PhD Opportunities
Possible research topics to be undertaken in the Systems, Power & Energy Division of the James Watt School of Engineering are given below. If you are interested in any of these projects, you should email the prospective supervisor for discussing your intentions.
The School of Engineering has a limited number of scholarships to offer to excellent candidates, application shall be discussed with the potential supervisor. The deadline for application is 31 January 2023. See details on Scholarships on our our Postgraduate Research page.
Alternatively, you are welcome to identify a different project topic within any relevant research areas by emailing your project proposal to the Head of Division, Dr Steven Neale, who will direct you towards a prospective supervisor with expertise in that area.
Themes
Medical and Industrial Ultrasonics
Medical and Industrial Ultrasonics
Processing of minerals through high power ultrasound
Supervisors
Description
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The dissolution of mineral ores to extract the metals they contain is a vital activity that contributes to supplying global economies with the strategic and base metals they need to build and maintain infrastructure and technologies. Societal pressure is driving a paradigm shift towards more environmentally sustainable supply chains, and this demands the development of more environmentally benign green processing of ores to extract valuable metals they contain. This project will focus on developing new ways to dissolve minerals that conventionally require complex, energy-intensive techniques involving large volumes of toxic chemicals. The project will explore more sustainable processing options using research at the interface of ultrasonics, engineering, and chemistry, with a view to upscaling the best performing technology to meet demand from industry.
In today's beneficiation processes, minerals are usually concentrated from rock materials with the use of flotation. Then the use of surfactants must be applied. Such agents stick to the surface of the finely grained particles and may cause impact on the subsequent processing on the deposited particles and may contaminate the soil. Ultrasonic cavitation may offer an alternative to flotation if selective leaching can be applied causing the valuable and critical metals to be leached and leaving ordinary minerals unperturbed.
In this project, three approaches will be investigated. The first is ultrasound- assisted digestion of ores using conventional solvents, the second is combined ultrasound and microwave assisted digestion of ores using conventional solvents, and the third is ultrasound-assisted digestion of ores using deep eutectic solvents.
The influence of ultrasound on the dissolution of ores in conventional mineral acids (such as HCl and H2SO4) will be investigated to determine the degree to which it allows a reduction in the use of these toxic solvents to achieve industrial objectives. It is known that cavitation can accelerate dissolution processes by reducing particle size, attacking protective barriers (for example oxides) on surfaces, and potentially through the production of new chemical species. Dedicated research on these effects within the field of hydrometallurgy is lacking and this research will provide fundamental insight into the most basic application of high-power ultrasound in hydrometallurgy.
Microwaves have been used to accelerate the dissolution of particularly refractory minerals such as silica. The second set of investigations will look at the degree to which the combined use of sonication and microwaves can be used to dissolve silicate minerals containing beryllium and rare earth elements.
Lastly, the potential of sonicated deep eutectic solvents to dissolve sulphide minerals will be investigated. The Centre for Medical and Industrial Ultrasonics in the James Watt School of Engineering, University of Glasgow, is currently investigating these ionic solvents which are both biodegradable and have remarkable, tuneable solvent properties. It has already been shown that ultrasound can enhance dissolution of plant matter in these solvents, producing higher yields and faster reaction times compared to processing without ultrasound. Therefore, many opportunities exist to applying the sonication of these solvents to extract metals from minerals.
How to Apply: Please refer to the following website for details on how to apply: http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/. |
Next-generation self-powered piezoelectric ultrasonic wearable devices for healthcare applications
Supervisors
Description
Wearable healthcare devices are forecast to be dominant in health monitoring over the coming years. Ultrasonic wearables will be vital for domestic monitoring of health indicators such as blood pressure. Significant progress has already been made in harnessing the properties of piezoresistive materials, but a fundamental limiter is the requirement of external power, restricting the patient or end-user experience. The goal of this doctoral research project is to develop unobtrusive and self-powered wearable technology based on piezoelectric materials, by replacing bulk-form piezoelectric materials with layered, advanced composites. The project will involve fabrication of piezoelectric sensors, with characterisation of the electromechanical and physical properties using techniques such as impedance spectroscopy, piezoelectric and surface roughness analysis. The piezoelectric devices will be embedded into a flexible polymer (such as PDMS) with development and implementation of power management circuitry, ensuring that small movements can be reliably measured.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Shape memory materials for adaptive ultrasonic devices
Supervisors
Description
Ultrasonic devices are an essential technology in applications across medicine, industrial processing, and sensing. However, those devices which are designed for low ultrasonic frequencies (approximately 20 – 100 kHz), tend to be optimised for operation in one resonant mode. They require precise control of geometry and material properties in order to tune device parameters such as resonance frequency and amplitude. The objective of this project is to engineer new multifunctional ultrasonic transducers with adaptive properties by using shape memory materials (SMMs). These are materials which can be trained to change state in response to a specific stimulus, such as temperature or stress. It is anticipated that the incorporation of SMMs into novel designs of ultrasonic transducer will open several new industrial and medical applications.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Green processing of ores and e-waste by sonocatalysis in deep eutectic solvents
Supervisors
Description
Deep Eutectic Solvents (DESs) are a class of liquids, many of which are biodegradable and environmentally benign, with remarkable solvent properties. Traditionally, they have been popular for dissolving plants for valuable chemicals, where ultrasound can enhance dissolution, producing higher yields and reaction times compared to processing without ultrasound. However, sonication in these solvents in the mineral processing field or in the recycling of e-waste must be investigated. This doctoral research project will explore sonocatalysis of DESs in mineral processing from both ores and e-waste, promoting significant reductions in the environmental impact of metal / mineral processing, realising a new highly-scalable green technology.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Ultrasonic fluidisation of granular materials for industry and exploration
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Granular materials are among the most widely-traded substances, as they include many fuels, foods, and feedstocks. They also cover large parts of the Earth, both surface and subsurface, and parts of other asteroids, moons, and planets as well.
