Engineering Tripos Part IIA, 3E3: Modelling Risk, 2018-19
Leader
Tutor
Timing and Structure
Michaelmas term. 2 lectures/week. 16 lectures.
Prerequisites
Basic probability theory and statistics and basic knowledge of using Excel of Microsoft.
Aims
The aims of the course are to:
- Provide an understanding of the mechanics of a range of management science modelling methods involving randomness, such as statistics, decision analysis, portfolio management, queueing theory, Markov chains, dynamic programming, forecasting, & regression.
- For each of the modelling areas, students will become familiar with the types of situations in which the method is useful.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand basic concepts of probability and the rationale behind statistical reasoning.
- Be able to calculate statistical measures like mean and variance, and interpret these in realistic situations.
- Use confidence intervals to quantify risk.
- Conduct hypothesis testing.
- Be able to understand decision trees and how to apply them in decision making.
- Be able to describe a Markov chain and analyse its long-term behaviour and steady state distribution.
- Understand and use simple formulas for queues in which arrivals occur as a Poisson process.
- Be able to model staged decisions by dynamic programming and to solve some dynamic programs using value iteration and policy iteration algorithms.
- Forecast data using short range extrapolative techniques such as exponential smoothing.
- Know how to take account of seasonality when forecasting.
- Apply regression techniques to estimate the way in which two variables are related.
- Be able to understand investment strategies for portfolios.
- Be able to incorporate risk into investment and decision making.
Content
"There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. These are things we don't know we don't know."
- Donald Rumsfeld
Inventory Management (2L)
- Basic concepts in inventory management: inventory management under deterministic demand (EOQ model), inventory management under stochastic demand (newsvendor model, (R, Q) policy).
Decision Analysis (2L)
- Events and decisions, decision trees, expected monetary value, sensitivity analysis, expected value of perfect information, expected value of sample information.
Mathematical Analysis of Stochastic Processes (6L)
- Dynamic programming: Bellman optimality equations, deterministic dynamic programming, probabilistic dynamic programming, value iteration algorithm, policy iteration algorithm.
- Markov chains: Discrete and continuous-time Markov chains, hitting times, steady-state distributions, steady state probabilities of birth and death processes.
- Queueing theory: Poisson arrival processes, classification of queueing systems, steady state, performance measures, Little's formula, benefits and limitations of queueing theory.
Regression Analysis and Forecasting (4L)
- Simple linear regression analysis, least squares estimates, significance of regression, multiple regression, multi-collinearity.
- Different methods for forecasting: moving average, exponential smoothing, modelling seasonality and trends.
Portfolio Management (2L)
- Basic portfolio concepts: securities, risk, arbitrage.
- The Capital Asset Pricing Model.
- Risk and expected return on a portfolio, and the efficient frontier.
Examples papers
In this course, we will have three examples classes for all students at the same time, rather than three supervisions for small groups.
- Class 1: Statistics, decision analysis and dynamic programming.
- Class 2: Queuing theory and Markov chains.
- Class 3: Regression, forecasting and portfolio analysis.
Coursework
To be announced in lectures.
There is no Full Technical Report (FTR) associated with this module.
Booklists
Please see the Booklist for Part IIA Courses for references for this module.
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.
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.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
Last modified: 28/03/2019 10:15
Engineering Tripos Part IIA, 3E3: Modelling Risk, 2019-20
Leader
Lecturer
Dr F Erhun-Oguz
Timing and Structure
Lent term. 2 lectures/week. 16 lectures.
Prerequisites
Basic probability theory and statistics and basic knowledge of using Excel of Microsoft.
Aims
The aims of the course are to:
- Provide an understanding of the mechanics of a range of management science modelling methods involving randomness, such as statistics, decision analysis, portfolio management, queueing theory, Markov chains, dynamic programming, forecasting, & regression.
- For each of the modelling areas, students will become familiar with the types of situations in which the method is useful.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand basic concepts of probability and the rationale behind statistical reasoning.
- Be able to calculate statistical measures like mean and variance, and interpret these in realistic situations.
- Use confidence intervals to quantify risk.
- Conduct hypothesis testing.
- Be able to understand decision trees and how to apply them in decision making.
- Be able to describe a Markov chain and analyse its long-term behaviour and steady state distribution.
- Understand and use simple formulas for queues in which arrivals occur as a Poisson process.
- Be able to model staged decisions by dynamic programming and to solve some dynamic programs using value iteration and policy iteration algorithms.
- Forecast data using short range extrapolative techniques such as exponential smoothing.
