The University of Southampton

FEEG1001 Design and Computing

Module Overview

This course develops your skills in design and computing with practical hands-on engineering to enable you to design, build and test artefacts relevant to your discipline. From the design component of the module you will be introduced to modern computer aided design techniques and geometry modelling and how they are used in your discipline illustrated further by examples drawn from across the full range of engineering. For the computing component you will understand both fundamental programming and numerical methods how to apply these to practical engineering problems across engineering. In addition you will participate in hands-on activities to build artefacts in your engineering discipline and understand the skills required to use a modern engineering workshop. You will work both individually on laboratory and practical assignments and also in groups on design, build and test activities. This sophisticated mix of design, computing and hands-on practical skills will be built on in future years of your degree programme to enable you to develop complex engineering systems and devices relevant to your discipline.

Aims and Objectives

Module Aims

• Introduce basic engineering hand sketching • Introduce 3D computer aided design (CAD) • Introduce the process of design from sketching through to parametric 3D CAD and 2D orthographic drawings to BS 8888 • Introduce basic manufacturing techniques • Encourage students to analyse the design of engineering artefacts critically • Understanding of programming principles • Introduction to computational modelling and numerical methods • Discipline-specific case studies and examples

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • Parametric design
  • The conventions of formal engineering drawing
  • Simple manufacturing techniques
  • Fundamental programming techniques
  • Linear and non-linear equations and solution strategies
  • A variety of numerical and computational methods used in computational modelling
  • Data handling & processing and visualisation methods
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Appreciate the key elements of engineering design
  • Appreciate the role of computers in both design and manufacture
  • Identify types of problems to pick the right computational solution strategy
  • Analyse computer programs to understand their structure
  • Design and implement small computer programs independently
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Produce basic designs both individually and through team working
  • Communicate a design idea/concept graphically
  • Examine a design critically and with understanding
  • Decompose a (mathematical) model of engineering systems and processes into smaller tasks that can be solved sequentially (by a computer)
  • Understand the concepts behind software engineering and design decisions in modelling software
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • Use precision measurement instruments found in a workshop (metrology)
  • Use workshop hand tools to produce an artefact in sheet metal
  • Undertake basic welding (MIG)
  • Produce and interpret 2D & 3D drawings
  • Use a lathe and mill to carry out simple machining
  • Use the Python programming language confidently for data processing and visualisation and solution of computational modelling/ numerical problems


There are two parts to the syllabus covering the design and the computing material. 1) DESIGN Design basics - Design methodology - Sketching (isometric) & geometry parameterization - Fits and tolerance - 2D drawings and sketching of assembly and parts - Drawing conventions to BS 8888 Computational Geometry I - Part modeling - basics - Part modeling - forging and patterning - Modelling revolution features and shell ribs - Design tables Design Exercises (by discipline) Discipline exemplars include: - 3D printed acoustical artefact - 3D printed wing & SolidWorks CFD / wind tunnel testing - 3D printed mechanical artefacts - 3D printed propeller / keel Computational Geometry II - Parametric modelling - Complex surface generation (NURBS & lofts) - Bottom-up assembly modeling - SolidWorks FEA basics - (discipline specific) Complex geometry: Surfaces (Faired lines plan) Workshop Skills (certificate) - In-house and external (intensive) Workshop skills including Metrology, Sheet Metal & Welding, CNC, lathe, mill, professional engineering, maintenance, tapping and drilling. 2) COMPUTING & COMPUTATIONAL MODELLING a) Computing • Introduction to computing – exemplars • Programming Building Blocks - Variables, data types, objects - Functions - Lists, tuples, strings - Loops and branching - Files and modules - Exceptions and testing • Modular program design: prototyping, functions, modules • Advanced programming techniques, robust software engineering, PEP8 style guide • Visualisation and data processing/ handling (matplotlib) • Python for Computational Modelling - Numpy, Scipy, Sympy, iPython, Spyder - Case Studies/ Exemplars b) Computational Modelling • Solution of Linear Systems - Gaussian Elimination - LU Decomposition • Interpolation and curve Fitting - Least squares - Polynomials - Splines • Numerical Integration - Trapezium - Simpson - Adaptive quadrature - Advanced techniques • Roots of an equation - 1D Bisection, - Secant, - Newton-Raphson, - Hybrid and multidimensional non-linear c) Computing skills • Getting Started • Simple Functions • Working with sequences, list comprehension • File input and output • Lists, File, Exceptions, Strings • Higher Order Functions, Closures • Dictionaries, Recursion • Linear algebra; interpolation; integration; root finding • Symbolic computation

Special Features

Design • The design build and test exercises test the students’ ability to work on an engineering design project as a group. The group will communicate those ideas graphically, build using newly acquired skills (or technology – 3D printing) and finally test the project. • Practical hands-on engineering workshop skills run internally and externally Computing and Computational Modelling • The self-paced problem solving with a computer in the presence of demonstrators is the key activity to engage the student with the material and achieve deep learning.

