Engineering Science

Wave impact on coastal structures

Supervisor

Mark Battley
John Cater
Colin Whittaker

Discipline

Engineering Science, Mechanical Engineering, Civil and Environmental Engineering

Project code: ENG059

lighthouse in a storm

The overall goal of this work is to develop experimental and numerical methods to investigate the effect of wave impacts on coastal structures and landscapes. This topic is of increasing global importance due to climate change induced sea level rises and extreme weather events, and is also very important to communities exposed to under-sea seismic risks.

Specific aims of this project are to:

  • Design, manufacture and instrument a scale model object (such as vertical cylinder or scale model building) which can be impacted by waves in an existing lab scale wave impact facility
  • Implement a high-speed imaging system to experimentally characterise the full-field fluid flow velocities and the structural deformations of the scale model object.
  • Undertake water impact experiments and collect and analyse the imaging data.
  • Develop numerical models of the coupled fluid-structure behaviour, compare the predictions to the experimental measurements and refine and validate the modelling methodology.
  • Document the results in a technical report and poster.

This project would suit a student who has a good background in computational mechanics and has an interest in developing an understanding of experimental methods and full-field continuum imaging techniques.

Modelling of 3D and 4D Freeform Additive Printing

Supervisor

Mark Battley

Discipline

Engineering Science, Mechanical Engineering

Project code: ENG060

3D printed lattice-type structure

The aim of this project is to develop and validate analysis methods that can be used to accurately predict the deformation and failure of 3D printed lattice-type structures from bio-based materials, and use the models to explore opportunities for 3D and 4D behaviour, where the structure responds to its environment such as by changing shape, stiffness or other functionalities.

Desired outcomes from the project include developing and validating analysis methodologies that can predict expected properties based on constituent material and printer performance inputs, and understanding how the geometry and material choice can be tailored to achieve required functionalities. This will include analytical and numerical (e.g. FEA) modelling of the material and structural behaviour, and undertaking experimental testing to measure the performance under different loading and environmental conditions.

The student should have a good understanding of mechanics of materials and structures, and an interest in learning more about how to apply various analysis methods to real-world problems.

CubeSat Antenna Testing

Supervisor

John Cater, Andrew Austin, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG061

This project will investigate and determine the antenna radiation pattern from a CubeSat, under different solar panel deployment scenarios. Antenna design or radio physics experience desirable.

Orbitology

Supervisor

John Cater, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG062

In this research the applicant will Develop a workflow to determine a preliminary orbit of a CubeSat deployed from a RocketLab Electron launch into low Earth orbit. Software experience is desirable.

Life in our Solar System

Supervisor

John Cater, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG063

This project will scope and design a mission to neighbouring planets and moons to look for evidence of life off-Earth within our solar system using micro-fluidic technology, such as the lab-on-a-chip. Knowledge of life processes is desirable for this project.

Synthetic Aperture Radar data processing

Supervisor

John Cater, Andrew Austin, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG064

This project will use existing radar data from the ESA Copernicus system to analyse markers of environmental pollution in New Zealand. Software programming or GIS experience is desirable.

Monitoring the Hauraki Gulf

Supervisor

John Cater, Andrew Austin, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG065

We need to develop a sensor suite for monitoring oceanic conditions in the Hauraki Gulf, suitable for drone or aircraft fly-over missions. Optics or image analysis is preferred.

Barriers and enablers of commuter cycling: The role of the weather in mode choice

Supervisor

Andrea Raith, Kim Dirks

Discipline

Engineering Science

Project code: ENG066

We seek to better understand the connection between commuter cyclist trips and the weather in this project. We will analyse available meterological data including temperature, rainfall, wind, sunshine hours as well as cycling data to understand the connection between commuter cyclist trips and weather. Cyclist data is either obtained from counters alongside popular cycle paths, such as the northwestern shared path, or from websites such as Strava.com, where members can log their trips giving information about the exact route travelled.

Initial results indicate that cyclist numbers on the northwestern shared path are significantly higher during working days, indicating that this is indeed a commuter route. Cyclist numbers also appear to be correlated with different weather variables. We will extend the analysis to include other environmental variables such as whether it was light or dark at the time of the journey, and analyse combinations of variables to answer questions such as “are people happier to ride in the rain if their commute is in the light”?