- Know how to take account of seasonality when forecasting.
- Apply regression techniques to estimate the way in which two variables are related.
- Be able to understand investment strategies for portfolios.
- Be able to incorporate risk into investment and decision making.
Content
"There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. These are things we don't know we don't know."
- Donald Rumsfeld
Inventory Management (2L)
- Basic concepts in inventory management: inventory management under deterministic demand (EOQ model), inventory management under stochastic demand (newsvendor model, (R, Q) policy).
Decision Analysis (2L)
- Events and decisions, decision trees, expected monetary value, sensitivity analysis, expected value of perfect information, expected value of sample information.
Mathematical Analysis of Stochastic Processes (6L)
- Dynamic programming: Bellman optimality equations, deterministic dynamic programming, probabilistic dynamic programming, value iteration algorithm, policy iteration algorithm.
- Markov chains: Discrete and continuous-time Markov chains, hitting times, steady-state distributions, steady state probabilities of birth and death processes.
- Queueing theory: Poisson arrival processes, classification of queueing systems, steady state, performance measures, Little's formula, benefits and limitations of queueing theory.
Regression Analysis and Forecasting (4L)
- Simple linear regression analysis, least squares estimates, significance of regression, multiple regression, multi-collinearity.
- Different methods for forecasting: moving average, exponential smoothing, modelling seasonality and trends.
Portfolio Management (2L)
- Basic portfolio concepts: securities, risk, arbitrage.
- The Capital Asset Pricing Model.
- Risk and expected return on a portfolio, and the efficient frontier.
Examples papers
In this course, we will have three examples classes for all students at the same time, rather than three supervisions for small groups.
- Class 1: Statistics, decision analysis and dynamic programming.
- Class 2: Queuing theory and Markov chains.
- Class 3: Regression, forecasting and portfolio analysis.
Coursework
To be announced in lectures.
There is no Full Technical Report (FTR) associated with this module.
Booklists
Please see the Booklist for Part IIA Courses for references for this module.
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.
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.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
Last modified: 15/05/2019 09:26
Engineering Tripos Part IIA, 3E3: Modelling Risk, 2023-24
Leader
Lecturer
Lab Leader
Timing and Structure
Lent term. 2 lectures/week. 16 lectures.
Prerequisites
Basic probability theory and statistics and basic knowledge of using Excel of Microsoft.
Aims
The aims of the course are to:
- Provide an understanding of a range of management science modelling methods involving randomness, such as statistics, decision analysis, behavioral factors, portfolio management, process analysis, queueing theory, forecasting, and regression.
- For each of the modelling areas, students will become familiar with the types of situations in which the method is useful.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand basic concepts of probability and the rationale behind statistical reasoning.
- Be able to calculate statistical measures like mean and variance, and interpret these in realistic situations.
- Use confidence intervals to quantify risk.
- Conduct hypothesis testing.
- Be able to understand decision trees and how to apply them in decision making.
- Identify and manage the bottleneck in a serial process, calculate the throughput of the entire system and utilisation at each step.
- Understand and use simple formulas for queues in which arrivals occur as a Poisson process.
- Understand the role of behavioral biases in decision making.
- Forecast data using short range extrapolative techniques such as exponential smoothing.
- Know how to take account of seasonality when forecasting.
- Apply regression techniques to estimate the way in which two variables are related.
- Be able to understand investment strategies for portfolios.
- Be able to incorporate risk into investment and decision making.
Content
"There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. These are things we don't know we don't know."
- Donald Rumsfeld
Note: The content covered across all lectures and example papers will be as listed below. However, elements of the content may be re-sequenced to achieve a better flow.
Mathematical Analysis of Deterministic and Stochastic Processes (4L)
- Process Analysis: Identify and manage the bottleneck in a serial process, calculate the throughput of the entire system and utilisation at each step, evaluate the impact of improvements to different steps in a process.
- Queueing theory: Poisson arrival processes, classification of queueing systems, steady state, performance measures, Little's formula, benefits and limitations of queueing theory.
Regression Analysis and Forecasting (4L)
- Simple linear regression analysis, least squares estimates, significance of regression, multiple regression, multi-collinearity.
- Different methods for forecasting: moving average, exponential smoothing, modelling seasonality and trends.
Inventory Management (2L)
- Basic concepts in inventory management: inventory management under stochastic demand.
Portfolio Management (2L)
- Basic portfolio concepts
- Risk and expected return on a portfolio, and the efficient frontier.
