Next generation turbomachinery with two-phase flow

The green transition of energy systems requires the implementation of a number of novel emerging energy conversion technologies based on turbomachinery with two-phase flow. However, the current level of knowledge and understanding of two-phase flow in turbomachinery is at a very low level, urgently calling for the need of education of scientists that can support the development of such technologies. The aim of Training42Phase is to educate the future leading scientists within turbomachinery with two-phase flow, thereby providing the scientific and technological basis required for the development of the next generation of turbomachinery. The project consortium includes all the key partners needed to address these challenging tasks and provide our group of 10 doctoral candidates with the best foundation for solving these challenges – leading European universities, and industrial partners from large international companies and SMEs, representing technology suppliers and providers of digitalized solutions. Training42phase will provide a first of its kind excellent training for 10 doctoral candidates within the following fields:
1) Innovative technological solutions that enable the design of cost-effective and reliable turbomachinery with two-phase flow.
2) Cutting-edge multi-disciplinary training in all fields related to the modelling, design, optimization and performance prediction of turbomachinery with two-phase flow, including aero-thermal modelling and design, stress and fatigue analysis, structural dynamics, hybrid/data-driven failure mechanism models, advanced optimization methods and data-driven analytic techniques based on machine learning.
3) Application of turbomachinery with two-phase flow to emerging novel technologies.
4) Top-level training in transferable skills, such as research and data management, scientific integrity and ethics, intellectual property rights and entrepreneurship, business planning, career planning and grant proposal writing.

Funding: This project has received funding from the European Union’s research and innovation programme Horizon Europe under the Marie Skłodowska-Curie Actions Doctoral Networks (MSCA-DN) grant agreement no. 101120366. The financial support is gratefully acknowledged.

Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.