We will also analyse cyclist routes from Strava and seek to understand trade-off between directness of routes and available cycling infrastructure, as well as other environmental parameters such as traffic, green space. For instance there is evidence elsewhere that cyclists do take detours in order to travel on cycle paths that are separated from routes. We may also be able to analyse gender differences in this context.

Ultimately this analysis could help better model uptake of cycling. The analysis of cyclist routes can feed into route choice (shortest path) models that can help optimise the location of new infrastructure when planning the extension of cycling networks.

Skills: R will be used for data manipulation statistical analysis, and a GIS system such as ArcGIS or qGIS will be used to extract cycle route information. Any student who is confident in R programming, and willing to independently learn to use GIS tools should be able to work on this project.

Electric Vehicle Routing

Supervisor

Andrea Raith

Discipline

Engineering Science

Project code: ENG067

One major concern with electric vehicles is that people suffer from what is called range anxiety, the fear of running out of energy before reaching the destination. On the one hand, drivers underestimate how far an electric vehicle with a full battery can drive. On the other hand, there are not that many public charging stations in New Zealand (see plugshare.com).

As part of this project we will develop a website that lets a user choose trip origin and destination, and display different routes that could be taken with charging stops, based on different types of electric vehicles.

We will build on existing models of electric vehicle energy consumption as well as develop new biojective shortest path methods to find routes that are short in terms of travel time, feasible in terms of the vehicle’s battery charge, and convenient for the traveller (such as having charging stops in interesting places, or where one can schedule a lunch break, for instance).

This project will build on existing python code, and some web programming will be necessary. A student who is confident in programming, and willing to independently learn new things should be able to work on this project.

Turning waste to gold: using microbes to treat e-waste

Supervisor

Dr. Vinod Suresh (Engineering Science)
Dr. Will Barker (Mint Innovation)

Discipline

Engineering Science

Project code: ENG068

94,000 tonnes of electronic waste will be landfilled in New Zealand this year. Not only is this terrible for the environment, but it wastes valuable metals such as gold, copper and rare earths. Mint has developed a novel process that dissolves printed circuit boards (PCBs) and utilises metal scavenging microbes that selectively absorb precious metals from the chemical soup. Mint’s process has scaled from the lab bench to a pilot plant which can process several kilograms of PCB’s. In this project you will work alongside Mint’s process engineers to design and build a demonstration plant which will process PCBs in tonne volumes recovering several kilograms of precious metals.

The project will involve carrying out detailed design calculations for process equipment (pumps, instrumentation, heat transfer equipment), carrying out lab and pilot trials and testing to confirm design parameters, and consultation with vendors and procurement of equipment.

The summer internship is open to students who are completing part 3 in any engineering specialisation. The student will need to be able to thrive in an ever changing environment and hold their own in ambiguous technical situations.

Probabilistic machine learning models for detecting the transition from Brownian to active Brownian motion