Decision Analysis (4L)
- Events and decisions, decision trees, expected monetary value, sensitivity analysis, expected value of perfect information, expected value of sample information.
- Behavioural Factors in Decision Making
Examples papers
In this course, we will have examples classes for all students at the same time, rather than supervisions for small groups.
- Class 1: Process Analysis and Queuing theory.
- Class 2: Regression, forecasting, and inventory management.
- Class 3: Portfolio and decision analysis.
Coursework
To be announced in lectures.
There is no Full Technical Report (FTR) associated with this module.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
Last modified: 30/10/2023 14:58
Engineering Tripos Part IIA, 3E3: Modelling Risk, 2024-25
Leader
Lecturer
Lab Leader
Timing and Structure
Lent term. 2 lectures/week. 16 lectures.
Prerequisites
Basic probability theory and statistics and basic knowledge of using Excel of Microsoft.
Aims
The aims of the course are to:
- Provide an understanding of a range of management science modelling methods involving randomness, such as statistics, decision analysis, behavioral factors, portfolio management, process analysis, queueing theory, forecasting, and regression.
- For each of the modelling areas, students will become familiar with the types of situations in which the method is useful.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand basic concepts of probability and the rationale behind statistical reasoning.
- Be able to calculate statistical measures like mean and variance, and interpret these in realistic situations.
- Use confidence intervals to quantify risk.
- Conduct hypothesis testing.
- Be able to understand decision trees and how to apply them in decision making.
- Identify and manage the bottleneck in a serial process, calculate the throughput of the entire system and utilisation at each step.
- Understand and use simple formulas for queues in which arrivals occur as a Poisson process.
- Understand the role of behavioral biases in decision making.
- Forecast data using short range extrapolative techniques such as exponential smoothing.
- Know how to take account of seasonality when forecasting.
- Apply regression techniques to estimate the way in which two variables are related.
- Be able to understand investment strategies for portfolios.
- Be able to incorporate risk into investment and decision making.
Content
"There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. These are things we don't know we don't know."
- Donald Rumsfeld
Note: The content covered across all lectures and example papers will be as listed below. However, elements of the content may be re-sequenced to achieve a better flow.
Mathematical Analysis of Deterministic and Stochastic Processes (4L)
- Process Analysis: Identify and manage the bottleneck in a serial process, calculate the throughput of the entire system and utilisation at each step, evaluate the impact of improvements to different steps in a process.
- Queueing theory: Poisson arrival processes, classification of queueing systems, steady state, performance measures, Little's formula, benefits and limitations of queueing theory.
Regression Analysis and Forecasting (4L)
- Simple linear regression analysis, least squares estimates, significance of regression, multiple regression, multi-collinearity.
- Different methods for forecasting: moving average, exponential smoothing, modelling seasonality and trends.
Inventory Management (2L)
- Basic concepts in inventory management: inventory management under stochastic demand.
Portfolio Management (2L)
- Basic portfolio concepts
- Risk and expected return on a portfolio, and the efficient frontier.
Decision Analysis (4L)
- Events and decisions, decision trees, expected monetary value, sensitivity analysis, expected value of perfect information, expected value of sample information.
- Behavioural Factors in Decision Making
Examples papers
In this course, we will have examples classes for all students at the same time, rather than supervisions for small groups.
- Class 1: Process Analysis and Queuing theory.
- Class 2: Regression, forecasting, and inventory management.
- Class 3: Portfolio and decision analysis.
Coursework
To be announced in lectures.
There is no Full Technical Report (FTR) associated with this module.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
Last modified: 29/01/2025 11:35
Engineering Tripos Part IIA, 3E3: Modelling Risk, 2025-26
Leader
Lecturer
Lab Leader
Timing and Structure
Lent term. 2 lectures/week. 16 lectures.
Prerequisites
Basic probability theory and statistics and basic knowledge of using Excel of Microsoft.
Aims
The aims of the course are to:
- Provide an understanding of a range of management science modelling methods involving randomness, such as statistics, decision analysis, behavioral factors, portfolio management, process analysis, queueing theory, forecasting, and regression.
- For each of the modelling areas, students will become familiar with the types of situations in which the method is useful.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand basic concepts of probability and the rationale behind statistical reasoning.
- Be able to calculate statistical measures like mean and variance, and interpret these in realistic situations.
- Use confidence intervals to quantify risk.
- Conduct hypothesis testing.
- Be able to understand decision trees and how to apply them in decision making.
