- UCAS course code
- H800
- UCAS institution code
- M20
Bachelor of Engineering (BEng)
BEng Chemical Engineering
Duration: 3 years
Year of entry: 2025
UCAS course code: H800 / Institution code: M20
- Key features:
Scholarships available
Accredited course
- Typical A-level offer: AAA including specific subjects
- Typical contextual A-level offer: AAB including specific subjects
- Refugee/care-experienced offer: ABB including specific subjects
- Typical International Baccalaureate offer: 36 points overall with 6,6,6 at HL, including specific requirements
Course unit details:
Computational Methods for Chemical Engineering
| Unit code | CHEN10051 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 1 |
| Teaching period(s) | Semester 1 |
| Available as a free choice unit? | No |
Overview
The unit will cover the following topics:
1. Fundamentals of Programming
- Introduction to programming concepts: variable types, number formats, and mathematical operations.
- Use of built-in functions and Python libraries for engineering applications, data analysis, and visualization.
- Graphical data representation and visualization techniques.
- Understanding algorithms, writing programs, and creating user-defined functions.
Program debugging, as well as data input and output handling.
2. Numerical Methods Using Python and NumPy
- Solving roots of equations and performing one-dimensional and multi-dimensional optimization.
- Methods for solving systems of linear algebraic equations.
- Techniques for numerical integration.
- Solving ordinary differential equations (ODEs) using numerical approaches.
3. Mathematical Formulation of Chemical Engineering Problems
- Translating chemical engineering problems into mathematical models.
- Identifying appropriate mathematical structures and equations to describe chemical engineering systems.
4. Numerical Solutions to Chemical Engineering Problems
- Applying numerical methods to solve mathematical models derived from chemical engineering problems.
- Using modern programming tools such as Python and relevant libraries to implement solutions.
5. Introduction to Data Analysis and Problem Exploration Using Programming
- Exploring chemical engineering problems through data analysis and coding as tools of inquiry.
- Formulating hypotheses, analyzing datasets, and building data-driven models.
Integrating programming with scientific reasoning to enhance problem-solving skills.
Aims
The unit aims to:
To provide the essential computational skills required for solving and analysing chemical engineering problems.
Learning outcomes
On successful completion of CHEN10051, a student will be able to…
LO1. Identify and formulate appropriate mathematical structures and equations to describe chemical engineering systems and their behaviour.
LO2. Select suitable numerical methods to solve chemical engineering problems represented as mathematical models.
LO3. Develop, debug, and validate algorithms to numerically solve mathematical models of chemical engineering systems.
LO4. Utilize computer programs as essential tools for inquiry in chemical engineering research and data analysis.
Teaching and learning methods
Lectures provide fundamental aspects supporting the critical learning of the module and will be delivered as pre-recorded asynchronous short videos via our virtual learning environment.
Synchronous sessions will support the lecture material with Q&A and problem-solving sessions where you can apply the new concepts. Surgery hours are also available for drop-in support.
Feedback on problems and examples, feedback on coursework and exams, and model answers will also be provided through the virtual learning environment. A discussion board provides an opportunity to discuss topics related to the material presented in the module.
Students are expected to expand the concepts presented in the session and online by additional reading (suggested in the Online Reading List) in order to consolidate their learning process and further stimulate their interest to the module.
Study budget:
- Core Learning Material (e.g. recorded lectures, problem solving sessions): 24 hours
- Self-Guided Work (e.g. continuous assessment, extra problems, reading) : 44 hours
- Exam Style Assessment Revision and Preparation: 32 hours
Assessment methods
Assessment Types | Total Weighting |
| Final exam | 80% |
| Online test | 20% |
Feedback methods
| Assessment task | How and when feedback is provided |
| Exam
| Generic exam feedback form after exam board |
| Online test on Excel | Final mark only one week after the assessment. |
Recommended reading
Reading lists are accessible through the Blackboard system linked to the library catalogue.
Study hours
| Independent study hours | |
|---|---|
| Independent study | 44 |
Teaching staff
| Staff member | Role |
|---|---|
| Lev Sarkisov | Unit coordinator |