Supervisor

Andreas Kempa-Liehr

Discipline

Engineering Science

Project code: ENG069

The transition from Brownian to active Brownian motion is a phenomenon, which is observed in complex self-organizing systems like e.g. dissipative solitons in semiconductor gas-discharge systems. Recently, the underlying theoretical models [1, 2, 3], which had predicted this transition [4, 5], have been used as benchmark data sets for machine learning libraries automating time series feature extraction [6].
This research projects extends the analysis of the original stochastic time series analysis from [4, 5, 7] with respect to probabilistic machine learning models, like e.g. Baysian Linear Regression. The data science project will start with the extraction of the experimental results from the original textual data format, amend them to a publishable format for the UCI machine learning repository [8], develop probabilistic machine learning models, and publish the findings in a research journal.
Basic programming skills are required, however a thorough introduction to Python, Jupyter notebooks, Revision Control, the data science process and probabilistic machine learning models will be given.
1. Andreas W. Liehr. Dissipative Solitons in Reaction Diffusion Systems. Mechanisms, Dynamics, Interaction, volume 70 of Springer Series in Synergetics. Springer, Berlin, 2013.
2. M. Or-Guil, M. Bode, C. P. Schenk, and H.-G. Purwins. Spot bifurcations in three- component reaction-diffusion systems: The onset of propagation. Phys. Rev. E, 57:6432–6437, 1998.
3. M. Bode, A. W. Liehr, C. P. Schenk, and H.-G. Purwins. Interaction of dissipative solitons: particle-like behaviour of localized structures in a three-component reaction- diffusion system. Physica D, 161(1-2):45–66, 2002.
4. A. W. Liehr, H. U. Bödeker, M. C. Röttger, T. D. Frank, R. Friedrich, and H.-G. Purwins. Drift bifurcation detection for dissipative solitons. New Journal of Physics, 5(89):1–9, 2003.
5. S. V. Gurevich, H. U. Bödeker, A. S. Moskalenko, A. W. Liehr, and H.-G. Purwins. Drift bifurcation of dissipative solitons due to a change of shape: experiment and theory. Physica D, 199(1–2):115–128, 2004.
6. Maximilian Christ, Nils Braun, Julius Neuffer, and Andreas W. Kempa-Liehr. Time series FeatuRe extraction on basis of scalable hypothesis tests (tsfresh – a Python package). Neurocomputing, 2018.
7. H. Bödeker, A. W. Liehr, T. D. Frank, R. Friedrich, and H.-G. Purwins. Measuring the interaction law of dissipative solitons. New Journal of Physics, 6(62):1–18, 2004.
8. Dua Dheeru and Efi Karra Taniskidou. UCI machine learning repository, 2017.

Collective cell migration in proliferating biological tissues: simulation and parameter estimation for individual-based models

Supervisor

Oliver Maclaren, Vinod Suresh

Discipline

Engineering Science

Project code: ENG070

Biological tissues are often approximated as homogeneous and/or continuous materials and modeled using partial differential equations. These tissues are, however, made up of large numbers of individual cells and can exhibit both ‘collective’ and ‘individual’ behaviors.

Thinking of tissues as arising from collections of individual cells is particularly important when trying to understand the regulation and dysregulation of ‘active’ tissues such as epithelia, which contain individually proliferating and migrating cells. Such proliferating tissues play particularly important roles in phenomena such as wound repair, embryogenesis, morphogenesis and the formation and growth of tumours. In this latter case, small numbers of ‘mutant’ cells can have large resultant effects, e.g. the progeny of a single cell can take over an entire region of the tissue.

This project will consist of developing ‘individual-based’ models, also known as ‘cell-based’ or ‘agent-based’ models, of proliferating cell populations. The student will explore ways of simulating these models, as well as ways of relating them to real experimental data using computational and statistical parameter estimation methods. It would suit a student with an interest in learning more about computational biology, simulating individual-based mechanistic models, and statistical parameter estimation.

Boiling Gold out of Geothermal Systems: Earthquakes, Collapsing Volcanoes and Magma Pulses

Supervisor

David Dempsey

Discipline

Engineering Science, Physics, School of Environment

Project code: ENG071

In the Rotokawa and Mokai geothermal systems, a lot of gold is dissolved in the hot geothermal waters. However, when we go looking for this gold in the form of economically extractable veins, there seem to be none. Apparently, there is a disconnect between gold in the water and gold in the rock.

The best way to get gold out of geothermal water is to boil it. This can occur if pressure drops abruptly, for instance after an earthquake or when an overlying volcano collapses. Alternatively, a deep pulse of magmatic fluid could increase temperatures to boiling. What is less well known is how large these perturbations have to be, over what timescales, and how much gold would be precipitated.

The goal of this project is to solve a simple heat and mass balance for a geothermal reservoir, accounting for different perturbations that could induce boiling. This model should be implemented in Python and visualised in a Jupyter notebook, for coding non-experts to get a feel for the different competing physics.

Note: Candidate would need programming skills in Python or MATLAB, and mathematical background in heat/mass conservations laws or thermodynamics.