- Identify and manage the bottleneck in a serial process, calculate the throughput of the entire system and utilisation at each step.
- Understand and use simple formulas for queues in which arrivals occur as a Poisson process.
- Understand the role of behavioral biases in decision making.
- Forecast data using short range extrapolative techniques such as exponential smoothing.
- Know how to take account of seasonality when forecasting.
- Apply regression techniques to estimate the way in which two variables are related.
- Be able to understand investment strategies for portfolios.
- Be able to incorporate risk into investment and decision making.
Content
"There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. These are things we don't know we don't know."
- Donald Rumsfeld
Note: The content covered across all lectures and example papers will be as listed below. However, elements of the content may be re-sequenced to achieve a better flow.
Mathematical Analysis of Deterministic and Stochastic Processes (4L)
- Process Analysis: Identify and manage the bottleneck in a serial process, calculate the throughput of the entire system and utilisation at each step, evaluate the impact of improvements to different steps in a process.
- Queueing theory: Poisson arrival processes, classification of queueing systems, steady state, performance measures, Little's formula, benefits and limitations of queueing theory.
Regression Analysis and Forecasting (4L)
- Simple linear regression analysis, least squares estimates, significance of regression, multiple regression, multi-collinearity.
- Different methods for forecasting: moving average, exponential smoothing, modelling seasonality and trends.
Inventory Management (2L)
- Basic concepts in inventory management: inventory management under stochastic demand.
Portfolio Management (2L)
- Basic portfolio concepts
- Risk and expected return on a portfolio, and the efficient frontier.
Decision Analysis (4L)
- Events and decisions, decision trees, expected monetary value, sensitivity analysis, expected value of perfect information, expected value of sample information.
- Behavioural Factors in Decision Making
Examples papers
In this course, we will have examples classes for all students at the same time, rather than supervisions for small groups.
- Class 1: Process Analysis and Queuing theory.
- Class 2: Regression, forecasting, and inventory management.
- Class 3: Portfolio and decision analysis.
Coursework
To be announced in lectures.
There is no Full Technical Report (FTR) associated with this module.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
Last modified: 04/06/2025 13:19
Engineering Tripos Part IIA, 3D8: Geo-Environmental Engineering, 2021-22
Module Leader
Lecturers
Prof S P G Madhabhushi and Prof A Al-Tabbaa
Lab Leader
Timing and Structure
Lent term. 16 lectures and Lab.
Aims
The aims of the course are to:
- The aim of the course is to introduce the transport processes of fluids, water and pollutants, in the porous media that constitute the geo-environment.
- The module aims to address the factors that influence groundwater, heat and pollutant transport, practical and design applications and problems that might arise.
- This course aims to introduce the students to the flow regimes that occur in porous media and ways to estimate the flow quantities using flownets.
- Similarly heat flow through porous media is introduced drawing parallels with the groundwater flow.
- Contaminant transport through porous media is another important aspect in geo-environmental engineering that is addressed in this module.
- Practical ways to dispose waste into the ground, the effects the contaminants have on the host soil and necessary aspects of remediation of contaminated land will also considered.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand the geotechnical environment.
- Determine flow patterns in steady state groundwater seepage.
- Evaluate potentials, pore water pressures, and flow quantities in the ground by constructing flow nets.
- Anisotropic soils and flow nets
- Seepage below concrete dams
- Seepage through embankment & earth dams
- Excavations and seepage, Cofferdams and stability
- Draw parallels between groundwater flow and heat flow in porous media
- Develop necessary skills to estimate heat storage and extraction from ground
- Introduction to contaminated soil and its remediation
- Understand the soil properties that affect the geo-environment and vice versa
- Develop an understanding of the interactions between soils and contaminants
- Understand the effect of soil contamination on geotechnical properties
- Develop an understanding of the fate and transport mechanisms of contaminants in the ground
- Solving of Advection-Dispersion equation using error functions
- Develop appreciation of the contaminated land/landfills environment
- Understand disposal of waste into well-engineered systems
- Be able to design a solution relevant to land remediation or a landfill
Content
The following topics will be covered:
Flow of Water through Porous Media, is an important aspect in the design of many civil engineering structures such as retaining walls, caissons, excavation for foundations, etc. As it will be shown in the second part of the module, the same physical principles and mathematical concepts can be used to understand flow of heat in porous media, for example, in the design of energy piles or ground source heat pumps.
Contaminant Transport through Porous Media, is important to understand the presence of contaminants in the ground and how they are transported through various mechanisms and how they affect the properties of the soil. Equally disposal of waste of waste safely into well-engineered facilities is critical to minimise the environmental impact of the waste.
