Undergraduate Teaching 2025-26

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Engineering Tripos Part IIB, 4M17: Practical Optimisation, 2021-22

Module Leader

Prof R Sepulchre

Lecturers

Prof R Sepulchre and Dr G Parks

Timing and Structure

Michaelmas term. 13 lectures + 3 computer lab sessions. Assessment: 100% coursework

Prerequisites

3M1

Aims

The aims of the course are to:

  • Teach some of the basic optimisation methods used to tackle difficult, real-world optimisation problems.
  • Teach means of assessing the tractability of nonlinear optimisation problems.
  • Develop an appreciation of practical issues associated with the implementation of optimisation methods.
  • Provide experience in applying such methods on challenging problems and in assessing and comparing the performance of different algorithms.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Understand the basic mathematics underlying linear and convex optimisation.
  • Be able to write and benchmark simple algorithms to solve a convex optimisation problem.
  • Understand the technique of Markov-Chain Monte Carlo simulation, and apply it to solve a Travelling Salesman Problem.
  • Understand the ways in which different heuristic and stochastic optimization methods work and the circumstances in which they are likely to perform well or badly.
  • Understand the principles of multiobjective optimization and the benefits of such of approaching real-world optimization problems from a multiobjective perspective.

Content

  • Introduction (what is Practical Optimisation ?)
  • Approximately solving Ax=b (various methods of norm minimization of residuals that lead to LP or convex problems)
  • Geometry of polyhedral and convex sets (review of the simplex method; introduction to algorithmic complexity)
  • Duality theory and its applications
  • Unconstrained optimisation
  • Important convex relaxations in cardinality problems 
  • Simulated Annealing: basic concepts, solution representation and generation, the annealing schedule, enhancements and modifications
  • Genetic Algorithms: basic concepts, solution representation, selection, crossover, mutation
  • Tabu Search: basic concepts, solution representation, local search, intensification, diversification
  • Multiobjective Optimization: archiving, multiobjective simulated annealing, multiobjective genetic algorithms
  • Case Study: multiobjective optimization of pressurised water reactor reload cores

Coursework

Coursework

Format

Due date

& marks

Coursework activity #1: Investigation of a moderate size Linear Regression problem with various norm and regularization approximations

Learning objective: 

  • convert a regression problem into a linear program and solve it with linprog
  • program a simple line search algorithm and experiment the impact of smoothness on convergence rate.
  • understand how different norms affect the solution of an approximation problem.

Individual report

anonymously marked

Deadline: 10th December 2021

[30/60]

Coursework activity #2: Investigation of the performance of two stochastic optimization methods on a hard problem

Learning objective: 

  • gain experience in applying stochastic optimization methods to challenging problems
  • explore and analyse the variation in optimizer performance as algorithm control parameters are modified
  • compare and analyse the performance of different optimization methods on challenging problems

Individual report

anonymously marked



Deadline: 19th January 2022

[30/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 27/09/2021 09:31

Engineering Tripos Part IIB, 4M17: Practical Optimisation, 2020-21

Module Leader

Prof R Sepulchre

Lecturers

Prof R Sepulchre and Dr G Parks

Timing and Structure

Michaelmas term. 13 lectures + 3 computer lab sessions. Assessment: 100% coursework

Prerequisites

3M1

Aims

The aims of the course are to:

  • Teach some of the basic optimisation methods used to tackle difficult, real-world optimisation problems.
  • Teach means of assessing the tractability of nonlinear optimisation problems.
  • Develop an appreciation of practical issues associated with the implementation of optimisation methods.
  • Provide experience in applying such methods on challenging problems and in assessing and comparing the performance of different algorithms.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Understand the basic mathematics underlying linear and convex optimisation.
  • Be able to write and benchmark simple algorithms to solve a convex optimisation problem.
  • Understand the technique of Markov-Chain Monte Carlo simulation, and apply it to solve a Travelling Salesman Problem.
  • Understand the ways in which different heuristic and stochastic optimization methods work and the circumstances in which they are likely to perform well or badly.
  • Understand the principles of multiobjective optimization and the benefits of such of approaching real-world optimization problems from a multiobjective perspective.

