This course introduces students to the fundamental of modelling geodynamical processes. Students are exposed to the foundations of finite element modelling and how to construct numerical models of earth systems based on material properties. This is built up using the methods of calculus, linear algebra, and differential equations to explore a range of geodynamical processes. Model accuracy is assessed using statistical tools. We leverage the open-source programming language Python and Jupyter notebooks, as a flexible platform for learning these concepts while developing numerical modelling skills.

5 weeks. 2 hours of lecture per week and 2 hours of practical per week, and a further 1 hour of supervised workshop a week for groups to develop and work on their project with instructor feedback.

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The two assessments for the course are linked to a group modelling project. The student groups select a natural process to model using the techniques presented in the lectures. Studio time is given to develop and run these models. The two assessments are:

1. A conference style group presentation presenting both the geodynamical problem and how they set up the model. (Equivalent to 500 words A portion of contribution will be weighted by github commits to track contributions. This will also assess code quality. Code assessment will examine readability of code and model performance. (30%)

2. Individual report --- own code to create own plots, and interpretation of data. 1500 words. (70%)

These two assessments are designed to mimic workplace dynamics, where you need to work as a team to solve problems as well as take personal responsibility for the presentation of your own contributions and an ability to understand how it fit within the larger context of the project. 

The aim of this course is to introduce students to the fundamentals of numerical modelling.

By the end of this course students will be able to:

■ Solve a variety of geodynamics problems using numerical implementations of calculus and linear algebra.

■ Transform differential equations into numerical models.

■ Recognise the role of material properties in the context of earth systems processes.

■ Evaluate model performance using statistical methods.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.