Master thesis - Impact of experimental uncertainty of engine data in compressor aerodynamics design

Job Description

Are you a master student planning to write your Master Thesis during spring 2020? Join us on our journey into the future #Siemens


Be part of an open and dynamic workplace where professional and personal development is high on the agenda. By making sustainable energy solutions more cost effective, developing new technologies for the future's smart industry and electrifying passenger and freight transport, we make reality of our vision of a sustainable world.


We are now looking for a student to take on the assignment “Impact of experimental uncertainty of engine data in compressor aerodynamics design.”


The assignment:

Designing a multi-stage axial compressor brings together various aerodynamic and structural challenges. Siemens has a long history for producing and designing high efficient compressors. There is still potential to increase the aerodynamic performance even further. In order to achieve a reasonable benefit, numerical tools are required to be robust and trustworthy. These numerical tools are validated against engine/test data. Therefore, achieving a high-quality aerodynamic test data is of prime importance in all aspect of aerodynamic designs. At the end, these data provide calibration factors for the numerical outcome that goes into the actual performance of the engine.


In general, a vast number of measurement equipment, probes are installed during the prototype tests and all these measurements have systematic and random errors. The various designs of the performance probes influence the outcome that goes into the overall performance. In this project experimental uncertainty of the engine data should be analyzed in detail mainly from aerodynamic/thermodynamic point of view. The influence of different measurement on the overall performance, for instance mass flow and efficiency, should be pointed out. These experimental uncertainties calculation should be incorporated into existing routine. The project should provide guidelines about how to improve the data quality and evaluation routines.


This assignment is to be performed by one student. We would prefer the work to commence in January/February 2020 and to be finished by the summer.


 

Your Profile: 
The project fits you who…

  • Is studying a master’s degree in mechanical engineering or similar

  • Has taken courses related to fluid mechanics/turbomachinery, measurement techniques and basic understanding of gas turbines

  • Is a well-driven person with a problem-solving mindset

  • Has good English language skill

Application:

Do not hesitate - apply today via siemens.se/jobb ref nr 186759 and no later than 2019-11-24.

For questions about the role please contact Ranjan Saha (ranjan.saha@siemens.com) or Sara Rabal Carrera (sara.rabal@siemens.com). For questions about the recruitment process contact the responsible recruiter Evelina Sundqvist +46 (0) 122 84711.

 

Trade Union representatives:
Veronica Andersson, Unionen, 0122-840 21
Simon Von Eckardstein, Sveriges Ingenjörer, 0122-842 24
Jan Lundgren, Ledarna, 0122-812 33
Kenth Gustavsson, IF Metall, 0122-815 25

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In this recruitment we renounce all calls relating to advertising and recruitment support.


Job ID: 186759

Organization: Gas and Power

Company: Siemens Industrial Turbomachinery AB

Experience Level: Student (Not Yet Graduated)

Job Type: Full-time

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