About the Course
This course trains learners in the application and analysis of a wide range of experimental material characterisation methods, providing valuable input properties for numerical modelling. The course focuses on the mechanical performance and manufacturing parameters of materials used in wind turbine components, including both metallic materials for structural parts and composites for blade structures. Through video demonstrations and complementary data files, learners will develop and apply Python-based tools to characterise key material properties. A core emphasis of the course is on directly linking high-quality experimental testing to numerical modelling, ensuring learners understand good practices not only for generating reliable material input data but also for designing experiments that reciprocally inform modelling efforts.
The course features a comprehensive library of different test methods tailored to various modelling tasks, covering both manufacturing and structural modelling of wind turbine materials. Measurement techniques addressed include permeability testing of fabrics, cure determination for adhesive and resin materials, elastic-plastic behavior analysis of metallic parts, stress-strain testing for adhesives and resins, viscoelastic material characterization, tensile and compressive testing of composites, single fiber testing for Weibull strength analysis, fatigue testing of composites, and cohesive law determination for adhesives, among others.
In addition to an overall introduction to Python-based data analysis, each measurement technique is presented as a standalone module, allowing for independent learning and flexible course progression. The course is designed to evolve over time, with not all measurement techniques covered in the initial offering. This modular approach enables different elements to be combined in various ways, depending on the specific focus of each course iteration and the needs of the learners.
After this course, you can
Specify appropriate test procedures to extract parameters for targeted numerical models.
Apply and develop Python scripts to analyse raw experimental data using scientific programming and data engineering techniques.
Assess and prepare high-quality input data for robust numerical analyses and simulations.
Validate numerical models by comparing them with experimental measurements.
1-2 weeks, hybrid, full-time
1. Basic proficiency in Python programming.
2. Foundational knowledge of solid mechanics.
3. Background in materials science.
The course is delivered online synchronously and asynchronously, featuring video lectures, measurement demonstrations, Python-based data analysis with Jupyter Classroom, and simulation validation exercises.
Evidence your learning with a Certificate of Achievement from the DTU on successful completion.
This course will be stackable with other LLL courses that will be developed by DTU Wind, to form certain specialisations or micro-degrees. For instance, we offer a series of courses that can be combined to form the specialisation “Data-Driven Decision Making for Wind Farm Operations.” This specialisation includes four courses, with “Model-Based Estimation of Remaining Useful Life” serving as the entry point.
Key Information
Meet your teachers
Learn from world-class researchers and passionate educators who bring cutting-edge expertise and hands-on experience into the classroom.
Lars P. Mikkelsen
Associate Professor
Lars P. Mikkelsen is an Associate Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). An internationally recognised expert in materials science and solid mechanics, he specialises in the mechanical characterisation...
Mohit Sharma
Senior Vice Presiden at Marubeni Corporation
Singapore
“Solid and comprehensive overview!”
"For anyone considering a career transition, this course offers a solid and comprehensive overview of wind energy. It equips you with the essential knowledge and skills needed to smoothly transition into the wind energy field."
Sophie Yin
Renewables Engineer, Woodside Energy
Australia
“Flexible learning with outstanding support!”
“What I enjoy the most about the programme is the flexibility. I have been able to access the content around other aspects of my life, which has been very valuable. Also, the lecturers have made them available to the students online to answer questions and actually provide knowledge beyond the course, which I really enjoyed.”
Fahd Outailleur
Head of Engineering at Enel Green Power
Morocco
“Europe’s leader in wind energy”
“I chose to enrol in this wind energy master's program because DTU is the leading technical university in Europe, renowned for its specialization in wind energy. The program reflects the state of the art of the sector. Before joining, I knew some of their software programmes like WAsP and the Global Wind Atlas. So I was confident about the quality of the training.”
DTU Student Testimonials
Discover what DTU students have to say about their journey, their experiences, and the skills they’ve gained.
Financing Options
We offer a range of discounts and packages to make the programme more accessible.
Early Bird Discount
Save
20%
Save 20%
Bring a Colleague
Sign up together with a colleague and you’ll both receive
10%
Off
Invite your friends
Team-Based Learning
Enroll a group of 3 or more participants from the same company and benefit from special team pricing.
Boost collaboration and apply knowledge directly in your workplace.
Join with your team
Pre-register here :)
For course-specific questions, please contact the course responsible Lars P Mikkelsen, Associate Professor at DTU Wind, lapm@dtu.dk
Didn't find what you were looking for? Or need a customised training solution for your company? Contact Karsten Kryger, Coordinator of Lifelong Learning at DTU Wind, kkry@dtu.dk