Content

  • Introduction (what is Practical Optimisation ?)
  • Approximately solving Ax=b (various methods of norm minimization of residuals that lead to LP or convex problems)
  • Geometry of polyhedral and convex sets (review of the simplex method; introduction to algorithmic complexity)
  • Duality theory and its applications
  • Unconstrained optimisation
  • Important convex relaxations in cardinality problems 
  • Simulated Annealing: basic concepts, solution representation and generation, the annealing schedule, enhancements and modifications
  • Genetic Algorithms: basic concepts, solution representation, selection, crossover, mutation
  • Tabu Search: basic concepts, solution representation, local search, intensification, diversification
  • Multiobjective Optimization: archiving, multiobjective simulated annealing, multiobjective genetic algorithms
  • Case Study: multiobjective optimization of pressurised water reactor reload cores

Coursework

Coursework

Format

Due date

& marks

Coursework activity #1: Investigation of a moderate size Linear Regression problem with various norm and regularization approximations

Learning objective: 

  • convert a regression problem into a linear program and solve it with linprog
  • program a simple line search algorithm and experiment the impact of smoothness on convergence rate.
  • understand how different norms affect the solution of an approximation problem.

Individual report

anonymously marked

Deadline: 11th December 2020

[30/60]

Coursework activity #2: Investigation of the performance of two stochastic optimization methods on a hard problem

Learning objective: 

  • gain experience in applying stochastic optimization methods to challenging problems
  • explore and analyse the variation in optimizer performance as algorithm control parameters are modified
  • compare and analyse the performance of different optimization methods on challenging problems

Individual report

anonymously marked



Deadline: 19th January 2021

[30/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 05/10/2020 12:32

Engineering Tripos Part IIB, 4M17: Practical Optimisation, 2019-20

Module Leader

Prof RJCPM Sepulchre

Lecturers

Prof RJCPM Sepulchre and Dr G Parks

Timing and Structure

Michaelmas term. 12 lectures + 4 computer lab sessions. Assessment: 100% coursework

Prerequisites

3M1

Aims

The aims of the course are to:

  • Teach some of the basic optimisation methods used to tackle difficult, real-world optimisation problems.
  • Teach means of assessing the tractability of nonlinear optimisation problems.
  • Develop an appreciation of practical issues associated with the implementation of optimisation methods.
  • Provide experience in applying such methods on challenging problems and in assessing and comparing the performance of different algorithms.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Understand the basic mathematics underlying linear and convex optimisation.
  • Be able to write and benchmark simple algorithms to solve a convex optimisation problem.
  • Understand the technique of Markov-Chain Monte Carlo simulation, and apply it to solve a Travelling Salesman Problem.
  • Understand the ways in which different heuristic and stochastic optimization methods work and the circumstances in which they are likely to perform well or badly.
  • Understand the principles of multiobjective optimization and the benefits of such of approaching real-world optimization problems from a multiobjective perspective.

Content

  • Introduction (what is Practical Optimisation ?)
  • Approximately solving Ax=b (various methods of norm minimization of residuals that lead to LP or convex problems)
  • Geometry of polyhedral and convex sets (review of the simplex method; introduction to algorithmic complexity)
  • Duality theory and its applications
  • Unconstrained optimisation
  • Important convex relaxations in cardinality problems 
  • Simulated Annealing: basic concepts, solution representation and generation, the annealing schedule, enhancements and modifications
  • Genetic Algorithms: basic concepts, solution representation, selection, crossover, mutation
  • Tabu Search: basic concepts, solution representation, local search, intensification, diversification
  • Multiobjective Optimization: archiving, multiobjective simulated annealing, multiobjective genetic algorithms
  • Case Study: multiobjective optimization of pressurised water reactor reload cores

Coursework

Coursework

Format

Due date

& marks

Coursework activity #1: Investigation of a moderate size Linear Regression problem with various norm and regularization approximations

Learning objective: 

  • convert a regression problem into a linear program and solve it with linprog
  • program a simple line search algorithm and experiment the impact of smoothness on convergence rate.
  • understand how different norms affect the solution of an approximation problem.

