An engineer who can solve complex mathematical equations is demonstrating strong

Mathematics is an essential tool for solving many engineering problems. You will  frequently use mathematics  in many of the courses you take as part of your engineering degree, so a strong mathematical foundation is vital.  This course assumes a thorough grounding in secondary school mathematics (including differentiation and integration) and builds upon this.  By the end of the course you should understand the mathematical modelling process and have developed proficiency in a range of  key mathematical techniques.  Your mathematics skills will be further developed in the follow up course, Mathematical Modelling 2 (ENGSCI 211).

Below is an overview of the skills developed in each of the sections of the course.

Mathematical Modelling

• Application of the mathematical modelling process, including the use of free body diagrams to formulate mathematical models from a word problem.

• Comprehend given proportionality relationships and then apply them to formulate mathematical models.

• Application of dimensional analysis to create and/or check the dimensional consistency of a model. 

• Application of function approximation to simplify a model for large or small values.

• Application of function optimisation by applying differential calculus. 

Modelling with Uncertainty

• Application of probability techniques including probability distributions, probability trees and Bayes theorem to compute the the probability of particular events/random variables given a situation described in words. 

Differentiation & Applications 

• Application of differentiation to solving relates rates of change problems, including the use of the chain rule to formulate the problem and implicit differentiation to find derivatives.

• Application of the formula for various types of series to determine polynomial approximations for functions, including the use of Maclaurin, Taylor and binomial series. 

• Application of finite difference formula for finding numerical derivatives using discrete tabulated data. 

• Comprehension of when polynomial approximations are valid (i.e. when they converge). 

Integration

• Application of integration techniques to compute integrals including the use of integration by substitution, parts and partial fractions. 

Ordinary Differential Equations

• Application of mathematical modelling to create Ordinary Differential Equations describing physical systems, identifying appropriate initial conditions where relevant. 

• Comprehension of different types of Ordinary Differential Equations, in order to classify them and identify the appropriate method of solution. 

• Application of appropriate types of solutions methods to relevant first order ODEs including the methods of direct integration, separation of variables, integration factor and Euler's method. 

• Application of boundary/intial conditions to solve spatially-varying/time-dependent systems described by an ODE, including finding and identifying steady state solutions. 

• Application of the method of exponential trial to solve second order, linear, homogeneous ODEs that have a characteristic equation that has distinct real roots. 

Vectors and Matrices

• Application of vector operations to solve 2/3D geometric problems described in words. 

• Application of matrix algebra in a physically meaningful context including geometric transformation and transitions matrices. 

• Application of linear algebra techniques to solving systems of linear equations.

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