Groundwater, Seepage and Heat Flow in Granular media (8L)
- Introduction
- Concept of porous media and bulk properties.
- Definitions of potential head, pressure head and pore pressure.
- Groundwater flow and seepage
- Theory of flownets
- Anisotropic soils and flownets
- Darcy's law and Hydraulic conductivity
- Laboratory and in situ measurements
- Seepage below concrete dams
- Seepage through embankments and earth dams
- Stability and seepage around excavations
- Coffer dams and their stability
- Fourier’s law and heat flow in porous media
- Parallels between ground water flow and heat flow
- Ground source heat pumps
- Storage and extraction of heat from ground
Contaminated Land and transport of contaminants through ground (8L)
- Introduction to contaminated land and contaminants in the geo-environment
- Introduction to waste containment structures – landfills
- The structure of clays
- The clay-water interactions
- The clay-water-contaminant interactions
- The effect of contaminants on the geotechnical properties of soils
- Mechanisms of contaminant transport
- Fick’s law for diffusion in porous media, dispersion and sorption, Peclet’s number
- Solving advection-dispersion equation, Error functions
- Land remediation and waste containment design applications
- Relevant case studies and project examples.
Coursework
Environmental Geotechnical Engineering
Learning objectives:
- Axi-Symmetric flow of ground water into a well boring
- Axi-Symmetric heat flow in saturated soil
Practical information:
- Sessions will take place in [ISG-88], during week(s) [2-6].
- This activity [doesn't involve] preliminary work but read the lab handout prior to the lab session ([1 hr]).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
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.
E4
Understanding of and ability to apply a systems approach to engineering problems.
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.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 27/07/2021 16:23
Engineering Tripos Part IIA, 3D8: Building Physics & Environmental Geotechnics, 2017-18
Module Leader
Lecturers
Dr S Fitzgerald, Prof A Al-Tabbaa
Lab Leader
Dr R Choudhary
Timing and Structure
Lent term. 16 lectures and Lab.
Aims
The aims of the course are to:
- Introduce the physics behind heat, liquid, and mass (air and moisture) transfer in materials,buildings, and energy systems and their interactions with outside environment, both air and ground.
- Provide the foundational knowledge for understanding environmental characterstics of the built environment, with a focus on aspects important for structural durability and energy efficiency.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand the geotechnical environment.
- Determine flow patterns in steady state groundwater seepage.
- Evaluate potentials, pore water pressures, and flow quantities in the ground by constructing flow nets.
- Analyze environmental behaviour of building components, such as heat flow rates, temperature variations (seasonal and diurnal).
- Calculate steady state energy balance for a building to determine hearing, cooling and ventilation demand from auxillary systems.
- Understand how choice of design and components influences the indoor environment and energy consumption of building.
Content
The following topics will be covered:
Flow of Water through Porous Media, which is an important aspect in the design of many civil engineering structures such as retaining walls, caissons, excavation for foundations, etc. As it will be shown in the second part of the module, the same physical principles and mathematical concepts can be used to understand flow of heat in porous media, for example, in the design of energy piles or ground source heat pumps.
Heat, air and moisture transfer across building elements: composite roofs and walls, surface-to-air, air gaps, ventilated spaces, transparent envelopes, and heat exchange between surfaces in a room; Heat exchange with ground will be covered for slab-on-grade, sub-surface structures, and ground-source heat exchangers.
The topics cover theoretical aspects of important energy flows through most common building elements, from foundations to the building envelope. This knowledge is also pre-requiste for learning simulation and modelling techniques for energy balance and environmental control systems of buildings.
Groundwater and Seepage (8L)
- Introduction
- Concept of porous media and bulk properties.
- Definitions of potential head, pressure head and pore pressure.
- Groundwater flow and seepage
- Theory of flownets.
- Darcy's law and Hydraulic conductivity
- Laboratory and in-stu measurements
Heat, Air and Moisture Transfer through Building Elements (8L)
- Conservation of energy, Fourier's laws, concept of steady state, periodic and transient.
- Conduction: 1D heat flow through single and multi -layered structures, response to temperature variations, contact temperature between layers, network analysis.
- Heat exchange with ground: examples of 2D and 3D heat flow between ground and building elements - pipes, slabs, sub-surfaces.
- Radiation: reflectance, absorption and transmission; radiant surfaces and block bodies; heat gains from solar (short wave) radiation, long wave radiation exchange between 2 isothermal surfaces in enclosures.
