Skip to main content
 

MATH43120: Topics in Applied Mathematics

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Open
Level 4
Credits 20
Availability Not available in 2024/2025
Module Cap None.
Location Durham
Department Mathematical Sciences

Prerequisites

  • Prior knowledge of Analysis in Many Variables and Fluid Mechanics

Corequisites

  • None

Excluded Combinations of Modules

  • None

Aims

  • To introduce some important ideas in modern applied mathematics.
  • To develop an understanding of two particular models: MHD and non-linear elasticity.
  • To prepare students for future research in Applied Mathematics.

Content

  • Equations of magnetohydrodynamics (MHD), and their ideal and diffusive limits.
  • MHD equilibria: potential, force-free and magnetohydrostatic solutions.
  • Alfven waves.
  • Introduction to dynamo theory.
  • Stress and strain tensors and the governing equations of non-linear elasticity.
  • Energy formulations.
  • Equilibrium solutions such as the expanding balloon.
  • Bistability explored further through strips.
  • Collapsing spheres and cavitation.

Learning Outcomes

Subject-specific Knowledge:

  • By the end of the module students will:
  • be able to solve novel and/or complex problems in Applied Mathematics.
  • have a systematic and coherent understanding of the mathematical formulation behind the MHD and nonlinear elasticity models.
  • have acquired a coherent body of knowledge of MHD and nonlinear elasticity through study of fundamental behaviour of the models as well as specific examples.

Subject-specific Skills:

  • Students will develop specialised mathematical skills in mathematical modelling which can be used with minimum guidance.
  • They will be able to formulate applied mathematical models for various situations.

Key Skills:

  • Students will have basic mathematical skills in the following areas: problem solving, modelling, computation.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
  • Assignments for self-study develop problem-solving skills and enable students to test and develop their knowledge and understanding.
  • Formatively assessed assignments provide practice in the application of logic and a high level of rigour as well as feedback for the students and the lecturer on the students progress.
  • The end-of-year examination assesses the knowledge acquired and the ability to solve predictable and unpredictable problems.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures422 per week in Michaelmas and Epiphany; 2 in Easter1 hour42 
Problems Classes8Fortnightly in Michaelmas and Epiphany1 hour8 
Preparation and Reading150 
Total200 

Summative Assessment

Component: ExaminationComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
End of year written examination3 hours100 

Formative Assessment

Eight written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students.

More information

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.