# REACTION ENGINEERING AND NUMERICAL METHODS - 2020/1

Module code: ENG2113

## Module Overview

The heart of any chemical or biochemical process is often said to be the reactor and a sound understanding the unit’s performance is a pre-requisite for the process design. This module builds on the reaction kinetics knowledge from level 1 and applies it to the design of homogeneous reactors and bioreactors. The design equations of such reactors often results in differential equations which require the application of standard numerical methods and the application of Matlab facilitates such a solution.

### Module provider

Chemical and Process Engineering

RAMIREZ REINA Tomas (Chm Proc Eng)

### Module cap (Maximum number of students): N/A

Independent Learning Hours: 89

Lecture Hours: 39

Tutorial Hours: 22

Semester 2

## Prerequisites / Co-requisites

Completion of the progression requirements to FHEQ Level 5 of the degree courses in Chemical Engineering, Chemical and Bio-Systems Engineering and Chemical and Petroleum Engineering, or equivalent.

## Module content

​Indicative content includes:

Numerical Methods:

• Roots of nonlinear equations, bisection method, simple iteration, Newton-Raphson method

• Solution of single ordinary differential equation by Euler & 4th order Runge-Kutta methods, deviation, errors, applications

• Numerical Integration, Trapezoidal rule, Simpson’s rule, errors, applications

• Solution of systems of non-linear equations, Gaussian elimination with inclusion of partial pivoting Gauss-Seidel iteration

Reaction Engineering:

Introduction to reactor design

Batch Reactors

• Types, uses and design equations

• Isothermal and non-isothermal design

Continuous Stirred Tank Reactors (CSTR)

• Uses, perfect mixing, design equations

• Single tank design

• CSTR with changing volumetric flow rates

• Multiple tank algebraic and graphical design

• Size and performance comparison CSTR vs PFR

Plug Flow Reactors (PFR)

• Uses and design equations

• Isothermal design

• PFR with changing volumetric flow rates

• Multiple plug flow reactors in series and parallel

• Plug flow reactors with recycle

• Mixed systems PFR-CSTR

• non-isothermal design

Design for Multiple Reactions

• Competitive Reactions

• Consecutive Reactions

• Selectivity/Yield in multiple reactions

• Microbial kinetics-Balanced Growth and the Monod Equation

• Bio-reactor Design (application of the chemical reactors into biological problems)

• Inactivation Bio-processes (sterilisation & irradiation)

## Assessment pattern

Assessment type Unit of assessment Weighting
Coursework COURSEWORK 20
Coursework NUMERICAL METHODS COURSEWORK 20
Examination EXAMINATION (2 HOURS) 60

N/A

## Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate

the full range of learning outcomes though the balanced mixture of lecture and tutorial/problem classes coupled with the carefully grades tutorial problems which reflect current industrial practice.

Thus, the summative assessment for this module consists of:

• Examination – 50%, 2 hours (LO1, LO2, LO3, LO4, LO5, LO6, LO7)

• Course Work – 25% (LO6, LO7)

• Reactor Design Project – 25% (Group project)

Formative assessment and feedback

• Two formative multiple choice tests will take place in the reaction engineering lectures followed by verbal feedback and open discussion during the lectures

## Module aims

• Allow students to develop a comprehensive understanding of the methodology of linking chemical kinetics with material and energy conservation in the design of idealised homogeneous chemical reactors, operating either in batch or continuous mode, and under either isothermal or non-isothermal conditions.
• Introduce students to the analysis of non ideal flow and, using the Dankwerts flow model, show its effect on both an idealised reactor design and sampling.
• Provide students with knowledge and experience of using standard numerical methods in order to solve complex engineering problems
• Provide students with knowledge and experience of using Matlab and programming in order to solve complex engineering problems

## Learning outcomes

 Attributes Developed 001 Explain the operation of homogeneous Batch, Continuous Stirred Tank and Plug Flow reactors and confidently propose the appropriate reactor for a specified duty KC 002 Propose a reactor design methodology and then correctly solve the volumetric design of homogeneous Batch, Continuous Stirred Tank and Plug Flow reactors processing simple reversible and irreversible reactions operating under both isothermal and non-isothermal KCP 003 Design of complex arrangements of ideals reactors including multiple reactors in series, parallel and combination series-parallel. KCP 004 Explain the complexity of reactor design, the need for safe design and the responsibilities of the designer of chemical reactors and bio-reactors KP 005 Explain the operation of homogeneous Batch, Fed-Batch, CSTR AND Plug Flow biochemical reactors and confidently propose the appropriate reactor type for a specific bioprocess KC 006 Evaluate the reactor characteristics in chemical and bio-reactors KCP 007 Use a range of standard numerical methods to solve complex engineering problems KCP 008 Use Matlab and programming as a tool to solve engineering problems particularly those associated with homogeneous reactor design KCPT 009 Application of numerical tools to ideal reactors design K

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

## Methods of Teaching / Learning

The learning and teaching strategy is designed to:

• Carefully cover in lectures the necessary fundamental material and analytical techniques, and demonstrate concepts with appropriate (and where possible practical) examples

• Allow students adequate time to practice the techniques using a large number of carefully selected tutorial problems.

The learning and teaching methods include:

• Lectures                                3.4 hours per week for 11 weeks (average)

• Tutorial/Problem Classes        3 hour per week for 10 weeks  (average)

• Independent learning               8.5 hours per week for 11 weeks (average)

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.