Individual report

anonymously marked

Deadline: 13th December 2019

[30/60]

Coursework activity #2: Investigation of the performance of two stochastic optimization methods on a hard problem

Learning objective: 

  • gain experience in applying stochastic optimization methods to challenging problems
  • explore and analyse the variation in optimizer performance as algorithm control parameters are modified
  • compare and analyse the performance of different optimization methods on challenging problems

Individual report

anonymously marked



Deadline: 17th January 2020

[30/60]

 

Booklists

Please see the Booklist for Group M Courses for references for this module.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 16/10/2019 08:44

Engineering Tripos Part IIB, 4M17: Practical Optimisation, 2018-19

Module Leader

Dr G Vinnicombe

Lecturers

Dr G Vinnicombe and Dr G Parks

Timing and Structure

Michaelmas term. 12 lectures + 4 computer lab sessions. Assessment: 100% coursework

Prerequisites

3M1

Aims

The aims of the course are to:

  • Teach some of the basic optimisation methods used to tackle difficult, real-world optimisation problems.
  • Teach means of assessing the tractability of nonlinear optimisation problems.
  • Develop an appreciation of practical issues associated with the implementation of optimisation methods.
  • Provide experience in applying such methods on challenging problems and in assessing and comparing the performance of different algorithms.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Understand the basic mathematics underlying linear and convex optimisation.
  • Be able to write and benchmark simple algorithms to solve a convex optimisation problem.
  • Understand the technique of Markov-Chain Monte Carlo simulation, and apply it to solve a Travelling Salesman Problem.
  • Understand the ways in which different heuristic and stochastic optimization methods work and the circumstances in which they are likely to perform well or badly.
  • Understand the principles of multiobjective optimization and the benefits of such of approaching real-world optimization problems from a multiobjective perspective.

Content

  • Introduction (what is Practical Optimisation ?)
  • Approximately solving Ax=b (various methods of norm minimization of residuals that lead to LP or convex problems)
  • Geometry of polyhedral and convex sets (review of the simplex method; introduction to algorithmic complexity)
  • Duality theory and its applications
  • Unconstrained optimisation
  • Important convex relaxations in cardinality problems 
  • Simulated Annealing: basic concepts, solution representation and generation, the annealing schedule, enhancements and modifications
  • Genetic Algorithms: basic concepts, solution representation, selection, crossover, mutation
  • Tabu Search: basic concepts, solution representation, local search, intensification, diversification
  • Multiobjective Optimization: archiving, multiobjective simulated annealing, multiobjective genetic algorithms
  • Case Study: multiobjective optimization of pressurised water reactor reload cores

Coursework

Coursework activity #1:  Investigation of a moderate size Linear Regression problem with various norm and regularization approximations

[30/60]


Learning objectives:

  1. • convert a regression problem into a linear program and solve it with linprog
  2. • program a simple line search algorithm and experiment the impact of smoothness on convergence rate.
  3. • understand how different norms affect the solution of an approximation problem.

Individual Report, anonymously marked


Deadline: 8th December 2017

Coursework activity #2: Investigation of the performance of two stochastic optimization methods on a hard problem

[30/60]

Learning objectives:

  1. gain experience in applying stochastic optimization methods to challenging problems
  2. explore and analyse the variation in optimizer performance as algorithm control parameters are modified
  3. compare and analyse the performance of different optimization methods on challenging problems

Individual Report, anonymously marked



Deadline: 16th January 2018



Booklists

Please see the Booklist for Group M Courses for references for this module.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 17/05/2018 15:00

Engineering Tripos Part IIB, 4M16: Nuclear Power Engineering (shared with IIA), 2025-26

Module Leader

Dr Paul Cosgrove

Lecturers

Dr Paul Cosgrove and Mr Bob Skelton

Timing and Structure

Lent Term. 12 lectures + 2 examples classes + 2 in-lecture demonstrations. Assessment: 100% exam. Lectures will be recorded.

