Type dienstverband:
Internship and graduation project
Locatie:
Delft
Opleidingsniveau:
WO
Uren per week:
Fulltime – 40

Internship | Physics-informed neural networks for fluid dynamics

About this position

Want to contribute to innovative solutions for complex multi-physics problems? Join us in applying physics-informed machine learning to case studies in the energy sector. Physics-informed machine learning holds the promise to combine the best of two worlds: (i) it uses machine learning to extract complex relationships from a dataset and to create a fast model, and (ii) it ensures that physics-based theories are satisfied, and reliable predictions can be made even in ‘unseen’ regimes (for parameters not contained in the ‘training’ dataset). In this project, this innovative approach will be applied to complex fluid behavior within pipes.

What will be your role?

Physics-informed neural networks (PINNs) are neural networks with a loss function forcing the NN to satisfy predefined laws (typically, conservation equations in the form of ODEs/PDEs). PINNs can be used to support traditional numerical methods (such as computational fluid dynamics, CFD) and speed-up design and optimization studies; they can handle ill-defined problem (for example when boundary conditions are not clearly defined) and directly incorporate noisy experimental data in the model; they can be used for model calibration or inverse problems, when some parameters of the underlying equations are unknown and need to be discovered using the available data.

We are using PINNs for applications in different domains, and in this project the focus will be on complex fluid behavior within pipelines. Particularly, the aim is to model viscoelastic turbulent flow to identify optimal operating conditions to maximize drag reduction. We envision to apply this methodology for applications in the context of geothermal production and district heating.

In consultation with the student and academic advisor, exact project scope and duration will be defined. Minimum project duration is 3 months. Within TNO, you will work in contact with an international team of highly motivated researchers in the Heat Transfer and Fluid Dynamics department in Delft; partial work from home is possible.

What we expect from you

You are in the final stages of your degree in engineering, physics, mathematics and have some track record in modelling and/or machine learning. You have experience in programming in Python, good communication skills (including in English), you have the right mix of curiosity-driven motivation and result-oriented mentality.

What you'll get in return

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

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. Read more about TNO as an employer.

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. Want to know more? Read what steps we are taking in the area of diversity and inclusion.

The selection process

After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.

Has this job opening sparked your interest?

Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button.

A portrait of the TNO internship