Turbine Development Engineer / R&D Project Manager

Led an R&D project to establish Machine Learning and Set-Based Concurrent Engineering for engineering optimization as core competencies of the company’s R&D, in collaboration with ABB’s Corporate Research Center in Switzerland. Developed new engineering design processes from scratch, incl. probabilistic design, and a supporting arsenal of Python code for the semi-automated design of complex mechanical components and their interfaces with CAD, FEA and CFD, and modularized legacy Fortran 77 and C++ programs to enable embarassingly-parallel computation on cutting-edge HPC Linux cluster infrastructure.

Turbine Development team, Turbocharger R&D

• Design of turbines/vanes/shafts/threads for performance, efficiency, reliability, TCO.
• Machine Learning for simulation-based engineering design and optimization.
• R&D project management for simulation-based engineering design optimization.
• Modularization of in-house computational tools for massive parameter studies.
• Monte-Carlo-based modeling of shaft loads and semi-automated shaft optimization.
• Discovery of new mixed modes of hub/blade burst for radial turbines.
• Massively parallelizable system for evaluation of blade resonance modes.
• Fully automated optimization of threaded shaft/compressor connectors.
• FEA (Abaqus), CFD (FINE Turbo), Python 2, FORTRAN 77, C++, Linux, HPC cluster.

“Due to his excellent, quick grasp of concepts, Mr. Tsalicoglou recognized problems immediately and acted in a solution-oriented manner. […] highly helpful and reliable nature […] high level of quality consciousness and very precise and efficient method of working […] very accommodating to changes.” — at ABB