Aims

The aims of the course are to:

  • give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry

Objectives

As specific objectives, by the end of the course students should be able to:

  • appreciate the nature of neutron-nucleus interactions
  • classify ionising radiation by physical nature and health hazard
  • conduct safely a simple experiment involving radiation
  • understand the principles of radiation detection and shielding
  • understand the principles of operation of UK nuclear reactors
  • apply elementary models of neutron behaviour in reactors
  • compute simple power distributions in reactors
  • compute simple temperature distributions in reactors and appreciate their consequences
  • appreciate the significance of delayed neutrons and xenon-135 to the control and operation of reactors
  • appreciate the advantages and disadvantages of on-load and off-load refuelling
  • perform simple calculations to predict the refuelling requirements of reactors
  • explain the operation of enrichment plant
  • appreciate the problems of radioactive waste management
  • appreciate the range of activities of the UK nuclear industry

Content

This module aims to give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry, particularly the technology used in the production of electricity in nuclear power stations, the preparation and subsequent treatment of the fuel and its by-products, and the detection of ionising radiation and the protection of workers within the nuclear industry and the general public from it.

Basic Principles and Health Physics (2L, Dr P.M. Cosgrove)

  • Principles of nuclear reactions;
  • Radioactivity and the effects of ionising radiation;
  • Introduction to health physics and shielding.

Reactor Physics (3L, Dr P.M. Cosgrove)

  • The fission chain process;
  • Interactions of neutrons with matter;
  • Models for neutron distributions in space and energy.

Reactor Design & Operation (4L, Dr P.M. Cosgrove)

  • Simple reactor design;
  • Heat transfer and temperature distributions in commercial reactors;
  • Time-dependent aspects of reactor operations; delayed neutrons and xenon poisoning;
  • In-core and out-of-core fuel cycles.

Fuel Processing (3L, Mr R.L. Skelton)

  • Enrichment and reprocessing;
  • The treatment, containment and disposal of radioactive wastes.

Demonstrations (2L, Dr P.M.Cosgrove)

Demonstration of the use of Geiger-Muller and scintillation counters for detecting ionising radiation (1 hour in-lecture time).

Demonstration of the detection and shielding of fast and thermal neutrons using a 37 GBq Americium-Beryllium source (1 hour in-lecture time).

Booklists

Please refer to the Booklist for references to this module. This can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 04/06/2025 13:33

Engineering Tripos Part IIB, 4M16: Nuclear Power Engineering (shared with IIA), 2024-25

Module Leader

Dr Paul Cosgrove

Lecturers

Dr Paul Cosgrove, Prof. Eugene Shwageraus and Mr Bob Skelton

Timing and Structure

Lent Term. 12 lectures + 2 examples classes + 2 in-lecture demonstrations. Assessment: 100% exam. Lectures will be recorded.

Aims

The aims of the course are to:

  • give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry

Objectives

As specific objectives, by the end of the course students should be able to:

  • appreciate the nature of neutron-nucleus interactions
  • classify ionising radiation by physical nature and health hazard
  • conduct safely a simple experiment involving radiation
  • understand the principles of radiation detection and shielding
  • understand the principles of operation of UK nuclear reactors
  • apply elementary models of neutron behaviour in reactors
  • compute simple power distributions in reactors
  • compute simple temperature distributions in reactors and appreciate their consequences
  • appreciate the significance of delayed neutrons and xenon-135 to the control and operation of reactors
  • appreciate the advantages and disadvantages of on-load and off-load refuelling
  • perform simple calculations to predict the refuelling requirements of reactors
  • explain the operation of enrichment plant
  • appreciate the problems of radioactive waste management
  • appreciate the range of activities of the UK nuclear industry

Content

This module aims to give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry, particularly the technology used in the production of electricity in nuclear power stations, the preparation and subsequent treatment of the fuel and its by-products, and the detection of ionising radiation and the protection of workers within the nuclear industry and the general public from it.

Basic Principles and Health Physics (2L, Prof. E. Shwageraus)

  • Principles of nuclear reactions;
  • Radioactivity and the effects of ionising radiation;
  • Introduction to health physics and shielding.