Learning and Teaching

Teaching and learning methods

We use a variety of group teaching, computer based labs along with practical workshops for individual work and in groups throughout the course. Design: A course of 20 x 1.5h supervised and guided labs (each per week throughout semesters 1 & 2), supported by an introduction of 3 double lectures. The lectures are delivered at the start of the course and can either be to the combined cohort or repeated by degree programme. The lectures are used to introduce new material which is developed through self-paced computer lab based exercises and group design tasks. During the practical sessions, students tackle a set of tasks designed to develop their understanding of the design process and the use of computational geometry. Academic staff and demonstrators are available to answer questions and support the learning activity. The first group-based design task takes place over five days during a two week period at the end of semester I. An intensive three day design period, after which the designs are 3D printed and is followed by two days of testing/critical analysis. The second task takes place during semester II, with elements of the semester II syllabus building towards the final design and construction of an artefact which is specific to each programme. In addition we provide practical workshop skills through a series of 3 hour labs run internally and an intensive external two-day course where you will learn a number of skills key to enabling you to build engineering artefacts throughout your degree programme. Computing and Computational Modelling: A course of 36 lectures is accompanied with 11 supervised practical exercises, which are scheduled to take place throughout the delivery of the material. The lectures are for the combined cohort and are balanced by the smaller classes for the labs and the high availability of staff/ demonstrators during these sessions. The lectures are used to demonstrate new concepts and to discuss solution strategies for given problems. During the practical sessions, students solve a set of programming/numerical tasks using a computer in a self-paced fashion. Academic staff and demonstrators are available to answer questions and support the learning activity. On completion of the exercises, students email the program they have written to a particular email account, where the program will be automatically tested and automatic feedback provided within a couple of minutes. The feedback comes back to the student’s email inbox. Each laboratory session is split into two parts: (i) the training component and (ii) the assessed component. For the training part, students can submit their files repeatedly to the email account to get feedback and to iteratively refine their program (with the help of demonstrators if required). For the assessed part, the first submission that is sent by email will be used to allocate a small mark for each lab session. In total, these marks contribute 10% to the computing mark. Students rate this automatic testing and feedback system highly, as (i) the response and thus feedback provision is virtually instantaneous, (ii) the testing is objective and thorough, (iii) students can make use of the automatic testing as many times as they like until they have found a working solution, and (iv) they can start the exercise before the scheduled laboratory session. Throughout the course there are additional guided tutorial sessions should extra help be required. Student support during module study: - Feedback on common mistakes made in the laboratory sessions will also be provided in the lectures. - Individual support (by appointment, through optional tutorials). - Weekly 2-hour open surgery session which students are invited to attend in addition to scheduled laboratory sessions.

Supervised time in studio/workshop48
Completion of assessment task96
Practical classes and workshops20
Project supervision28
Preparation for scheduled sessions48
Total study time300

Resources & Reading list

Burden, RL and Faires, JD (2005). Numerical Analysis. 

Numerical Recipes in C” , “Numerical Recipes in Fortran”, “Numerical Recipes 3rd Edition”.

Module teaching notes. 

Jaan Kiusalaas (2010). Python book on Numerical Methods with a focus on Engineering, “Numerical Methodsin Engineering with Python”. 

Paul DeVries (1993). A first course in Computational Physics. 

David Kincaid and Ward Cheney (1996). Numerical Analysis. 

Course notes (for design and computing). Module teaching notes from design lectures and Solidworks/ AutoCAD lab manuals/ notes as per Annex 1.

Software requirements. Free Python software available from

How to think like a Computer Scientist.

H P. Langtangen (2003). Python Scripting for Computational Science. 


Assessment Strategy

The learning outcomes of this module will be assessed under the Part I Assessment Schedule for FEE Engineering Programmes which forms an Appendix to your Programme Specification. Feedback will be available on the formative work undertaken during the module.


MethodPercentage contribution
Part I Assessment Schedule 100%
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