Fachbeiträge 2023

  • Kirschbaum, S. / Powilleit, M. / Schotte, M. / Özbeg, F.: Efficient Solving of Time-Coupled Energy System MILP Models Using a Problem Specific LP Relaxation. In: Proceedings of the 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2023), pp. 2774 - 2785.
  • Koddenbrock, M. / Heinze, H.: Condition Monitoring of a Mechanical Pulsatile Heart Support System via Support-Vector Machine. In: Part of the Lecture Notes in Computer Science book series (LNCS,volume 13765), Conference paper, First Online: 11 February 2023, DOI: https://doi.org/10.1007/978-3-031-26236-4_6.
  • May, M. / Krämer, M. / Schlundt, M. (Eds.): BIM in Real Estate Operations – Application, Implementation, Digitalization Trends and Case Studies. Springer Nature, Wiesbaden, 2023, Print: ISBN 978-3-658-40829-9, eBook: ISBN 978-3-658-40830-5.
  • May, M. / Opić, M.:  Neue Zertifizierung von FM-Spezialsoftware. In: Der Facility Manager, 30 (9) 2023, S. 46 – 48. ISSN 0947-0026.
  • Ashworth, S. / May, M.: The Built Environment, BIM and the FM Perspective. In: BIM in Real Estate Operations, pp. 1 - 17, DOI: 10.1007/978-3-658-40830-5_1.
  • May, M. et al.: Digitalization Trends in Real Estate Management. In: BIM in Real Estate Operations, pp. 19 - 68, DOI: 10.1007/978-3-658-40830-5_2.
  • Krämer, M.et al.: BIM Basics for Real Estate and Facility Managers. In: BIM in Real Estate Operations, pp. 69-98, DOI: 10.1007/978-3-658-40830-5_3.
  • Schlundt, M. et al.: Data Management and Data Exchange for BIM and FM. In: BIM in Real Estate Operations, pp. 129-146, DOI: 10.1007/978-3-658-40830-5_5.
  • May, M. et al.: BIM in FM Applications. In: BIM in Real Estate Operations, pp. 177-198, DOI: 10.1007/9_8.
  • Schlundt, M. et al.: BIM in Real Estate and Facility Management – Case Studies. In: BIM in Real Estate Operations, pp. 199-259, DOI: 10.1007/978-3-658-40830-5_9.
  • Krämer, M. et al.: BIM Perspectives in Real Estate Operations. In: BIM in Real Estate Operations, pp. 261-277, DOI: 10.1007/978-3-658-40830-5_10.
  • Schmeißer, A. et al.: Simulation-based setting suggestions for yarn winding units to reduce color variation in knitted fabric. In: Textile Research Journal 2023. Online verfügbar unter https://doi.org/10.1177/00405175221145908.
  • Schmies, L. et al.: Classification of fracture characteristics and fracture mechanisms using deep learning and topography data. In: Practical Metallography, Volume 60, Issue 2, pp. 76 - 92, Jan. 2023, DOI: 10.1515/pm-2022-1008.
  • Wasserfall, J. / Ouso, M. / Kirschbaum, S.: Simplified Dispatching Method for Unlocking Energy Flexibilities of Decentralized Energy Systems for the Day-ahead and Balancing Power Market. In: Proceedings of the 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2023), pp. 2491 - 2502.
  • Wrobel, G. / Scheffler, R.: Classification for the Concrete Syntax of Graph-Like Modeling Languages. In: SN Computer Science 2023, DOI: 10.1007/s42979-022-01574-3, Online verfügbar unter https://link.springer.com/article/10.1007/s42979-022-01574-3.