Numerical Solution of Partial Differential Equations (L.7) (845G1)

15 credits, Level 7 (Masters)

Spring teaching

You will learn how to develop computational methods for the approximation of PDEs and rigorously prove their accuracy. As part of a computational project, you will also implement these methods and illustrate that the computational results agree with the developed theoretical analysis.

Topics that will be covered include the variational formulation of boundary value problems, Sobolev spaces, abstract variational problems, the Lax-Milgram Lemma, the Galerkin method, the finite element method, elementary approximation theory, and error analysis.


100%: Lecture


20%: Coursework (Portfolio, Problem set, Project)
80%: Examination (Unseen examination)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 33 hours of contact time and about 117 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2023/24. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum. We’ll make sure to let you know of any material changes to modules at the earliest opportunity.