Reactor Physics (3L, Dr P.M. Cosgrove)

  • The fission chain process;
  • Interactions of neutrons with matter;
  • Models for neutron distributions in space and energy.

Reactor Design & Operation (4L, Dr P.M. Cosgrove)

  • Simple reactor design;
  • Heat transfer and temperature distributions in commercial reactors;
  • Time-dependent aspects of reactor operations; delayed neutrons and xenon poisoning;
  • In-core and out-of-core fuel cycles.

Fuel Processing (3L, Mr R.L. Skelton)

  • Enrichment and reprocessing;
  • The treatment, containment and disposal of radioactive wastes.

Demonstrations (2L, Dr P.M.Cosgrove)

Demonstration of the use of Geiger-Muller and scintillation counters for detecting ionising radiation (1 hour in-lecture time).

Demonstration of the detection and shielding of fast and thermal neutrons using a 37 GBq Americium-Beryllium source (1 hour in-lecture time).

Booklists

Please refer to the Booklist for references to this module. This can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 01/10/2024 10:39

Engineering Tripos Part IIB, 4M16: Nuclear Power Engineering (shared with IIA), 2023-24

Module Leader

Prof. Geoff Parks

Lecturers

Prof. Geoff Parks, Prof. Eugene Shwageraus and Mr Bob Skelton

Timing and Structure

Lent Term. 12 lectures + 2 examples classes + 2 in-lecture demonstrations. Assessment: 100% exam. Lectures will be recorded.

Aims

The aims of the course are to:

  • give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry

Objectives

As specific objectives, by the end of the course students should be able to:

  • appreciate the nature of neutron-nucleus interactions
  • classify ionising radiation by physical nature and health hazard
  • conduct safely a simple experiment involving radiation
  • understand the principles of radiation detection and shielding
  • understand the principles of operation of UK nuclear reactors
  • apply elementary models of neutron behaviour in reactors
  • compute simple power distributions in reactors
  • compute simple temperature distributions in reactors and appreciate their consequences
  • appreciate the significance of delayed neutrons and xenon-135 to the control and operation of reactors
  • appreciate the advantages and disadvantages of on-load and off-load refuelling
  • perform simple calculations to predict the refuelling requirements of reactors
  • explain the operation of enrichment plant
  • appreciate the problems of radioactive waste management
  • appreciate the range of activities of the UK nuclear industry

Content

This module aims to give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry, particularly the technology used in the production of electricity in nuclear power stations, the preparation and subsequent treatment of the fuel and its by-products, and the detection of ionising radiation and the protection of workers within the nuclear industry and the general public from it.

Basic Principles and Health Physics (2L, Prof. E. Shwageraus)

  • Principles of nuclear reactions;
  • Radioactivity and the effects of ionising radiation;
  • Introduction to health physics and shielding.

Reactor Physics (3L, Prof. G.T. Parks)

  • The fission chain process;
  • Interactions of neutrons with matter;
  • Models for neutron distributions in space and energy.

Reactor Design & Operation (4L, Prof. G.T. Parks)

  • Simple reactor design;
  • Heat transfer and temperature distributions in commercial reactors;
  • Time-dependent aspects of reactor operations; delayed neutrons and xenon poisoning;
  • In-core and out-of-core fuel cycles.

Fuel Processing (3L, Mr R.L. Skelton)

  • Enrichment and reprocessing;
  • The treatment, containment and disposal of radioactive wastes.

Demonstrations (2L, Prof. G.T. Parks)

Demonstration of the use of Geiger-Muller and scintillation counters for detecting ionising radiation (1 hour in-lecture time).

Demonstration of the detection and shielding of fast and thermal neutrons using a 37 GBq Americium-Beryllium source (1 hour in-lecture time).

Booklists

Please refer to the Booklist for references to this module. This can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

S1

The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.

S4

Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

 
Last modified: 30/05/2023 15:35

Engineering Tripos Part IIB, 4M16: Nuclear Power Engineering (shared with IIA), 2022-23

Module Leader

Prof. Geoff Parks

Lecturers

Prof. Geoff Parks, Prof. Eugene Shwageraus and Mr Bob Skelton

Timing and Structure

Lent Term. 12 lectures + 2 examples classes + 2 in-lecture demonstrations. Assessment: 100% exam. Lectures will be recorded.

