Master Thesis - Physic-Driven Machine Learning for Solid Mechanics in High Temperature Gas Turbine ApplicationBackground
Siemens Energy Finspång develops and manufactures gas turbines for power generation and operation of compressors and pumps. Siemens Energy is also a total contractor for distribution and transmission projects in Sweden, and provides total solutions in electrification, automation and digitalization for the process and basic industries.
Gas turbines are designed to operate during long periods of time and in tough environments. This puts high demand on the turbine components regarding their life cycle. One ambition is to predict the behavior of different components using machine learning. One method is to use Multi Objective Optimization. The number of design points required results in more or less good results. To minimize the simulation time in optimization loops a need for more efficient simulation techniques is needed. By replacing finite element modelling with surrogate models trained with machine learning algorithms will speed up the MDO work.
The task for this master thesis is to implement findings from literature to a solid mechanic approach. Including geometries loaded by rotation, gas pressure and high temperatures will further stretch the knowledge in this area.Objectives
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- Perform a literature review regarding Physic Driven Machine Learning (report)
- Implement from literature an elastic-plastic thermomechanical set up with simplified geometry (preferably with possibility to compare results with analytical solution)
- Further develop Machine Learning features by adding more loads (pressure, rotational, temperature and contacts)
- Write a Master Thesis report
LET'S TALK ABOUT US
- AI/Machine learning with some experience in solid/fluid mechanics
- Skilled in coding in Python
- Interested in design automatization and optimization
- Open minded and curious
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Job & Career: https://www.siemens-energy.com/global/en/company/jobs.htmlApplication
Don't hesitate - apply via https://jobs.siemens-energy.com/jobs id nr 224283 not later than 2021-05-23.
For questions about the role, please contact the recruiting manager Dr Olle Skrinjar on tel. 0737455581
For questions about the recruitment process please contact the responsible recruiter Nelly Johansson on tel. 0122-81505.
After applying for the Master thesis position the selection of suitable candidates will be based on a multiple choise test and a programming assignment that will be sent out to all candidates.
Location: FinspångTrade Union Representatives:
Veronica Andersson, Unionen, 0122-840 21
Simon Von Eckardstein, Sveriges Ingenjörer, 0122-842 24
Jan Lundgren, Ledarna, 0122-812 33
Jonny Persson, IF Metall, 0122-817 69