Postdoc Digital Twin-based Prognostics for Wind Turbine Blade Preventive Maintenance Decisions

Updated: 23 days ago
Deadline: 28 Mar 2024

Challenge: Enable optimal wind turbine blade preventive maintenance

Change: Develop digital twin-based prognostics and health management

Impact: Improve the reliability of wind turbine blades

There is a rapid increase in the size of wind turbine rotor blades, and a continuous stream of new blade models is being introduced to the market. However, there are concerns regarding the durability of large rotor blades, and new failure mechanisms are being observed. This is a widespread issue in the industry, which has significant implications for both blade manufacturers and windfarm operators. The advancement of modelling, condition monitoring techniques, and data analytics enables the creation of a digital twin of the rotor blade. The main challenge lies in accurately characterizing the failure mechanisms in the structural model, estimating the remaining useful life, and effectively utilizing this information in the operation and maintenance of offshore windfarms.

This PostDoc position offers a unique opportunity to work within the recently awarded HER+ ReliaBlade 2 project, which aims at improving the reliability of wind turbine rotor blades by monitoring their structural health throughout the lifetime. To achieve this, a digital twin framework fed by measurements from blade-mounted sensors is developed to obtain real-time information about the blade structural health and remaining useful life. Within the ReliaBlade 2 project, a unique opportunity is available for a passionate and highly motivated researcher to work on digital twin driven prognostics for predictive maintenance decision-making.

The research will first develop a data-informed framework for the probabilistic forecasting of the remaining useful life of blades, enhanced by a hybrid approach for the assessment of damage and deterioration, and then implement these findings for optimal planning of both calendar- and condition-based interventions. As a postdoc at TU Delft, you will work closely with leading wind turbine blade manufacturers, sensor technologies providers and wind farm operators as well as researchers at TU Delft and TNO and international collaborators in leading research institutes and industry.      

We are seeking for an excellent candidate who has:

  • a PhD in an appropriate discipline, e.g. Engineering, Physical Sciences, Computer Science, Applied Mathematics or similar;
  • general background and specific experience in the technical domains covered by the position;
  • excellent analytical and programming skills in Python/MATLAB, combined with experience in working with wind energy systems and data processing and stochastic analysis;
  • demonstrable knowledge and interest in AI methods, preferably deep learning techniques:
  • demonstrable knowledge of probabilistic lifetime prediction tools;
  • a curiosity-driven mindset and a strong motivation of conducting independent research;
  • capacity to work both independently and in a team;
  • ability and track record of effective communication to academic and industrial audiences in an international environment;
  • eagerness to learn new skills and knowledge as needed for the project;
  • excellent spoken and written English.

Female scientists are particularly encouraged to apply. A strict equal opportunity, gender-neutral and internationally comparable recruitment procedure is implemented.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.

Click here  to go to the website of the Faculty of Aerospace Engineering.

Are you interested in this vacancy? Please apply no later than 28 March 2024 via the application button and upload:

  • 1-page motivation letter detailing the knowledge, skills and experience you think make you the right candidate for the job;
  • Detailed Curriculum Vitae including the list of publications;
  • Summary of academic record and research experience;
  • Contact information of at least two relevant references.

For more information about this vacancy, please contact Dr Donatella Zappalá, [email protected] ([email protected] ), or Prof. dr. Simon J. Watson, [email protected] ([email protected] ).

Please note:

  • You can apply online. We will not process applications sent by email and/or post.
  • Please do not contact us for unsolicited services.

A pre-employment screening can be part of the selection procedure.



Similar Positions