Aims

The aims of the course are to:

  • give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry

Objectives

As specific objectives, by the end of the course students should be able to:

  • appreciate the nature of neutron-nucleus interactions
  • classify ionising radiation by physical nature and health hazard
  • conduct safely a simple experiment involving radiation
  • understand the principles of radiation detection and shielding
  • understand the principles of operation of UK nuclear reactors
  • apply elementary models of neutron behaviour in reactors
  • compute simple power distributions in reactors
  • compute simple temperature distributions in reactors and appreciate their consequences
  • appreciate the significance of delayed neutrons and xenon-135 to the control and operation of reactors
  • appreciate the advantages and disadvantages of on-load and off-load refuelling
  • perform simple calculations to predict the refuelling requirements of reactors
  • explain the operation of enrichment plant
  • appreciate the problems of radioactive waste management
  • appreciate the range of activities of the UK nuclear industry

Content

This module aims to give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry, particularly the technology used in the production of electricity in nuclear power stations, the preparation and subsequent treatment of the fuel and its by-products, and the detection of ionising radiation and the protection of workers within the nuclear industry and the general public from it.

Basic Principles and Health Physics (2L, Prof. E. Shwageraus)

  • Principles of nuclear reactions;
  • Radioactivity and the effects of ionising radiation;
  • Introduction to health physics and shielding.

Reactor Physics (3L, Prof. G.T. Parks)

  • The fission chain process;
  • Interactions of neutrons with matter;
  • Models for neutron distributions in space and energy.

Reactor Design & Operation (4L, Prof. G.T. Parks)

  • Simple reactor design;
  • Heat transfer and temperature distributions in commercial reactors;
  • Time-dependent aspects of reactor operations; delayed neutrons and xenon poisoning;
  • In-core and out-of-core fuel cycles.

Fuel Processing (3L, Mr R.L. Skelton)

  • Enrichment and reprocessing;
  • The treatment, containment and disposal of radioactive wastes.

Demonstrations (2L, Prof. G.T. Parks)

Demonstration of the use of Geiger-Muller and scintillation counters for detecting ionising radiation (1 hour in-lecture time).

Demonstration of the detection and shielding of fast and thermal neutrons using a 37 GBq Americium-Beryllium source (1 hour in-lecture time).

Booklists

Please refer to the Booklist for references to this module. This can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

S1

The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.

S4

Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

 
Last modified: 21/07/2022 12:17

Engineering Tripos Part IIB, 4M16: Nuclear Power Engineering (shared with IIA), 2021-22

Module Leader

Dr G T Parks

Lecturers

Dr G T Parks, Dr E Shwageraus and Mr R L Skelton

Timing and Structure

Lent Term. 12 lectures + 2 examples classes + 2 in-lecture demonstrations. Assessment: 100% exam

Aims

The aims of the course are to:

  • give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry

Objectives

As specific objectives, by the end of the course students should be able to:

  • appreciate the nature of neutron-nucleus interactions
  • classify ionising radiation by physical nature and health hazard
  • conduct safely a simple experiment involving radiation
  • understand the principles of radiation detection and shielding
  • understand the principles of operation of UK nuclear reactors
  • apply elementary models of neutron behaviour in reactors
  • compute simple power distributions in reactors
  • compute simple temperature distributions in reactors and appreciate their consequences
  • appreciate the significance of delayed neutrons and xenon-135 to the control and operation of reactors
  • appreciate the advantages and disadvantages of on-load and off-load refuelling
  • perform simple calculations to predict the refuelling requirements of reactors
  • explain the operation of enrichment plant
  • appreciate the problems of radioactive waste management
  • appreciate the range of activities of the UK nuclear industry

Content

This module aims to give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry, particularly the technology used in the production of electricity in nuclear power stations, the preparation and subsequent treatment of the fuel and its by-products, and the detection of ionising radiation and the protection of workers within the nuclear industry and the general public from it.

