THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2012/2013
- ARCHIVE as at 1 September 2012 for reference only
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DRPS : Course Catalogue : School of Engineering : Chemical

Undergraduate Course: Computational Methods for Chemical Engineers 2 (CHEE08011)

Course Outline
SchoolSchool of Engineering CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) Credits10
Home subject areaChemical Other subject areaNone
Course website None Taught in Gaelic?No
Course descriptionFor the first five weeks, the students work on a self-study MATLAB module which will consist of five individual units. The individual units will be concluded by competence based self tests so that the students can test whether they understood the concepts and are able to apply them. These units will be supported by weekly computing drop-in sessions. The learning outcomes of the module will be assessed by a computer-based class test.

The second half of the course focuses on the application of numerical methods in a chemical engineering context. The learning outcomes of this part of the course will be assessed by completion of the weekly computing labs weeks 6 - 9 and a hand-in exercise.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Mathematical Methods 1 (MATH08029) AND Applicable Mathematics 2 (MATH08031) AND Mathematical Methods 2 (MATH08032) OR Mathematics for Science and Engineering 1a (MATH08060) AND Mathematics for Science and Engineering 1b (MATH08061)
Students MUST have passed:
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: 2012/13 Semester 1, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Location Activity Description Weeks Monday Tuesday Wednesday Thursday Friday
King's BuildingsLaboratoryTLF, Fleeming Jenkin1-11 14:00 - 17:00
King's BuildingsLecture3217, JCMB1-11 10:00 - 10:50
King's BuildingsLectureLecture Theatre C, JCMB1-11 10:00 - 10:50
First Class First class information not currently available
No Exam Information
Summary of Intended Learning Outcomes
After completing this course, students will be able to:
* demonstrate proficiency in the basics and fundamentals of MATLAB
* demonstrate ability to construct computer algorithms for implementation in MATLAB programs
* apply MATLAB and numerical methods to a variety of problems in a chemical engineering context


Assessment Information
The course is continuously assessed by an open book class test (50 %), completion of weekly computing labs (20 %), a hand-in exercise (30 %)."
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus The course comprises a self-study MATLAB module (week 1 - 5) assessed by a 1 hour computer-based open book class test, 10 lectures (weeks 6 - 10), 4 compulsory computing labs (assessed by the successful completion of the tasks) and 6 drop-in computing sessions. The application of numerical methods to chemical engineering problems is assessed by a hand-in exercise.
Lectures
The following subjects will be covered during the course:
Week 1 - 5: Self-study MATLAB module, units 1 - 5
Week 1: Introductory Lecture
Weeks 6 - 9: Application of numerical methods to chemical engineering problems using MATLAB:
Week 6: How to tackle more complex programming tasks
Week 7: Solving ODEs numerically
Week 8: Root finding
Week 9: Regression analysis & parameter estimation
Week 10: Hand-in exercise
Week 11: Electronic submission of hand-in exercise
Laboratories
Week 1 - 5: Drop-in sessions about the MATLAB module
Week 6: More complex programming tasks: Equations of state
Week 7: ODE solvers in MATLAB: Irreversible reactions in a batch reactor; Solving stiff ODEs with MATLAB, Flight of a parachutist
Week 8: Root finding: Bubble point calculation; Terminal velocity of falling particles in a liquid; Reactions with multiple steady states.
Week 9: Parameter estimation: Fitting different polynomials to thermal conductivity data and deciding which correlation fits best; Fitting a rate equation to initial rate datal; Enzyme kinetics
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsNot entered
Contacts
Course organiserDr Tina Duren
Tel: (0131 6)50 4856
Email: tina.duren@ed.ac.uk
Course secretaryMrs Sharon Potter
Tel: (0131 6)51 7079
Email: Sharon.Potter@ed.ac.uk
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