Tarik Sahin M.Sc.

Professur für Computergestützte Simulation im Bauingenieurwesen
Gebäude 41/100, Zimmer 5125
+49 89 6004-3788

Tarik Sahin M.Sc.

Academic Career

since 02/2021 Research and Teaching Associate, Institute for Mathematics and Computer-Based Simulation, University of the Bundeswehr Munich

Master of Science,  Computational Engineering,

Master's thesis: Tetrahedral Mesh Refinement, a collaboration of MTU Aero Engines and the Institute of Structural Mechanics Ruhr University Bochum


Graduate Research Assistant, Institute of Lightweight, Steel and Composite Structures, Ruhr University Bochum


Graduate Research Assistant, Institute of Structural Mechanics, Ruhr University Bochum


Bachelor of Science, Aerospace Engineering, Middle East Technical University

Bachelor's thesis: Design, Analysis, and Production of a Vertical Take-off and Landing Aircraft (VTOL)

Research Focus

  • Hybrid Digital Twins
  • Physics-Informed Neural Networks (PINNs) for solving computational mechanics problems
  • Combination of classical simulation methods with Machine Learning and Deep Learning (Data-driven simulations)
  • Numerical methods, solvers, optimization


Use case 1: Hertz contact problem FEM vs PINNs


Use case 2: Prediction of beam deflection via PINNs with a wall scenario. 


Preprints and Articles Submitted for Publication

  1. Sahin, T., Wolff, D., von Danwitz, M., & Popp, A. (2024). Towards a Hybrid Digital Twin: Physics-Informed Neural Networks as Surrogate Model of a Reinforced Concrete Beam. Preprint, submitted for publication arXiv web-logo.png

Conference Proceedings (with Peer-Review)

  1. von Danwitz M, Kochmann T, Sahin T, Wimmer J, Braml T, Popp A (2023): Hybrid Digital Twins: A Proof of Concept for Reinforced Concrete Beams. Proceedings in Applied Mathematics and Mechanics, 22(1): e202200146, DOI (Open Access) doi.png
  2. Milani, R., Sahin, T., von Danwitz, M., Moll, M., Popp, A., Pickl, S. (2023). Automatic concrete bridge crack detection from strain measurements: A preliminary study. In: Critical Information Infrastructures Security. CRITIS 2022. Lecture Notes in Computer Science, vol 13723, Hämmerli, B., Helmbrecht, U., Hommel, W., Kunczik, L., Pickl, S. (Eds) . Springer, Cham, Germany, DOI (Open Access) doi.png

Articles in Peer-Reviewed International Journals

  1. Sahin, T., von Danwitz, M.,  Popp A. (2024): Solving forward and inverse problems of contact mechanics using physics-informed neural networks. Adv. Model. and Simul. in Eng. Sci. 11, 11 (2024), DOI (Open Access) doi.png

International Conference Contributions with Abstract

  • Sahin, T.: Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks, 10th GACM Colloquium on Computational Mechanics 2023, Vienna, Austria, September 11 - 13, 2023.
  • Sahin T.: Physics-Informed Neural Networks With Hard Constraints for Solid and Contact Mechanics, Math 2 Product Conference, Taormina, Italy, May 30 - June 1, 2023. 
  • Sahin, T.: Solving Forward and Inverse Problems of Solid and Contact Mechanics using Physics-Informed Neural Networks, 9th GACM Colloquium on Computational Mechanics 2022, Essen, Germany, September 21 - 23, 2022.
  • Sahin, T., von Danwitz, M., Popp A.: Physics-Informed Neural Networks for Solid and Contact Mechanics, 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics, Aachen, Germany, August 15 - 19, 2022
  • Sahin, T., Popp A.: Simulation-assisted deep learning approach for predicting the real contact area and the contact pressure, Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (MMLDT-CSET), San Diego, California, September 26 - 29, 2021


Courses & Exercises

Supervised Student Projects / Theses

  1. Simulationsgestützte Machine Learning-Ansätze zur Vorhersage der maximalen Durchbiegung eines Trägers (2022)
  2. Implementierung von Physik-Informierten Neuronalen Netzen in der Elastizitätstheorie unter Verwendung 2D-Rechengebieten (2022)
  3. Optimierung der Hyperparameter für Physik-informierte Neuronale Netze (2023)