- Ventilation: Driving forces (wind, stack, mechanical), air exchange rates.
- Infliteration: air through permeable materials, gaps, ventilated cavities, heat losses due to transmission and ventilation.
- Moisture: Water vapour in air and relative humidity, characteristics of moist air, mold and surface condensation, moisture balance of building components and ventilated spaces.
- combined Heat and Mass Transfer: exercised from practical scenarios.
Coursework
Building Physics and Environment Geotechnics
Learning objectives:
Practical information:
- Sessions will take place in [Location], during week(s) [xxx].
- This activity [involves/doesn't involve] preliminary work ([estimated duration]).
Full Technical Report:
Students [will/won't] have the option to submit a Full Technical Report.
Booklists
Please see the Booklist for Part IIA Courses for references for this module.
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.
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
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.
E4
Understanding of and ability to apply a systems approach to engineering problems.
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.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 03/08/2017 15:35
Engineering Tripos Part IIA, 3D8: Geo-Environmental Engineering, 2022-23
Module Leader
Lecturers
Prof S P G Madhabhushi and Prof A Al-Tabbaa
Lab Leader
Timing and Structure
Lent term. 16 lectures and Lab.
Aims
The aims of the course are to:
- The aim of the course is to introduce the transport processes of fluids, water and pollutants, in the porous media that constitute the geo-environment.
- The module aims to address the factors that influence groundwater, heat and pollutant transport, practical and design applications and problems that might arise.
- This course aims to introduce the students to the flow regimes that occur in porous media and ways to estimate the flow quantities using flownets.
- Similarly heat flow through porous media is introduced drawing parallels with the groundwater flow.
- Contaminant transport through porous media is another important aspect in geo-environmental engineering that is addressed in this module.
- Practical ways to dispose waste into the ground, the effects the contaminants have on the host soil and necessary aspects of remediation of contaminated land will also considered.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand the geotechnical environment.
- Determine flow patterns in steady state groundwater seepage.
- Evaluate potentials, pore water pressures, and flow quantities in the ground by constructing flow nets.
- Anisotropic soils and flow nets
- Seepage below concrete dams
- Seepage through embankment & earth dams
- Excavations and seepage, Cofferdams and stability
- Draw parallels between groundwater flow and heat flow in porous media
- Develop necessary skills to estimate heat storage and extraction from ground
- Introduction to contaminated soil and its remediation
- Understand the soil properties that affect the geo-environment and vice versa
- Develop an understanding of the interactions between soils and contaminants
- Understand the effect of soil contamination on geotechnical properties
- Develop an understanding of the fate and transport mechanisms of contaminants in the ground
- Solving of Advection-Dispersion equation using error functions
- Develop appreciation of the contaminated land/landfills environment
- Understand disposal of waste into well-engineered systems
- Be able to design a solution relevant to land remediation or a landfill
Content
The following topics will be covered:
Flow of Water through Porous Media, is an important aspect in the design of many civil engineering structures such as retaining walls, caissons, excavation for foundations, etc. As it will be shown in the second part of the module, the same physical principles and mathematical concepts can be used to understand flow of heat in porous media, for example, in the design of energy piles or ground source heat pumps.
Contaminant Transport through Porous Media, is important to understand the presence of contaminants in the ground and how they are transported through various mechanisms and how they affect the properties of the soil. Equally disposal of waste of waste safely into well-engineered facilities is critical to minimise the environmental impact of the waste.
Groundwater, Seepage and Heat Flow in Granular media (8L)
- Introduction
- Concept of porous media and bulk properties.
- Definitions of potential head, pressure head and pore pressure.
- Groundwater flow and seepage
- Theory of flownets
- Anisotropic soils and flownets
- Darcy's law and Hydraulic conductivity
- Laboratory and in situ measurements
- Seepage below concrete dams
- Seepage through embankments and earth dams
- Stability and seepage around excavations
- Coffer dams and their stability
- Fourier’s law and heat flow in porous media
- Parallels between ground water flow and heat flow
- Ground source heat pumps
- Storage and extraction of heat from ground
Contaminated Land and transport of contaminants through ground (8L)
- Introduction to contaminated land and contaminants in the geo-environment
- Introduction to waste containment structures – landfills
- The structure of clays
- The clay-water interactions
- The clay-water-contaminant interactions
- The effect of contaminants on the geotechnical properties of soils
- Mechanisms of contaminant transport
- Fick’s law for diffusion in porous media, dispersion and sorption, Peclet’s number
- Solving advection-dispersion equation, Error functions
- Land remediation and waste containment design applications
- Relevant case studies and project examples.
