Mathematical Modelling 3

Semester 2, 2019

Staff

- Peter Bier
- Richard Clarke (director)
- Kevin Jia (coordinator)
- Andreas Kempa-Liehr

Teaching schedule

Please see Student Services Online for the official class timetable and locations.

Lectures are currently scheduled on Mon, Tue, Thu, Fri 1-2pm in 260-098.

Calendar notes

A selection from: ordinary differential equations, systems of equations, analytical and numerical methods, non-linear ODEs, partial differential equations, separation of variables, numerical methods for solving PDEs, models for optimisation, industrial statistics, data analysis, regression, experimental design reliability methods.

Prerequisite: ENGSCI 211Restriction: ENGSCI 313, 314

## Intended learning outcomes |
## Related graduate attributes |
## Related assessments |
---|---|---|

Models for Optimization: Students will have comprehension of the standard linear, nonlinear and integer programming models. They will be able to model real world problems using these optimization models and solve these using Excel's Solver. |
ENGA01: engineering knowledge (4) ENGA02: problem analysis (2) ENGA04: investigation (4) ENGA05: modern tool usage (4) ENGA10: communication (2) ENGK02: mathematical modelling (4) ENGK03: abstraction and formulation (2) ENGP01: depth of knowledge required (4) ENGP02: range of conflicting requirements (4) ENGP03: depth of analysis required (4) UOA_1: Disciplinary Knowledge and Practice (4) UOA_2: Critical Thinking (3) UOA_3: Solution Seeking (2) UOA_4: Communication and Engagement (2) UOA_5: Independence and Integrity (2) |
MFO Quiz MFO Assignment Exam |

Data Analysis: Students will have an comprehension of the standard statistical methods of the analysis of variance, the use of linear regression and the development of multiple regression models. They will be able to apply these techniques to analyse the type of data that arises in engineering practice. |
ENGA01: engineering knowledge (4) ENGA02: problem analysis (2) ENGA04: investigation (4) ENGA05: modern tool usage (4) ENGA10: communication (2) ENGK02: mathematical modelling (4) ENGK03: abstraction and formulation (2) ENGP01: depth of knowledge required (4) ENGP02: range of conflicting requirements (4) ENGP03: depth of analysis required (4) UOA_1: Disciplinary Knowledge and Practice (4) UOA_2: Critical Thinking (3) UOA_3: Solution Seeking (2) UOA_4: Communication and Engagement (2) UOA_5: Independence and Integrity (2) |
DA Assignment Exam |

Ordinary Differential Equations: The student will gain knowledge of 1st and 2nd order systems of ODEs and how to solve such systems using eigenvalue and eigenvector methods. The student can apply systems of ODEs theory to analyse signals and solve some signal based problems. |
ENGA01: engineering knowledge (4) ENGA02: problem analysis (2) ENGK01: theory of natural sciences (4) ENGK02: mathematical modelling (4) ENGK03: abstraction and formulation (2) ENGP01: depth of knowledge required (4) ENGP02: range of conflicting requirements (4) ENGP03: depth of analysis required (4) UOA_1: Disciplinary Knowledge and Practice (4) UOA_2: Critical Thinking (3) UOA_3: Solution Seeking (2) UOA_5: Independence and Integrity (2) |
ODE Assignment Exam |

Partial Differential Equations: Knowledge, comprehension and the application of partial differential equations in modelling in engineering science. Students are also required to be able to analyse the results of their models, to synthesise this in terms of the original physical model and to evaluate the usefulness of the model. |
ENGA01: engineering knowledge (4) ENGA02: problem analysis (2) ENGA04: investigation (4) ENGA05: modern tool usage (4) ENGK01: theory of natural sciences (4) ENGK02: mathematical modelling (4) ENGK03: abstraction and formulation (2) ENGP01: depth of knowledge required (4) ENGP02: range of conflicting requirements (4) ENGP03: depth of analysis required (4) UOA_1: Disciplinary Knowledge and Practice (4) UOA_2: Critical Thinking (3) UOA_3: Solution Seeking (2) UOA_5: Independence and Integrity (2) |
PDE Test Exam |

Coursework

3 assignments (ODE, MFO, DA) at 10% each.

(MFO has a 3% quiz component included in the assignment weighting, due separately).

1 test (PDE) at 10%

Exam rules

60% Exam + 40% Coursework (as listed above)

Final percentage may not exceed exam percentage by more than 10%. As with all courses, the final grade is subject to scaling.

The exam is 3 hours long. No calculators are permitted in the exam.

In the event of a student seeking an aegrotat, a greater weight may be placed on the test (reflecting that it is sat under exam conditions). Students who did not complete the test may be required to complete an additional written or oral assessment as part of any aegrotat application.

All queries regarding assignment marks must be made before the exam. No changes in assignment marks are possible once the exam has been sat.

Inclusive learning

Students are urged to discuss privately any impairment-related requirements face-to-face and/or in written form with the course convenor/lecturer and/or tutor.

Other assessment rules

Written assignments are to be submitted via Canvas as PDF files. Assignments may be hand-written and scanned, or typed up and converted to a PDF, or a mix of both.

Assignment Extensions: If you need an extension on an assignment, perhaps because of illness, then please contact the course coordinator (details above) as soon as possible. You will need to obtain a medical certificate or other documentation for most extensions.

Note that pressure of work and/or overseas travel are not sufficient reasons to grant extensions or assignment/test extensions or exemptions.

Policy on Late Assignment Submissions:

For assignments given as Canvas Quizzes, no late submissions will be accepted. Once the due date / time is past, all active quizzes will be automatically submitted.

For written assignments, aim to have all files safely uploaded well before the due time. It is highly recommended that you upload draft copies of all files at least one day in advance of the deadline, in case of last-minute technical difficulties. Late submissions will be marked as usual, but will be subject to a penalty of 10% (of the total number of marks available) per hour-or-part-thereof. Example: Assignment 1 is due at 7pm and is worth 12 marks. A submission received at 19:40pm on the due date would lose 1.2 marks (10% of 12 marks).

Academic integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting his or her learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the world-wide web. A student's assessed work may be reviewed against electronic source material using computerised detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerised review.

All students enrolled at the University of Auckland are required to complete a compulsory Academic Integrity course, usually in their first semester/year of enrolment. The University of Auckland’s full guidelines on procedures and penalties for academic dishonesty are available here.

Actions shared/based on previous feedback

Incremental improvements have been made to all course material. Assignment due times are now 1pm to avoid confusion.

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All the information here is accurate at the time of publication, but you are are advised to additionally consult our official document, the University of Auckland Calendar, for accurate academic regulations, requirements, and policies.