# Course Title: Mathematics for Engineers

## Part A: Course Overview

Course Title: Mathematics for Engineers

Credit Points: 12.00

## Terms

### Teaching Period(s)

MATH1122

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

MATH1122

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 1 2018,
Sem 1 2019

Course Coordinator: Dr Yan Ding

Course Coordinator Phone: +61 3 9925 3217

Course Coordinator Email: yan.ding@rmit.edu.au

Course Coordinator Location: Building 8, level 9, room 19

Pre-requisite Courses and Assumed Knowledge and Capabilities

MATH2128 Engineering Mathematics B
MATH2129 Mathematics and Statics.
Or equivalent first year university mathematics courses

Ability to apply the techniques of integral and differential calculus to formulate and solve problems involving change and approximation, including problems with more than one variable.
Ability to recognize the properties of the common mathematical functions (polynomials, exponentials and hyperbolic functions, logarithms, inverse trigonometric and inverse hyperbolic functions) and their combinations commonly found in engineering applications.
Ability to recognize the properties of vectors and curves in space; apply the techniques of vector analysis to problems involving three-dimensional geometry and motion.
Ability to recognize the properties of complex numbers; apply complex numbers to the solution of algebraic equations.
Ability to formulate and solve differential equations.
Ability to recognize the properties of matrices; apply the techniques of matrix analysis to problems involving three-dimensional geometry and transformations in three-dimensional space; calculate determinants of matrices; find eigenvalues and eigenvectors.
Ability to recognize the basic properties of infinite series and apply power series to problems involving approximation of functions.
Ability to create a Taylor series approximation to a function of one variable and determine its radius of convergence.
Knowledge of introductory fluid dynamics including fluid flow velocity, acceleration, energy and momentum.
Knowledge of introductory statics including Newton’s laws, momentum, force, work, energy, equilibrium, shear and bending moments, stresses and strains, mechanical properties of materials

Course Description

Mathematics for Engineers is a single semester course consisting of four mathematics topics. The course content has been selected, in consultation with the Chemical Engineering discipline to provide the necessary mathematical training that will assist and expand your learning experience within your discipline of study. Topics include: Laplace transforms, polynomial interpolations and approximations, finite element method- preliminary mathematics foundation and finite element methods and its engineering applications.

Objectives/Learning Outcomes/Capability Development

On successful completion of this course, you should be able to:

1. Manipulate Laplace transforms and their inverses; effectively use tables of Laplace transforms and operational formulae; and solve appropriate initial value problems’ using Laplace transforms.
2. Obtain polynomial interpolating functions for approximating complex mathematical functions of engineering problems and/or describing experimental data mathematically.
3. Use the mathematical foundations of the Finite Element Method (FEM) in the approximate solutions of engineering problems.
4. Apply the Finite Element Method (FEM) to solve structural engineering problems that a chemical engineer will meet in a process plant using ANSYS – one of the industrial engineering simulation software used internationally.
5. Demonstrate relevant capacities in problem solving, critical thinking and report writing.

This course contributes to the following Program Learning Outcome for
• BH079 - Bachelor of Engineering (Chemical Engineering) (Honours)
• BH098 - Bachelor of Science (Applied Chemistry) / Bachelor of Engineering (Chemical Engineering) (Honours)
• BH099 Bachelor of Science (Food Technology & Nutrition) / Bachelor of Engineering (Chemical Engineering) (Honours)
• BH087 - Bachelor of Engineering (Chemical Engineering) / (Honours)/Bachelor of Science (Biotechnology)
• BH085 - Bachelor of Engineering (Chemical Engineering) (Honours) / Bachelor of Business (Management).
1.2. Conceptual understanding of mathematics, numerical analysis, computer and information sciences which underpin the engineering discipline.

Overview of Learning Activities

This course is presented using a mixture of classroom instruction; in-class problem-based exercises; online quizzes and nline tests; and problem-based computer laboratory assignments.
Primarily you will be learning in face-to-face lectures where key concepts and their applications will be explained and illustrated with many examples.
An online course site will be used to disseminate course materials, provide you access to online quizzes and online tests and to submit the problem-based computer laboratory assignments.
Problem-based weekly exercises will build your capacity to solve problems and to think analytically and critically. Mathematical theories and applications will also be reinforced through the online quizzes and tests. Online quizzes are designed to provide instant feedback and can be attempted as many times as you like until proficiency in the learning objectives is achieved before you attempt the corresponding online tests. The computational laboratory sessions are designed to assist students in learning to use the industrial engineering simulation software ANSYS. Assignments will enhance your understanding of mathematical theories and help you to develop  abilities in applying mathematical theories to analyse and solve real engineering problems.
Sample exam style questions are provided to assist in your preparation for the final examination.

Teacher Guided Hours: 4 hours per week (3 lecture hours and 1 computer lab hour).
Learner Directed Hours: 6 hours per week (Online quizzes and tests; weekly exercises; and computer assignments).

Overview of Learning Resources

A Canvas site links to the course Google site where you will find:

1. Teaching schedule and suggested reading
2. Assessment guide and assessment schedule.
3. Guide to online tests.
4. Lecture slides.
5. Computer lab guides for using Excel in statistics
6. Assignment papers
7. Recommended references.
8. Tables and formula sheets.
9. Weekly exercises and answers.
10. Practice exam questions.

You can access Maths learning resources through myDesktop (http://rmit.libguides.com/mathstats).
You can access industrial simulation software ANSYS in the Maths department computer labs: 8.9.48, 8.9.49 and 8.9.58, Chemical engineering computer labs and the RMIT University 24 hours computer lab, 28.03.002.
Access to ANSYS software is available by downloading the free ANSYS Student software version at the following website: http://www.ansys.com/Student on to their personal computers. You can learn to use ANSYS in  your own time and location,  not only during this course of study but also in your future career.

Overview of Assessment

This course has no hurdle requirements.

Early Assessment Task:  (Weeks 2-6), Online Tests
Weighting: 12%
This assessment task supports CLO (1)

Assessment Task 2: Tests
Weighting: 18%
This assessment task supports CLOs (1),(2),(3),(4).

Assessment Task 3: FEM Assignments
Weighting: 20%
This assessment task supports CLOs (4), (5).

Assessment Task 4:  End of semester Exam (2-hour open book)
Weighting: 50%
This assessment task supports CLOs: (1),(2),(3),(4),(5).