Dr. Görtz earned his M.Sc. in Mechanical Engineering from Darmstadt University of Technology, Germany, and his M.Sc. in Vehicle Engineering and his Ph.D. in Aeronautical Engineering from the Royal Institute of Technology (KTH), Sweden. After a short-term research position at the Swedish Defence Research Agency (FOI), he performed his post-doctoral research at the US Air Force Academy.
Dr. Görtz joined DLR’s Institute of Aerodynamics and Flow Technology in 2006. He is the head of the Aerodynamic Surrogates and Optimization Group, which is part of the Center for Computer Applications in AeroSpace Science and Engineering (C²A²S²E).
He is the principle investigator of the DLR project VicToria (Virtual Aircraft Technology Integration Platform), which addresses DLR’s guiding concept “The Virtual Product” and aims at virtualizing the aircraft design, development and manufacturing processes, including the definition of an appropriate validation strategy.
His present research interests are in numerical methods for predicting aerodynamic data for loads, handling qualities and performance based on high-fidelity CFD, including surrogate and reduced modelling methods, in methods for uncertainty quantification and robust design, and in collaborative multi-disciplinary optimization.
1. N. Kroll, M. Abu-Zurayk, D. Dimitrov, T. Franz, T. Führer, T. Gerhold, S. Görtz, R. Heinrich, C. Ilic, J. Jepsen, J. Jägersküpper, M. Kruse, A. Krumbein, S. Langer, D. Liu, R. Liepelt, L. Reimer, M. Ritter, A. Schwöppe, J. Scherer, F. Spiering, R. Thormann, V. Togiti, D. Vollmer, J.-H. Wendisch, „DLR Project Digital-X: Towards Virtual Aircraft Design and Flight Testing based on High-Fidelity Methods,“ CEAS Aeronautical Journal, Vol. 7, No. 1, p. 3-27, 2016.
2. D. Maruyama, D. Liu, S. Görtz, ”An Efficient Aerodynamic Shape Optimization Framework for Robust Design of Airfoils Using Surrogate Models, in Proceedings of the ECCOMAS Congress 2016, Crete Island, Greece,5 – 10 June 2016.
3. S. Görtz, C. Ilic, M. Abu-Zurayk, R. Liepelt, J. Jepsen, T. Führer, R. Becker, J. Scherer, T. Kier, M. Siggel, “Collaborative Multi-Level MDO Process Development and Application To Long-Range Transport Aircraft,” ICAS Paper 2016_0345, in Proceedings of the 30th Congress of the International Council of the Aeronautical Sciences (ICAS), Daejeon, South-Korea, 25-30 September, 2016.
4. D. Liu, S. Görtz, “Efficient Quantification of Aerodynamic Uncertainty due to Random Geometry Perturbations,” in Dillmann, A.; Heller, G.; Krämer, E.; Kreplin, H.-P.; Nitsche, W.; Rist, U. (Eds.), New Results in Numerical and Experimental Fluid Mechanics IX, Contributions to the 18th STAB/DGLR Symposium, Stuttgart, Germany 2012, Notes on Numerical Fluid Mechanics and Multidisciplinary Design, Vol. 124, pp. 65-73, 2014.
5. T. Franz, R. Zimmermann, S. Görtz, N. Karcher, „Interpolation-based Reduced-order Modeling for Steady Transonic Flows via Manifold Learning,” in Special Issue: Reduced order modelling: the road towards real-time simulation of complex physics, International Journal of Computational Fluid Dynamics, Volume 28, Issue 3-4, 2014.
6. Z. H. Han, S. Görtz, R. Zimmermann, ”Improving variable-fidelity surrogate modeling via gradient-enhanced kriging and a generalized hybrid bridge function,” Journal of Aerospace Science and Technology, Volume 25, Issue 1, Pages 177–189, March 2013.