DCU Home | Our Courses | Loop | Registry | Library | Search DCU
<< Back to Module List

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title Numerical Problem Solving for Engineers
Module Code EEG1005 (ITS: EM114)
Faculty Electronic Engineering School Engineering & Computing
NFQ level 8 Credit Rating 5
Description

This module is intended to complement the formal, analytical mathematical theory presented in Engineering Mathematics I and II and focuses on practical problem-solving skills. This includes problem specification skills, problem solving skills, numerical skills as well as visualisation and verbal skills. The module will integrate 1st year students’ mathematical knowledge more comprehensively with the real world and other first year modules. A particular focus is on the practical use of computers: both as a visualisation and instructional aid for mathematics and also as a flexible tool for analysing and solving complex, unfamiliar problems.

Learning Outcomes

1. Divide a larger technical problem into a series of sub-problems, identifying the inter-relationship and dependencies between them.
2. Identify the appropriate mathematical techniques required to solve the constituent elements of a large engineering problem.
3. Identify and apply suitable approximations needed to reduce the complexity of a problem and render it suitable for analysis.
4. Formulate algorithms capable of implementing these techniques discretely on a computer and articulate these algorithms in the form of a flowchart.
5. Translate algorithms into appropriate basic computer code.
6. Design and implement tests to assess the accuracy and efficiency of the resultant computer – based solutions.
7. Understand information expressed visually and design and implement appropriate visualisation methods for any problems being examined.


WorkloadFull time hours per semester
TypeHoursDescription
Lecture24Problem based learning approach to engineering problems tractable to numerical solution.
Laboratory10Supported learning to solve computing problems using a high level programming language. Implementation of techniques outlined in lectures and studied independently.
Independent Study90Formulation of solutions to problems similar to those posed in lectures.
Directed learning1Individual class test to solve problems.
Total Workload: 125
Section Breakdown
CRN20137Part of TermSemester 2
Coursework0%Examination Weight0%
Grade Scale40PASSPass Both ElementsY
Resit CategoryRC1Best MarkN
Module Co-ordinatorDonnacha LowneyModule TeacherConor Brennan, Marissa Condon
Assessment Breakdown
TypeDescription% of totalAssessment Date
In Class TestComputerised class test.20%Week 7
Practical/skills evaluationFive laboratory sessions to be completed.60%Every Second Week
Short Answer QuestionsExercises implemented on a STEM online homework system.20%Every Second Week
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
RC1: A resit is available for both* components of the module.
RC2: No resit is available for a 100% coursework module.
RC3: No resit is available for the coursework component where there is a coursework and summative examination element.

* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Visualisation
Plotting functions: polynomial, exponential, trigonometric, logarithmic, rational, piecewise. Plotting the functions, their derivatives and integrals, and interpreting the relationship between the resultant curves. Taylor series approximations to functions – accuracy, dependence on expansion point, remainder term, linear approximation. Representing and manipulating complex numbers in computer code. Visualising the complex plane, Argand diagrams. Representing and manipulating vectors in computer code. Visualising vectors and vector operations, cross and dot products etc.

Curve fitting
Choosing and fitting curves to real-life data, i.e. a periodic curve to real-life tidal height data, exponential curve to real-life population growth data, polynomial interpretation using Vandermonde technique etc.

Vectors
Basic manipulation of vectors. Develop an algorithm to determine whether a point is inside or outside a polygon (application of cross product and dot product). Write code to determine the intersection between two line segments, or line segment and plane. Application of above to determine whether line of sight (LOS) exists between GPS satellite and receiver in presence of buildings, or whether LOS exists between sun and solar energy panel.

Complex numbers
Visualisation of complex plane, visualisation of mathematical operations involving complex numbers (e.g. Develop an algorithm to generate the Mandelbrot fractal).

Matrix Algebra
Examples of large linear systems from engineering. Solution via Gaussian elimination.

Calculus
Identification of maxima and minima. Maximum power transfer – Simulation of maximum power transfer theorem and comparison with analytical result (from EEG1004). Ballistics – Simulation of simple projectile motion and identification of maximum range, point of maximum height etc. Comparison with analytical result (from EEG1003). Generation of simple “angry birds” type game (in conjunction with root finding).

Introduction to numerical methods
Forward backward and central difference, Euler integration, computation of sequences and series, root finding via Newton-Raphson and bisection methods, Euler method for solution of ODEs.

Indicative Reading List

Books:
  • Timo Heister,Leo G. Rebholz: 2023, Scientific Computing, de Gruyter, 978-3-1109-9961-7
  • Thomas Povey: 2015, Professor Povey's Perplexing Problems, Oneworld Publications, 384, 978-1-7807-4775-0
  • Sandeep Nagar: 2017, Introduction to Python for Engineers and Scientists, Apress, 978-1-4842-3203-3
  • John Wiley & Sons Australia, Limited,Pearson Education Canada,Prentice Hall Books: 1991, RV Park and Campground Directory, 1991, Prentice Hall General, 496, 978-0-1302-6857-7
  • Polya: 1990, How to solve it: A new aspect of mathematical method, Penguin, 978-0-1401-2499-6


Articles:
None
Other Resources

None

<< Back to Module List View 2024/25 Module Record for EM114