Coursework
Environmental Geotechnical Engineering
Learning objectives:
- Axi-Symmetric flow of ground water into a well boring
- Axi-Symmetric heat flow in saturated soil
Practical information:
- Sessions will take place in [ISG-88], during week(s) [2-6].
- This activity [doesn't involve] preliminary work but read the lab handout prior to the lab session ([1 hr]).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
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.
E4
Understanding of and ability to apply a systems approach to engineering problems.
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.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 24/05/2022 12:55
Engineering Tripos Part IIA, 3D8: Geo-Environmental Engineering, 2024-25
Module Leader
Lecturers
Prof S P G Madhabhushi and Prof A Al-Tabbaa
Lab Leader
Timing and Structure
Lent term. 16 lectures and Lab.
Aims
The aims of the course are to:
- The aim of the course is to introduce the transport processes of fluids, water and pollutants, in the porous media that constitute the geo-environment.
- The module aims to address the factors that influence groundwater, heat and pollutant transport, practical and design applications and problems that might arise.
- This course aims to introduce the students to the flow regimes that occur in porous media and ways to estimate the flow quantities using flownets.
- Similarly heat flow through porous media is introduced drawing parallels with the groundwater flow.
- Contaminant transport through porous media is another important aspect in geo-environmental engineering that is addressed in this module.
- Practical ways to dispose waste into the ground, the effects the contaminants have on the host soil and necessary aspects of remediation of contaminated land will also considered.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand the geotechnical environment.
- Determine flow patterns in steady state groundwater seepage.
- Evaluate potentials, pore water pressures, and flow quantities in the ground by constructing flow nets.
- Anisotropic soils and flow nets
- Seepage below concrete dams
- Seepage through embankment & earth dams
- Excavations and seepage, Cofferdams and stability
- Draw parallels between groundwater flow and heat flow in porous media
- Develop necessary skills to estimate heat storage and extraction from ground
- Introduction to contaminated soil and its remediation
- Understand the soil properties that affect the geo-environment and vice versa
- Develop an understanding of the interactions between soils and contaminants
- Understand the effect of soil contamination on geotechnical properties
- Develop an understanding of the fate and transport mechanisms of contaminants in the ground
- Solving of Advection-Dispersion equation using error functions
- Develop appreciation of the contaminated land/landfills environment
- Understand disposal of waste into well-engineered systems
- Be able to design a solution relevant to land remediation or a landfill
Content
The following topics will be covered:
Flow of Water through Porous Media, is an important aspect in the design of many civil engineering structures such as retaining walls, caissons, excavation for foundations, etc. As it will be shown in the second part of the module, the same physical principles and mathematical concepts can be used to understand flow of heat in porous media, for example, in the design of energy piles or ground source heat pumps.
Contaminant Transport through Porous Media, is important to understand the presence of contaminants in the ground and how they are transported through various mechanisms and how they affect the properties of the soil. Equally disposal of waste of waste safely into well-engineered facilities is critical to minimise the environmental impact of the waste.
Groundwater, Seepage and Heat Flow in Granular media (8L)
- Introduction
- Concept of porous media and bulk properties.
- Definitions of potential head, pressure head and pore pressure.
- Groundwater flow and seepage
- Theory of flownets
- Anisotropic soils and flownets
- Darcy's law and Hydraulic conductivity
- Laboratory and in situ measurements
- Seepage below concrete dams
- Seepage through embankments and earth dams
- Stability and seepage around excavations
- Coffer dams and their stability
- Fourier’s law and heat flow in porous media
- Parallels between ground water flow and heat flow
- Ground source heat pumps
- Storage and extraction of heat from ground
Contaminated Land and transport of contaminants through ground (8L)
- Introduction to contaminated land and contaminants in the geo-environment
- Introduction to waste containment structures – landfills
- The structure of clays
- The clay-water interactions
- The clay-water-contaminant interactions
- The effect of contaminants on the geotechnical properties of soils
- Mechanisms of contaminant transport
- Fick’s law for diffusion in porous media, dispersion and sorption, Peclet’s number
- Solving advection-dispersion equation, Error functions
- Land remediation and waste containment design applications
- Relevant case studies and project examples.
Coursework
Environmental Geotechnical Engineering
Learning objectives:
- Axi-Symmetric flow of ground water into a well boring
- Axi-Symmetric heat flow in saturated soil
Practical information:
- Sessions will take place in [ISG-88], during week(s) [2-6].