Basic Principles and Health Physics (2L, Dr E Shwageraus)

  • Principles of nuclear reactions;
  • Radioactivity and the effects of ionising radiation;
  • Introduction to health physics and shielding.

Reactor Physics (3L, Dr G T Parks)

  • The fission chain process;
  • Interactions of neutrons with matter;
  • Models for neutron distributions in space and energy.

Reactor Design & Operation (4L, Dr G T Parks)

  • Simple reactor design;
  • Heat transfer and temperature distributions in commercial reactors;
  • Time-dependent aspects of reactor operations; delayed neutrons and xenon poisoning;
  • In-core and out-of-core fuel cycles.

Fuel Processing (3L, Mr R L Skelton)

  • Enrichment and reprocessing;
  • The treatment, containment and disposal of radioactive wastes.

Demonstrations (2L, Dr G T Parks)

Demonstration of the use of Geiger-Muller and scintillation counters for detecting ionising radiation (1 hour in-lecture time).

Demonstration of the detection and shielding of fast and thermal neutrons using a 37 GBq Americium-Beryllium source (1 hour in-lecture time).

Booklists

Please refer to the Booklist for references to this module. This can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

S1

The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.

S4

Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

 
Last modified: 23/08/2021 16:57

Engineering Tripos Part IIB, 4M16: Nuclear Power Engineering (shared with IIA), 2020-21

Module Leader

Dr G T Parks

Lecturers

Dr G T Parks and Mr R L Skelton

Timing and Structure

Lent Term. 12 lectures + 2 examples classes + 2 in-lecture demonstrations. Assessment: 100% exam

Aims

The aims of the course are to:

  • give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry

Objectives

As specific objectives, by the end of the course students should be able to:

  • appreciate the nature of neutron-nucleus interactions
  • classify ionising radiation by physical nature and health hazard
  • conduct safely a simple experiment involving radiation
  • understand the principles of radiation detection and shielding
  • understand the principles of operation of UK nuclear reactors
  • apply elementary models of neutron behaviour in reactors
  • compute simple power distributions in reactors
  • compute simple temperature distributions in reactors and appreciate their consequences
  • appreciate the significance of delayed neutrons and xenon-135 to the control and operation of reactors
  • appreciate the advantages and disadvantages of on-load and off-load refuelling
  • perform simple calculations to predict the refuelling requirements of reactors
  • explain the operation of enrichment plant
  • appreciate the problems of radioactive waste management
  • appreciate the range of activities of the UK nuclear industry

Content

This module aims to give the student an introduction to and appreciation of nuclear power engineering and the UK nuclear industry, particularly the technology used in the production of electricity in nuclear power stations, the preparation and subsequent treatment of the fuel and its by-products, and the detection of ionising radiation and the protection of workers within the nuclear industry and the general public from it.

Basic Principles and Health Physics (2L, Dr G T Parks)

  • Principles of nuclear reactions;
  • Radioactivity and the effects of ionising radiation;
  • Introduction to health physics and shielding.

Reactor Physics (3L, Dr G T Parks)

  • The fission chain process;
  • Interactions of neutrons with matter;
  • Models for neutron distributions in space and energy.

Reactor Design & Operation (4L, Dr G T Parks)

  • Simple reactor design;
  • Heat transfer and temperature distributions in commercial reactors;
  • Time dependent aspects of reactor operations; delayed neutrons and xenon poisoning;
  • In-core and out-of-core fuel cycles.

Fuel Processing (3L, Mr R L Skelton)

  • Enrichment and reprocessing;
  • The containment and disposal of radioactive wastes.

Demonstrations (2L, Dr G T Parks)

Demonstration of the use of Geiger-Muller and scintillation counters for detecting ionising radiation (1 hour in-lecture time).

Demonstration of the detection and shielding of fast and thermal neutrons using a 37 GBq Americium-Beryllium source (1 hour in-lecture time).

Booklists

Please refer to the Booklist for references to this module. This can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

S1

The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.

S4

Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

 
Last modified: 11/09/2020 17:17

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