CHEN20070 Computers in Chemical & Bioprocess Engineering

Academic Year 2023/2024

In this module students develop further (advancing from CHEN10040) their core skills in the use of Matlab and MS Excel, including VBA, for the purpose of solving more advanced problems in the context of Chemical & Bioprocess Engineering. This will be done, in part, through a rigorous study of a number of numerical techniques frequently used for solving such problems, but will also involve more advanced problem solving considerations (sustainability, ethics, data analytics, data management).

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Curricular information is subject to change

Learning Outcomes:

On completion of this module students should be able to,

1. Use the Matlab and Visual Basic for Applications(VBA) programming environments and to develop complex programs using the extensive functionality of both.
2. Solve chemical and bioprocess engineering problems, which require significant numerical programming by means of the Matlab and VBA programming environments, including subject to additional constraints (sustainability, ethics).
3. Recognise the importance of validation in the complete solution to a numerical problem and the ability to use either hand-calculation or spreadsheet based computation to verify Matlab program results.
4. Big Data, data Integrity, data management, version control.
5. Report and communicate the results of numerical calculations in a clear, rigorous and concise manner.

Indicative Module Content:

Students will learn to apply selected numerical methods in the solution of chemical engineering based problems using Matlab and Excel. The module content will cover selected topics from the following,

1. The nature of the problem: sustainability & ethics
2. Problem solving, data management, data control, integrity.
3. Algorithms, Precision & Errors
4. Solutions of Non-Linear Equations
5. Solution of Systems of Non-Linear Algebraic Equations
6. Iterative Solutions of Systems of Linear Equations
7. Polynomial Interpolation
8. Cubic Spline Interpolation
9. Linear Regression
10. Data Smoothing & Differentiating
11. Non-Linear Regression
12. Numerical Integration
13. Numerical Solution of Ordinary Differential Equations
14. Partial Differential Equations

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Computer Aided Lab

24
Autonomous Student Learning

72
Total

120
Approaches to Teaching and Learning:
This module will include a mixture of lectures (topic delivery) and computer laboratories (skills practice). 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Pre-requisite:
CHEN10040 - Intro. to Eng. Computing


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Computer-based assignment 3 Week 12 n/a Other No

12
Class Test: Mid-term examination Week 7 n/a Other No

21
Class Test: End-of-Semester Class Test Week 12 n/a Other No

43
Assignment: Computer-based assignment 1 Week 5 n/a Other No

12
Assignment: Computer-based assignment 2 Week 9 n/a Other No

12

Carry forward of passed components
Yes
 
Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

n/a

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Spring
      
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 11:00 - 11:50
Computer Aided Lab Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 15:00 - 16:50
Spring