Module overview
Modern engineering increasingly relies on high-performance computing, numerical modelling and robust software to solve problems that would be impossible using analytical methods alone. This module builds on your earlier programming experience, developing the advanced computational skills needed to create efficient, reliable engineering software for scientific and engineering applications.
You will learn advanced programming techniques using C and compiled languages while exploring software engineering principles, numerical methods and computational modelling. Through laboratory sessions and programming assignments, you will develop, test and optimise engineering software, gaining experience of writing efficient code, implementing numerical algorithms and solving increasingly complex engineering problems. Throughout the module, emphasis is placed on producing software that is both computationally efficient and scientifically reliable.
By the end of the module, you will be able to develop high-performance computational solutions for engineering analysis and modelling, providing valuable skills for careers in simulation, digital engineering, scientific computing, robotics, artificial intelligence and engineering research.
Aims and Objectives
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- The C-programming language.
- Version control and one version control tool.
- Shell commands.
- Remote and local use of Linux computers.
- Complied versus interpreted language.
- Symbolic methods and code generation.
- Combining C-code with Python.
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Use strategies to effectively address computational bottlenecks with Python and C code.
- Decompose a computational problem into small parts. - analyse the computational bottleneck.
- Develop makefiles and test programs.
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Write, compile and run C-programs.
- Learn the steps in the C-program development cycle.
- Connect to the Linux server.
- Check error messages generated by the compiler.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Use a computer to perform computational modelling studies.
- Apply software engineering techniques for science and engineering.
Learning Outcomes
Having successfully completed this module you will be able to:
- C1/M1 As part of the individual assignment, the student must use a computer to perform computational modelling studies and demonstrate comprehensive understanding of software engineering techniques for science and engineering. C2/M2 As part of the individual assignment students must use data files and decompose a computational problem into small parts-analyse the computational bottleneck using first principles of numerical methods and programming language. C3/M3 As part of the individual assignment, the student must demonstrate understanding of C-programming language, combining C-code and Python, use numerical and analytical techniques to address complex engineering problems. C4/M4 As part of the individual assignment, write compile and run C-programmes to find solutions for advanced software engineering problems using relevant technical literature. C5/M5 As part of the individual assignment students must discuss modern computational software techniques and apply C-programme language with code of practice to solve complex engineering problems. C6/M6 As part of the individual assignment students must use strategies to effectively address computational bottlenecks with C-programming codes, decompose a computational problem into small parts. - analyse the computational bottleneck for complex problems. C12/M12 As part of the laboratory assignment students must write, compile and run C-programmes for computational modelling problems. C15/M15 As part of the individual assignment students must apply knowledge of software engineering tools and computer programme languages to solve advanced engineering problems with commercial context. C16/M16 As part of the individual assignment the student must demonstrate knowledge and understanding of software engineering techniques for science and engineering.
Syllabus
Programming:
- Introduction to operating systems, shells.
- Introduction compiled and interpreted languages, with examples C, Python, Matlab.
C-Programming:
- Data types and number representation
- Data output.
- Loops and conditionals.
- Special operators.
- Integer division and casting.
- Functions.
- Arrays.
- Pointers and memory allocation.
- Examples.
Software engineering for computational science and engineering:
- Efficient program design and implementation: linking high level (Python) code with C code,
- Cython, ctypes,
- Tests and Test Driven Development,
- Makefiles.
- Version control (git).
- Linux terminal and shell scripting.
- Remote working with SSH.
Computational Methods:
- Applied Computational Methods – examples.
- Symbolic methods and auto generation of code.
Learning and Teaching
Teaching and learning methods
Teaching methods include
- Lectures and computer programme lab sessions.
Learning activities include
- Individual programming practice to enhance breadth of understanding.
- Problem solving in supervised lab sessions and through assignments.
- Informal help session.
| Type | Hours |
|---|---|
| Wider reading or practice | 20 |
| Lecture | 24 |
| Completion of assessment task | 26 |
| Follow-up work | 48 |
| Practical classes and workshops | 20 |
| Preparation for scheduled sessions | 12 |
| Total study time | 150 |
Resources & Reading list
General Resources
Course Notes.
Internet Resources
Hans Fangohr: “Python for Computational Science and Engineering“.
Assessment
Assessment strategy
Feedback: Feedback throughout lab sessions.Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Final Assessment | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Set Task | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Set Task | 100% |
Repeat Information
Repeat type: Internal & External