Internship | Fatigue behaviour of riveted connections in bridges using data-driven symbolic regression ML

Internship opportunity: Fatigue behaviour of riveted connections in bridges using data-driven symbolic regression ML

About this position

The fatigue life of riveted connections in steel bridges is of a growing concern since the age of these bridges and the traffic volume increases. TNO has gathered 629 fatigue tests from literature, and evaluated these with the conventional net section stress resulting in a largely scattered S-N plot. If this is applied, the fatigue assessment method will have to be very conservative for a large number of riveted connections. Therefore, TNO has proposed a new fatigue driving force for riveted connections, based on a more local stress parameter, and developed an analytical model that estimates this stress parameter. The analytical model is deterministic, mostly based on physics, and therefore uses the joint geometry as input. This model reduces the scatter significantly, indicating the dependency of the fatigue life on the geometry. The goal of this proposal is to evaluate the fatigue tests with a machine learning (ML) algorithm based on symbolic regression instead of based on physics. Symbolic regression is a method to determine equations that presents a good fit of a dataset. It combines variables (input), with mathematical operators, constants, and analytical functions. Because the output are the equations, the ML algorithm provides insight in the relations between the different variables, and is therefore interpretable.

What will be your role?

This internship will include the following steps:

1. Understanding and implementation of an open-source symbolic regression ML algorithm.
2. Training of the ML algorithm on a part of the fatigue test dataset (training set). This includes determining the coefficient of determination, and Pearson correlation coefficients. Multiple combinations of analytical functions, variables and mathematical operators will be tested.
3. Application of the predicted equations from the ML algorithm to the rest of the fatigue test dataset (test set), to determine the performance of the algorithm.
4. A sensitivity analysis will be performed to determine how the predicted equations from the ML algorithm hold for values of the variables outside of the tested ranges.
5. The results of 3. will be compared to the developed analytical model.

What we expect from you

• You follow a master program in STEM such as civil engineering, mechanical engineering, architecture, (applied) physics or mathematics, computer science, marine/aerospace engineering, or similar.
• You have an investigative and critical attitude, you want to know why certain phenomena occur and determine its effect.
• You like to cooperate with others and are creative.
• You live in The Netherlands.
• You have excellent oral and written communication skills in English, and preferably Dutch language (B1 level).

What you'll get in return

• A highly professional, innovative internship environment, within a team of top experts.
• A suitable internship allowance (615 euro for wo-, hbo- and mbo-students, for a full-time internship).
• Possibility of eight hours of free leave per internship month (for a full-time internship).
• A free membership of Jong TNO, where you can meet other TNO professionals and join several activities, such as sports activities, (work-related) courses or the yearly ski-trip.
• Use of a laptop.
• An allowance for travel expenses in case you don’t receive an OV-card.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world.

At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society.

More information about this vacancy?

• Rik Hendriks
  • E-mailadres: rik.hendriks@tno.nl