Bachelor-/Masterthesis: Thermal simulations of plain bearings to predict bearing damage due to overheating

Website Chair for Wind Power Drives

The Institute for Machine Elements and Systems Engineering (MSE) and Chair for Wind Power Drives (CWD) research the fundamental structural and tribological behavior of machine elements. One of the research objectives is to increase the availability, robustness and energy efficiency of wind turbines and to reduce the energy costs. For this experiment’s with software simulation tools and modern test benches are combined.

In order to reduce the power generation costs of modern wind turbines (WTG), the power density of the planetary gearboxes in WTGs is to be increased. The use of plain bearings, which have already been used in industry for a number of years, is a suitable solution. Stable operation of plain bearings is however necessary to limit the downtime of wind turbines. The CWD and MSE are therefore conducting research into wear and temperature prediction in planetary plain bearings. In this context a state-of-the-art thermal wear tool chain is developed at the institute.

The aim of this thesis work is to extend this tool chain for simulative prediction of thermal criticality in order to avoid overheating failures in plain bearings.

Tasks:

  • Familiarization with the topic of planetary plain bearings in wind turbines and wear
  • Simulation of EHD and FEM models of a plain bearing test bench
  • Using existing tool chain, to calculate transient change in local bearing temperature
  • Optimizing the tool chain to predict overheating failures in plain bearings while considering computational efficiency

Your profile:

  • Motivation to work on a futuristic tool chain that can help predict plain bearing safety
  • Interest in plain bearing technology, wind energy,
  • Previous knowledge of Matlab and Python would be desirable
  • First experiences with multi-body simulation programs like AVL Excite (EHD) and Abaqus (FEM) would be advantageous

What we offer:

  • Independent and self-learning mode of work to bring the best out of you
  • Scientific work in a highly motivated research team with a very good working atmosphere and intensive supervision
  • Fun team events and network building
  • Learning practice-relevant automated simulation methods
  • Immediate start possible and flexible working hours
  • Working on trending and future oriented problems

 

We look forward to your application by email:

Anuj Khare, M. Eng.
Institut für Maschinenelemente und Systementwicklung

Schinkelstr. 10, 52062 Aachen
anuj.khare@imse.rwth-aachen.de

Um sich für diesen Job zu bewerben, sende deine Unterlagen per E-Mail an anuj.khare@imse.rwth-aachen.de