Building a generic tool box for simulating patient transits

Supervisor

Michael O’Sullivan

Discipline

Engineering Science

Project code: ENG072

The ORUA research group has a flagship model for a simulation model of patient transits at North Shore Hospital. Several steps of the process is automated, but more work needs to be done into order to provide a generic modelling tool box for any hospital.

This project will work towards the realisation of that tool box. Students will need knowledge of Java and Python.

Building a generic toolbox for simulating piling operations

Supervisor

Michael O’Sullivan

Discipline

Engineering Science

Project code: ENG073

The ORUA research group has an initial simulation model for piling operations. There is interest from the construction industry for more models of other piling operations, but more work needs to be done into order to provide a generic modelling tool box for any piling operation.

This project will work towards the realisation of that tool box. Students will need knowledge of Java and knowledge of Python would be preferred, but is not essential.

Participate in international optimization challenge

Supervisor

Caroline Jagtenberg

Discipline

Engineering Science

Project code: ENG074

winners of the 2017 VErog challenge

Together with your supervisor, you will participate in a so-called ‘solver challenge’. This means you write code to solve an optimization problem, and compete with several teams world wide for the best solutions.

The problem at hand will be a vehicle routing problem, but one with special features. You will program a piece of software that reads in problem instances and writes solutions to file. And the most interesting part happens in between! You can try some of the optimization techniques that you are already familiar with, and will learn a few new ones along the way. No design of user interface necessary – everything is txt based. The focus of this project is more on optimization than on programming; however, note that you will spend a lot of your time programming.

Both exact methods and heuristics are allowed. If you don’t know what those are: sorry, you are probably not qualified.

Skills required

- At least one programming language of your choice (e.g., C#, C++, Java).
- Knowledge of Operations Research

Timing

flexible throughout summer.

FAQ

1) What can we win?

There is some prize money (8000 nzd is distributed over the top 3 teams), as well as bragging rights (winning such a challenge is something to put on your resume!). In the past, the organizers of this challenge have also paid for plane tickets for the top 3 teams to come to Europe and talk about their solutions. But let’s not get ahead of ourselves…

2) What’s my supervisor background regarding this challenge?
Your supervisor organized such a challenge last year, and personally knows the organizers of the challenge this year.

Software Development for orbital radar

Supervisor

John Cater, Andrew Austin, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG075

This project will use start of the art Arena miniaturized radar system to create an unfocussed synthetic aperture radar system for use in space. Some programming experience is required.

Plasma thruster development

Supervisor

John Cater, Andrew Austin, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG076

Development of plasma thrusters for satellite manoeuvring, including possible testing at the Advanced Instrumentation Technology Centre in Australia. Physics or mechanics experience desirable.

Titanium foams for space

Supervisor

John Cater,Peng Cao, Nicholas Rattenbury

Discipline

Engineering Science

Project code: ENG077

Research into the creation and mechanical properties of titanium alloy foams for use in space. Materials testing experience preferred.

Adding Multi-criteria Optimisation to OpenSolver

Supervisor

Andrew Mason
Andrea Raith

Discipline

Engineering Science

Project code: ENG078

This project will extend the popular open source optimiser, OpenSolver, so that users can model and solve optimisation problems with more than one objective using Excel. Solving these problems requires showing users a set of possible solutions, and letting them easily understand the trade-offs in these solutions. We will need to develop good solution algorithms and new visualisation tools to let the user explore the solution set.

The student needs good skills in programming (preferably with some VBA experience), experience using OpenSolver, and an understanding of linear and integer programming.

A new Simulation and Scenario Manager tool for Excel

Supervisor

Andrew Mason

Discipline

Engineering Science

Project code: ENG079

Through our work on the popular open-source optimiser, OpenSolver, we have developed a good understanding of the needs of Excel users and the technologies available to meet these needs. An important area that OpenSolver does not yet address is simulation in Excel. This project will extend existing work to create an open-source simulation environment for Excel that is easy to use, tightly integrated with OpenSolver, and includes new visualisation tools to help users visualise and understand their simulation results. This project will also continue work on a closely-related scenario manager tool that is currently in beta development

The student needs good skills in programming (preferably with some VBA experience), experience using Excel (and ideally OpenSolver), and a willingness to experiment with and learn new software tools. This work may involve collaboration with other open-source developers in this space.

