PhD Student - Department of Electromechanical, Systems and Metal Engineering

Updated: almost 2 years ago
Job Type: FullTime
Deadline: 01 Aug 2022

Last application date Aug 01, 2022 00:00

Department TW08 - Department of Electromechanical, Systems and Metal Engineering

Contract Limited duration

Degree Master of Science in Mechanical, Chemical or Physics Engineering.

Occupancy rate 100%

Vacancy type Research staff


Job description

Context

Thermo-Elastohydrodynamic Lubrication (TEHL) is a specific lubrication regime that typically occurs in classic machine components such as rolling element bearings, gears, cam-follower systems, etc., and is therefore very relevant in many machine applications. TEHL is characterized by thin lubricant films (50 nm-1 m) in which the hydrodynamic pressure can reach values up to GPa range (1-4 GPa), inducing elastic deformation of the opposing contact surfaces in the order of the film thickness. At such high pressures, the lubricant becomes compressible and behaves in a highly non-Newtonian way by local solidification and shear-thinning.

Accurate computational simulation of TEHL by means of continuum models requires therefore an accurate description of the lubricant’s compressibility and the rheology (i.e. piezo-viscosity and shear thinning) as well as the thermal properties (specific heat, conductivity), wall slip and cavitation. Today, however, the thermomechanical properties of only a handful of “academic” lubricant oils have been measured experimentally and documented in the literature, due to the technical challenges of performing experiments at extreme pressures and shear rates. Hence, typically data is limited to 1.5GPa.

In the past decades Molecular Dynamics (MD) has emerged as a more sophisticated computational approach to study interfacial phenomena and thin film rheology. Such an MD approach offers the advantage of obtaining an accurate estimate of the lubricant’s thermo-mechanical properties, by directly simulating the lubricant’s molecular structure subject to different conditions of pressure, temperature, shear, etc.. Despite the increase in popularity of MD, the accuracy and reliability of these calculations are not always guaranteed and highly depend on the accuracy and reliability of the force fields that describe the inter-and intra-molecular forces. Typically, available force fields are applied in the literature, without being designed or “calibrated” for the lubricant molecule under investigation.

Your Tasks

The research assignment involves the development of a framework for accurate and reliable calculation of thermomechanical properties of an industrially relevant monomolecular lubricant based on Non-Equilibrium MD (NEMD), using tailored force fields, with minimal empiricism. This involves DFT-D modeling, Force Field Modelling using Machine learning, and NEMD simulations.


Job profile
  • You hold a Master's degree in Mechanical, Physical, or Chemical engineering.
  • You have a strong motivation for conducting scientific research at a high level.
  • You possess good analytical and technical skills.
  • You are interested in Advanced Scientific Computing.
  • Experience with programming in C++, and Python is necessary.
  • You have good knowledge and experience with Molecular Dynamics (LAMMPS).
  • You take responsibility for the development of your project in a well-structured, thorough way, and you’re able to solve problems independently. You display creativity in solving problems, generating ideas, or finding new ways of working.
  • You have an open personality and are willing to contribute to the team and participate in didactic projects.
  • You have excellent communication skills in English, both orally and written. Knowledge of Dutch is certainly an asset.

  • How to apply

    To apply, please complete the application form at the following link before August 1st 2022:

    Apply: https://forms.gle/1y1zisvqhkpZNeNd9

    Your application will be taken into consideration on condition that all fields in the application form are completed properly.



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