- This activity [doesn't involve] preliminary work but read the lab handout prior to the lab session ([1 hr]).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
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.
E4
Understanding of and ability to apply a systems approach to engineering problems.
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.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 31/05/2024 07:29
Engineering Tripos Part IIA, 3D8: Environmental Geotechnics, 2020-21
Module Leader
Lecturers
Prof S P G Madhabhushi and Prof A Al-Tabbaa
Lab Leader
Timing and Structure
Lent term. 16 lectures and Lab.
Aims
The aims of the course are to:
- The aim of the course is to introduce the transport processes of fluids, water and pollutants, in the porous media that constitute the geo-environment.
- The module aims to address the factors that influence groundwater, heat and pollutant transport, practical and design applications and problems that might arise.
- This course aims to introduce the students to the flow regimes that occur in porous media and ways to estimate the flow quantities using flownets.
- Similarly heat flow through porous media is introduced drawing parallels with the groundwater flow.
- Contaminant transport through porous media is another important aspect in geo-environmental engineering that is addressed in this module.
- Practical ways to dispose waste into the ground, the effects the contaminants have on the host soil and necessary aspects of remediation of contaminated land will also considered.
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand the geotechnical environment.
- Determine flow patterns in steady state groundwater seepage.
- Evaluate potentials, pore water pressures, and flow quantities in the ground by constructing flow nets.
- Anisotropic soils and flow nets
- Seepage below concrete dams
- Seepage through embankment & earth dams
- Excavations and seepage, Cofferdams and stability
- Draw parallels between groundwater flow and heat flow in porous media
- Develop necessary skills to estimate heat storage and extraction from ground
- Introduction to contaminated soil and its remediation
- Understand the soil properties that affect the geo-environment and vice versa
- Develop an understanding of the interactions between soils and contaminants
- Understand the effect of soil contamination on geotechnical properties
- Develop an understanding of the fate and transport mechanisms of contaminants in the ground
- Solving of Advection-Dispersion equation using error functions
- Develop appreciation of the contaminated land/landfills environment
- Understand disposal of waste into well-engineered systems
- Be able to design a solution relevant to land remediation or a landfill
Content
The following topics will be covered:
Flow of Water through Porous Media, is an important aspect in the design of many civil engineering structures such as retaining walls, caissons, excavation for foundations, etc. As it will be shown in the second part of the module, the same physical principles and mathematical concepts can be used to understand flow of heat in porous media, for example, in the design of energy piles or ground source heat pumps.
Contaminant Transport through Porous Media, is important to understand the presence of contaminants in the ground and how they are transported through various mechanisms and how they affect the properties of the soil. Equally disposal of waste of waste safely into well-engineered facilities is critical to minimise the environmental impact of the waste.
Groundwater, Seepage and Heat Flow in Granular media (8L)
- Introduction
- Concept of porous media and bulk properties.
- Definitions of potential head, pressure head and pore pressure.
- Groundwater flow and seepage
- Theory of flownets
- Anisotropic soils and flownets
- Darcy's law and Hydraulic conductivity
- Laboratory and in situ measurements
- Seepage below concrete dams
- Seepage through embankments and earth dams
- Stability and seepage around excavations
- Coffer dams and their stability
- Fourier’s law and heat flow in porous media
- Parallels between ground water flow and heat flow
- Ground source heat pumps
- Storage and extraction of heat from ground
Contaminated Land and transport of contaminants through ground (8L)
- Introduction to contaminated land and contaminants in the geo-environment
- Introduction to waste containment structures – landfills
- The structure of clays
- The clay-water interactions
- The clay-water-contaminant interactions
- The effect of contaminants on the geotechnical properties of soils
- Mechanisms of contaminant transport
- Fick’s law for diffusion in porous media, dispersion and sorption, Peclet’s number
- Solving advection-dispersion equation, Error functions
- Land remediation and waste containment design applications
- Relevant case studies and project examples.
Coursework
Environmental Geotechnical Engineering
Learning objectives:
- Axi-Symmetric flow of ground water into a well boring
- Axi-Symmetric heat flow in saturated soil
Practical information:
- Sessions will take place in [ISG-88], during week(s) [2-6].
- This activity [doesn't involve] preliminary work but read the lab handout prior to the lab session ([1 hr]).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
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.
E4
Understanding of and ability to apply a systems approach to engineering problems.
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.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 13/09/2020 18:24
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