MATHS 2106 - Differential Equations for Engineers II

North Terrace Campus - Semester 1 - 2024

Mathematical models are used to understand, predict and optimise engineering systems. Many of these systems are deterministic and are modelled using differential equations. This course provides an introduction to differential equations and their applications in engineering. The following topics are covered: Linear ordinary differential equations of second and higher order, series solutions, Fourier series, Laplace transforms, partial differential equations, Fourier transforms.

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Course Details

Course Code	MATHS 2106
Course	Differential Equations for Engineers II
Coordinating Unit	Mathematical Sciences
Term	Semester 1
Level	Undergraduate
Location/s	North Terrace Campus
Units	3
Contact	Up to 5 hours per week.
Available for Study Abroad and Exchange	Y
Prerequisites	MATHS 1012
Incompatible	MATHS 2102, MATHS 2201
Assumed Knowledge	Basic Matlab programming skills such as would be obtained from ENG 1002 or ENG 1003 or COMP SCI 1012 or COMP SCI 1101 or COMP SCI 1102 or COMP SCI 1201 or MECH ENG 1100 or MECH ENG 1102 or MECH ENG 1103 or MECH ENG 1104 or MECH ENG 1105 or C&ENVENG 1012
Restrictions	Available to Bachelor of Engineering students only.
Assessment	Ongoing assessment, examination.

Course Staff

Course Coordinator: Associate Professor Ben Binder

Course Timetable

The full timetable of all activities for this course can be accessed from .

Course Learning Outcomes

Students who successfully complete the course will be able to:

Derive mathematical models of physical systems.
Present mathematical solutions in a concise and informative manner.
Recognise ODEs that can be solved analytically and apply appropriate solution methods.
Solve more difficult ODEs using power series.
Know key properties of some special functions.
Express functions using Fourier series.
Solve certain ODEs and PDEs using Fourier and Laplace transforms.
Solve problems numerically via the fast Fourier transform using Matlab.
Solve standard PDEs (wave and heat equations) using appropriate methods.
Evaluate and represent solutions of differential equations using Matlab.

最新糖心Vlog Graduate Attribute	Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.	All
Attribute 2: Creative and critical thinking, and problem solving Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.	All
Attribute 7: Digital capabilities Graduates are well prepared for living, learning and working in a digital society.	7,10

Learning & Teaching Modes

This course relies on instructional videos and workshops to guide students through the material, tutorial classes for peer and tutor support, and a sequence of written and online assignments that provide opportunities for students to practise techniques and develop their understanding of the course.

Workload

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

Activity	Quantity	Workload hours
Course videos		60
Workshops	12	12
Tutorials	11	22
Midsemester test	1	7
Written assignments	5	25
Online assignments	10	30
TOTALS		156

Learning Activities Summary

Schedule
Week 1	Differential equations and applications Ordinary differential equations (ODEs), directional fields Separable and linear first-order ODEs, substitution
Week 2	Exact first-order ODEs Existence and uniqueness of solutions of first-order ODEs Homogeneous ODEs, superposition, linear independence, Wronskian Reduction of order
Week 3	Constant-coefficient homogenous ODEs Modelling of mass-spring-dashpot systems, free oscillations Nonhomogeneous ODEs, method of undetermined coefficients Forced oscillations, electrical circuits
Week 4	Variation of parameters Systems of first-order ODEs and applications Constant-coefficient homogeneous linear systems of ODEs Variable-coefficient homogeneous ODEs, Euler-Cauchy equation, power series method
Week 5	Ordinary and singular points, Legendre's equation Frobenius method, Bessel's equation Bessel functions
Week 6	Laplace transform Inverse Laplace transform, partial fractions, s-shifting Laplace transform of derivatives, application to ODEs
Week 7	Convolution Unit step function, t-shifting, Dirac delta function Fourier series
Week 8	Complex form of Fourier series, energy spectrum, convergence Fourier sine and cosine series, half-range expansions
Week 9	Partial differential equations (PDEs) Wave equation, D’Alembert’s solution Separation of variables in 1D
Week 10	Heat equation Laplace equation Laplace transform solution of PDEs
Week 11	Fourier transform, Fourier integral, Fourier sine and cosine transforms Fourier transform solution of PDEs
Week 12	Discrete Fourier transform Fast Fourier transform

Tutorials will be held each week, commencing from week 2. Tutorials cover material from the previous lectures.

The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

Assessment must encourage and reinforce learning.
Assessment must enable robust and fair judgements about student performance.
Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
Assessment must maintain academic standards.

Assessment Summary

Assessment
Task	Type	Weighting	Learning Outcomes
Written assignments	Formative and Summative	12.5 %	All
Mobius (online) assignments	Formative and Summative	12.5 %	All except 2
Midsemester test	Summative	15 %	1,2,3,4,5
Examination	Summative	60 %	All

Assessment Related Requirements

To pass the course the student must attain:

an aggregate score of 50%, and
at least 40% on the final examination.

Assessment Detail

Written assignments are due every fortnight. The first written assignment will be released in Week 2 and due in Week 4.

Mobius (online) assignments are due every week. The first Mobius assignment will be released in Week 2 and due in Week 4.

The midsemester test will be held in Week 8. Further details, including test dates, times and venues, will be provided by email and MyUni.

Submission

Assignments must be submitted according to the policies and procedures published on the Differential Equations for Engineers II MyUni site.

Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade	Mark	Description
FNS		Fail No Submission
F	1-49	Fail
P	50-64	Pass
C	65-74	Credit
D	75-84	Distinction
HD	85-100	High Distinction
CN		Continuing
NFE		No Formal Examination
RP		Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through .

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SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the 最新糖心Vlog to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Maintained by:	Course Outlines Administrator

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