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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Numerical Partial Differential Equations (MATH10044)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) Credits10
Home subject areaMathematics Other subject areaSpecialist Mathematics & Statistics (Honours)
Course website https://info.maths.ed.ac.uk/teaching.html Taught in Gaelic?No
Course descriptionThis course provides an introduction to the numerical treatment of partial differential equations (PDEs). We will first consider the classical theory and discuss the wave equation (d'Alembert in 1747), the heat equation (Fourier 1822) and the Laplace equation (Laplace 1785, Legendre 1785). Many interesting PDEs may not have a solution in a classical sense and we will introduce weak solutions for such problems. Numerical methods to approximate both classical and weak solutions will be discussed.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Pure & Applied Analysis (MATH10008) AND Complex Variable & Differential Equations (MATH10033)
Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2013/14 Semester 2, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 13/01/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 100 ( Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 98 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 80 %, Coursework 20 %, Practical Exam 0 %
No Exam Information
Summary of Intended Learning Outcomes
1. Familiarities with different type of PDEs.

2. Knowledge about classical methods for simple PDE model problems.

3. Knowledge about numerical methods for the approximation of classical and weak solution of simple PDE model problems.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsNPDE
Contacts
Course organiserDr Martin Dindos
Tel:
Email: M.Dindos@ed.ac.uk
Course secretaryMrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email: Alison.Fairgrieve@ed.ac.uk
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