Job Description

Description

The opportunity

Understanding the moisture dynamics in transformer insulation is critical for predicting aging, dielectric failure, and overall

reliability. While recent models like the Thermo-Chemical Digital Twin offer advanced simulation capabilities, one of the main

opportunities for improvement lies in the modeling non-uniform water distribution and its impact on voltage behavior under

transient conditions. Additionally, no established criterion exists for evaluating water content in paper insulation under

energized conditions.

Your responsibilities

Model Development:

Extend the water diffusion model to include spatially resolved moisture dynamics and additional influencing factors such as temperature gradients and oil aging

Diagnostic Criteria:

Develop a practical criterion for evaluating water content in paper insulation under energized conditions

Voltage Behavior Analysis:

Investigate how increased and non-uniform moisture distribution affects voltage response under impulse and switching conditions

Validation:

Validate model improvements through simulations and comparison with Breakdown Voltage (BDV) tests using special wave shapes

Your background

Master’s student in Electrical Engineering, Power Systems, Applied Physics, or related fields Strong foundation in modeling and simulation (e.g., MATLAB, Python, COMSOL) Knowledge of dielectric materials and transformer insulation systems Analytical and independent working style Fluent in English; German is a plus

What we offer

Supervision by experienced R&D professionals Access to internal models, data, and simulation tools Opportunity to contribute to cutting-edge transformer diagnostics Potential for follow-up opportunities in research or engineering roles switching conditions

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