From Physics Based Modelling to Data Driven

Type of course:

Digital learning, Lesson

Language:

Duration:

15 minutes

Workload:

2 hours

Proficiency:

Beginner

Target:

Students, Workers

This nugget delves into the transition from traditional physics-based modeling to data-driven approaches in modeling and analysis. It explores the applications of physics-based modeling and the rise of data-driven techniques, driven by advancements in big data and machine learning. Additionally, it highlights the concept of digital twins, computational models that evolve over time to accurately represent physical assets. By understanding the strengths and limitations of both approaches and exploring their potential synergy, we can leverage the power of data-driven modeling to revolutionize various fields and drive innovation.

Learning outcomes

After completing this Nugget, the learner will be able to describe the benefits and disadvantages of Physics modeling, as well as of Data-driven modeling
After completing this Nugget, the learner will be able to differentiate which method is most suited based on the type of problem
After completing this Nugget, the learner will be able to apply a transition from a physics-based modelling to a data-driven approach, or vice versa.