“I dream of improving numerical model predictions for 3D printing”
I enjoy studying at the TU/e because it is a small-scale university where it is easy for students to reach out to professors. What excites me most about studying Mechanical Engineering at the TU/e are the group projects known as Challenge Based Learning (CBL). In these projects, you collaborate with fellow students to tackle real-world industrial problems and are given the opportunity to build prototypes using techniques like laser cutting and 3D printing.
Throughout my studies, I have enjoyed exploring material’s deformation through modeling. Across various courses, I have learned how to properly develop structured models in different programming languages. In the track Materials for High-Tech Systems Design (MHS), you study the material’s response to thermal or mechanical loading conditions experimentally and/or numerically. Typically, we study the material’s deformation in the processing state, where the material is still flowing, or in the processed state, where the material is solidified.
In my graduation project I have studied the deformation of a fluid in a squeeze flow, which is a type of flow in which the material is compressed between two parallel plates. I have compared the model outcome to the experimental data obtained using a custom-made experimental setup. I have applied a probabilistic framework to the model known as Bayesian uncertainty quantification, where we investigate the uncertainty in the model parameters with the goal of improving the predictive capabilities of the model.
In the future, I would like to apply this framework to more advanced production techniques, such as 3D printing, because these systems are surrounded by uncertainties and require sophisticated material models to describe the flow behavior. That's what makes it so interesting.