Developing an online SolverStudio for Google Sheets: A New Online Optimisation Tool

Supervisor

Andrew Mason

Discipline

Engineering Science

Project code: ENG080

SolverStudio is an Excel add-in that allows optimisation models to be built using Excel and modern modelling languages such as the AMPL clone GMPL. This project will build on our experience moving OpenSolver to the online Google Sheets framework to create a new add-in that allows GMPL models to be built and solved using Google Sheets.

The student will need experience programming in JavaScript and developing web sites with client-side code. Experience with the Google API’s would be a bonus.

Enhancement of SolverStudio for Excel

Supervisor

Andrew Mason

Discipline

Engineering Science

Project code: ENG081

SolverStudio is an Excel add-in that allows optimisation models to be built using Excel and modern modelling languages such as PuLP and JuMP. This project will extend SolverStudio by adding support for more modelling languages (including SCIP), adding new visualisation capabilities, and creating a new interface for creating and editing OpenSolver models within SolverStudio.

The student will need good programming skills, and will ideally have experience with Python and perhaps Visual Basic. Experience in C# would give more scope for the range of improvements that could be implemented, but is not essential.

Advanced tools for Analytics Visualisations in Excel

Supervisor

Andrew Mason
Tony Downward

Discipline

Engineering Science

Project code: ENG082

Microsoft have recently released a new coding framework for extending Excel with browser-based tools. We have some limited experience in using these new capabilities to create new visualisations and interactive tools within Excel. This project will build on this preliminary work to create new open-source Excel add-ins based on this new technology. Possible applications include adding new plotting capabilities to SolverStudio, displaying interactive visualisations of OpenSolver’s Branch and Bound process, building interactive Gantt charts and staff scheduling displays, building 3D visualisations for the Simplex algorithm, etc.

The student will need experience programming in JavaScript and developing web sites with client-side code. Experience with the Microsoft Office Javascript API’s would be a bonus.

OpenSolver optimisation for Libre Office

Supervisor

Andrew Mason

Discipline

Engineering Science

Project code: ENG083

OpenSolver is a popular open source optimisation tool that is currently only available for Excel. This makes it inaccessible to those who choose to use open source spreadsheets such as Calc in Libre Office. This project will develop a first release of OpenSolver for Libre Office, written either using Python or OpenOffice Basic.

The student will need experience with Linux, good programming skills, and a willingness to learn much more about the inner workings of Libre Office than is known by their supervisor!

Analytics for Identifying Māori Shareholders

Supervisor

Andrew Mason
Andy Philpott

Discipline

Engineering Science

Project code: ENG084

We are commencing a National Science Challenge project that involves developing analytics and optimisation tools that can help identify missing shareholders. Many Māori organisations have a growing number of shareholders and face the very real challenge of keeping track of these shareholders. This is not easy, as demonstrated, for example, by the over $3,000,000 of dividends that the Taranki-based organisation, Parininihi ki Waitotara (PKW), has owing to missing shaeholders. Similar problems are faced by the Māori Trustee who is tasked with managing Māori land, where each land parcel can have 100’s of owners. We are developing analytics tools that use public information to help organisations such as PKW better understand and locate its missing shareholders. We are seeking a student with good programming and mathematical modelling skills to work with us in developing these tools.

Advanced non-linear optimisation for OpenSolver – the open source optimiser for Excel

Supervisor

Andrew Mason

Discipline

Engineering Science

Project code: ENG085

This project will develop a new enhanced non-linear tool for OpenSolver – a popular open source optimiser for Excel that has been downloaded over 335,000 times. OpenSolver currently solves non-linear models by translating the Excel spreadsheet formula into various internal formats before writing out a file suitable for a non-linear solver. This leads to many problems, including memory overflows, crashes, poor error messages, and slow solving. We are seeking a student with good VBA (and/or C#) skills to create a new approach for handling non-linear problems. These changes will address the most common complaints from our OpenSolver community, and make a real difference to our tens of thousands of users.