SWZ  >  
Forschungsgebiete  >  


Folgende Veröffentlichungen sind im Rahmen der vom SWZ geförderten Projekte entstanden:


  • H.-T. Luu, S.-L. Dang, T.-V. Hoang und N. Gunkelmann. Molecular dynamics simulation of nanoindentation in Al and Fe: On the influence of system characteristics. Appl. Surf. Science 551:149221, 2021.
  • H. Song, N. Gunkelmann, G. Po und S. Sandfeld. Data-mining of dislocation microstructures: concepts for coarse-graining of internal energies. MSMSE 29:035005, 2021.


  • K. C. Le, S. L. Dang, H.-T. Luu und N Gunkelmann. Thermodynamic dislocation
    theory: Application to bcc-crystals. MSMSE 29(1): 015003, 2020.
  • H.-T. Luu, R. J. Ravelo, M. Rudolph, E. M. Bringa, T. C. Germann, D. Rafaja und N. Gunkelmann, Shock-induced plasticity in nanocrystalline iron:
    Large-scale molecular dynamics simulations, Phys. Rev. B 102, 020102(R), 2020.
  • Y. Rosandi, H.-T. Luu, H. M. Urbassek und N. Gunkelmann, Molecular Dynamics Simulations of the Mechanical Behavior of Alumina Coated Aluminum Nanowires under Tension and Compression, RSC Advances,  10, 1435, 2020
  • N. Gunkelmann und M. Merkert,  Improved energy minimization of iron carbon systems: On the influence of positioning interstitial atoms, MSMSE 28(4) , 045005, 2020.
  • H.-J. Stromberg, N. Gunkelmann und A. Lohrengel In: Simulation Science, Second International Workshop, SimScience 2019: Communications in Computer and Information Science (CCIS), 1199, 153. Springer, Cham, 2020



  • N. Gunkelmann, E. M. Bringa und Y. Rosandi, Molecular Dynamics Simulations of Aluminium Foams under Tension: Influence of Oxidation, J. Phys. Chem. C 122, 26243, 2018.



  • V. Honsel, S. Herbold and Jens Grabowski. Learning from Software Project Histories: Predictive Studies Based on Mining Software Repositories, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD)  2016 - NEKTAR Track.

  • D. Honsel, V. Honsel, M. Welter, S. Waack and Jens Grabowski. Monitoring Software Quality by Means of Simulation Methods, 10th International Symposium on Empirical Software Engineering and Measurement (ESEM), 2016.
  • V. Honsel, S. Herbold and Jens Grabowski. Hidden Markov Models for the Prediction of Developer Involvement Dynamics and Workload, 12th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2016).


  • V. Honsel, D. Honsel, J. Grabowski and Stephan Waack. Developer Oriented and Quality Assurance Based Simulation of Software Processes, Proceedings of the Seminar Series on Advanced Techniques & Tools for Software Evolution (SATToSE) 2015.
  • V. Honsel, Statistical Learning and Software Mining for Agent Based Simulation of Software Evolution, Doctoral Symposium at the 37th International Conference on Software Engineering (ICSE 2015), Florence, Italy.
  • V. Honsel, D. Honsel, S. Herbold, J. Grabowski and S. Waack; Mining Software Dependency Networks for Agent-Based Simulation of Software Evolution, The 4th International Workshop on Software Mining, 2015.
  • H. Richter, About the Suitability of Clouds in High-Performance Computing, to be published in Proc. ISC Cloud&Big Data, Sept. 28–30, Frankfurt, Germany, 2015.
  • T. Ahlbrecht, J. Dix and F. Schlesinger. From Testing Agent Systems to a Scalable Simulation Platform. In T. Eiter et al. (Eds.): Brewka Festschrift, LNAI 9060, pp. 47-62. Springer International Publishing Switzerland, 2015.
  • H. Richter and A. Keidel and R. Ledyayev, Über die Eignung von Clouds für das Hochleistungsrechnen (HPC), in IfI Technical Report Series ISSN 1860-8477, IfI-15-03, editor: Department of Computer Science, Clausthal University of Technology, Germany, 2015.