Concerning Multiscale Methods and Uncertainty Quantification  in EXA-DUNE,” in Software for Exascale Computing -- SPPEXA 2013--2015, H.-J. Bungartz, P. Neumann, and W. E. Nagel, Eds. Springer, 2016, pp. 25--43.
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  31. U. Baur, P. Benner, B. Haasdonk, C. Himpe, I. Maier, and M. Ohlberger, “Comparison of methods for parametric model order reduction of instationary  problems,” in Model Reduction and Approximation for Complex Systems, P. Benner, A. Cohen, M. Ohlberger, and K. Willcox, Eds. Birkhäuser Publishing, 2016.
  32. F. Bayer, F. D. Brunner, M. Lazar, M. Wijnand, and F. Allgöwer, “A tube-based approach to nonlinear explicit MPC,” 55th IEEE Conference on Decision and Control (CDC), pp. 4059--4064, 2016, doi: 10.1109/CDC.2016.7798884.
  33. F. Bayer, M. A. Müller, and F. Allgöwer, “Min-max economic model predictive control approaches with guaranteed performance,” 55th IEEE Conference on Decision and Control (CDC), pp. 3210--3215, 2016, doi: 10.1109/CDC.2016.7798751.
  34. F. Bayer, M. Lorenzen, M. A. Müller, and F. Allgöwer, “Robust economic Model Predictive Control using stochastic information,” Automatica, vol. 74, pp. 151--161, 2016, doi: 10.1016/j.automatica.2016.08.008.
  35. A. Beck, D. Flad, C. Tonhäuser, G. Gassner, and C.-D. Munz, “On the Influence of Polynomial De-aliasing on Subgrid Scale Models,” Flow Turbulence Combustion, vol. 97, pp. 475--511, 2016, doi: 10.1007/s10494-016-9704-y.
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  37. F. Berner, M. Hermes, S. Lange, and D. Gräser, “Lean Construction in the logistics of underground and road construction    Optimization of construction in constricted conditions,” BAUINGENIEUR, vol. 91, pp. 166–171, 2016.
  38. F. Betancourt and C. Rohde, “Finite-Volume Schemes for Friedrichs Systems with Involutions,” App. Math. Comput., vol. 272, Part 2, pp. 420–439, 2016, doi: 10.1016/j.amc.2015.03.050.
  39. A. Bhatt and B. E. Moore, “Structure-preserving Exponential Runge-Kutta Methods,” SIAM J. Sci Comp, 2016.
  40. A. Bhatt, “Structure-preserving Finite Difference Methods for Linearly Damped  Differential Equations,” University of Central Florida, 2016.
  41. A. Bhatt and B. E. Moore, “Geometric Integration of a Damped Driven Nonlinear Schrodinger Equation.” 2016.
  42. S. Bidier and W. Ehlers, “A homogenisation strategy for micromorphic continua based on particle mechanics,” Proceedings in Applied Mathematics and Mechanics, vol. 16, pp. 515--516, 2016, doi: 10.1002/pamm.201610246.
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  44. R. F. Boisvert, “Incentivizing reproducibility,” Communications of the ACM, vol. 59, no. 10, pp. 5--5, 2016, doi: 10.1145/2994031.
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  46. J. Brown, T. Demeranville, and A. Meadows, “Open Access in Context: Connecting Authors, Publications and Workflows Using ORCID Identifiers,” Publications, vol. 4, no. 4, p. 30, 2016, doi: 10.3390/publications4040030.
  47. V. Bruder, S. Frey, and T. Ertl, “Real-Time Performance Prediction and Tuning for Interactive Volume Raycasting,” SIGGRAPH ASIA 2016 Symposium on Visualization, vol. 7, 2016, doi: 10.1145/3002151.3002156.
  48. F. D. Brunner, M. A. Müller, and F. Allgöwer, “Enhancing Output Feedback MPC for Linear Discrete-time Systems with Set-valued Moving Horizon Estimation,” 55th IEEE Conference on Decision and Control (CDC), pp. 2733--2738, 2016, doi: 10.1109/CDC.2016.7798675.
  49. F. D. Brunner, M. Heemels, and F. Allgöwer, “Robust self-triggered MPC for constrained linear systems: A tube-based approach,” Automatica, vol. 72, pp. 73--83, 2016, doi: 10.1016/j.automatica.2016.05.004.
  50. F. D. Brunner and F. Allgöwer, “A Lyapunov Function Approach to the Event-triggered Stabilization of the Minimal Robust Positively Invariant Set,” 6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, pp. 25--30, 2016, doi: 10.1016/j.ifacol.2016.10.367.
  51. F. D. Brunner, F. A. Bayer, and F. Allgöwer, “Robust Steady State Optimization for Polytopic Systems,” 55th IEEE Conference on Decision and Control (CDC), pp. 4084--4089, 2016, doi: 10.1109/CDC.2016.7798888.
  52. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, ?“-invasive event-triggered and self-triggered control for perturbed linear systems,” 55th IEEE Conference on Decision and Control (CDC), pp. 1346--1351, 2016, doi: 10.1109/CDC.2016.7798453.
  53. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Dynamic Thresholds in Robust Event-Triggered Control for Discrete-Time Linear Systems,” Proceedings of the European Control Conference (2016), pp. 983--988, 2016, doi: 10.1109/ECC.2016.7810417.
  54. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Numerical Evaluation of a Robust Self-Triggered MPC Algorithm,” 6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, pp. 151--156, 2016, doi: 10.1016/j.ifacol.2016.10.388.
  55. M. Burch, R. Woods, R. Netzel, and D. Weiskopf, “The Challenges of Designing Metro Maps,” Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, pp. 195--202, 2016, doi: 10.5220/0005679601950202.
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  61. R. Cavoretto, S. De Marchi, A. De Rossi, E. Perracchione, and G. Santin, “Approximating basins of attraction for dynamical systems via stable  radial bases,” in AIP Conf. Proc., 2016, doi: 10.1063/1.4952177.
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  72. D. Diehl, J. Kremser, D. Kröner, and C. Rohde, “Numerical Solution of Navier-Stokes-Korteweg Systems by Local Discontinuous  Galerkin Methods in Multiple Space Dimensions,” Appl. Math. Comput., vol. 272, Part 2, pp. 309–335, 2016, doi: 10.1016/j.amc.2015.09.080.
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  75. F. I. Dragomirescu, K. Eisenschmidt, C. Rohde, and B. Weigand, “Perturbation solutions for the finite radially symmetric Stefan problem,” INTERNATIONAL JOURNAL OF THERMAL SCIENCES, vol. 104, pp. 386–395, 2016, doi: 10.1016/j.ijthermalsci.2016.01.019.
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