These materials are difficult to handle. They can behave as quasi-fluids, but more often they are almost uniquely challenging. If you have ever tried to press your finger directly into sand, without wiggling, you will discover that their stiffness rapidly increases. Similarly, they can stop the rotation of a drilling auger, and jam in the chutes of handling systems.
One solution may be ultrasonic vibration. Our initial studies have shown that sonicated tools can ‘fluidise’ granular materials, making them flow almost like a liquid. With viscosity reduced, penetrators and augers can operate more easily. We can push through the materials, and handle them as we wish, with lower forces and less power. We may even be able to pump them like liquids. This has the potential to facilitate both trade and planetary exploration, where landers might have to drill through regolith using low forces and torques in a low gravity environment.
This project will require the design of resonant ultrasonic tools, and the construction of autonomous mechatronic drilling rigs to carry out multiple penetrometry and augering tests in granular materials such as glass microspheres. Applications to use external, variable-gravity facilities are also anticipated.
High-speed imaging and emission characterisation of acoustically activated drug delivery particles
Supervisors
Dr Paul Prentice
Dr Helen Mulvana
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Acoustically activated microbubbles (and advanced particles based on microbubbles) for localised and non-invasive drug delivery to a range of organs (including brain and pancreas), continue to attract significant and world-wide research attention, including numerous in-vivo and preclinical trials. In publications generated by this research, it is common for therapeutic bioeffect to be reported in parallel with some representation (often the noise-spectrum) of the acoustic emissions detected from the driven microbubble population, such that the bubble activity can be classified or quantified for correlation to the drug delivery, or degree of tissue damage.
Somewhat remarkably, however, the behaviour of microbubble populations within blood vessels, exposed to therapeutic ultrasound – and in particular, the acoustic emissions generated – are still poorly understood. Clearly, this deficit in knowledge hinders refinement and optimisation of exposure and detection protocols, but is also critical to understanding the mechanisms underpinning microbubble mediated therapies.
This project is dedicated to addressing this deficit, using two state-of-the-art ultra-high speed cameras, a range of hydrophone detectors (including with complex calibration for magnitude and phase response), and research-enabled diagnostic imaging arrays, to interrogate and characterise microbubble activity in capillary models. Dual high-speed imaging will allow unprecedented investigations of phenomena at varying timescales – for example, clustering dynamics under the action of secondary radiation forces during the initial acoustic exposure, and temporally resolved cluster oscillations (at image acquisition rates of up to 10 million frames per second) for direct correlation to the detected acoustic emission.
Therapeutic ultrasound parameters including frequency, pressure amplitude and pulsing duty cycle, as well as microbubble concentration, and flow rate (to mimic blood circulation) will all be systematically studied. The work will make use of anatomically accurate flow phantoms, already in use to study the physiological effects of blood vessel geometry and flow on microbubble dynamics and in vivo delivery data arising from a separate study to use microbubbles for delivery to the rat placenta.
Advanced drug delivery vehicles will also be investigated in the latter stages of this project, including
- Acoustic Cluster Therapy (ACTTM; combining commercial GE healthcare microbubble agent, Sonazoid, with drug-loaded vapourisation droplets), via an existing industrial collaboration with manufacturers; Phoenix Solutions AS (Oslo, Norway).
- SPION (superparamagnetic iron oxide nanoparticles) microbubbles as novel multimodal contrast agent for magnetomotive ultrasound imaging
Flexible ultrasonic surgical devices
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Ultrasonic devices for surgery applications rely on resonant structures. This results in the surgical tips being simple geometries, usually straight or with a single bend. Many surgical procedures require devices to reach locations in the body that are difficult to access and therefore a flexible device, able to move along a tortuous path to the site of surgery would have very significant advantages.
This project investigates a completely new approach to the design of ultrasonic surgical devices. The surgical tips will be driven by new, innovative transducers that can enable the device itself to be flexible. The project will research the capabilities of innovative transducers to deliver sufficient ultrasonic excitation and the optimal vibrational motion to the surgical tip to perform precision cutting of tissue. A key focus of the research will be in miniaturisation of devices for minimal access surgeries.
Smart ultrasonic transducers for surgical devices
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
A significant research effort in the Ultrasonic Group is developing new ultrasonic surgical devices, particularly for miniaturised minimal access surgeries involving bone cutting procedures. Recent research has been successful in incorporating a shape memory alloy (SMA), Nitinol, in a novel ultrasonic cymbal transducer. The transducer is capable of being operated in the same mode of vibration at two distinct resonant frequencies through a phase change in the material as a result of a small change in temperature.
This project will investigate how the temperature change required for the phase change can be controlled and minimised through the choice of material and will also investigate other phase change materials. Research will also focus on how the phase change could be achieved through small changes to the loading of the transducer. Methods of driving the transducer to deliver the required phase change will also be researched. The project will develop alternative transducer designs that can incorporate SMAs for dual or multiple frequency operation. The overall aim will be to deliver small surgical devices that can cut both soft and hard tissues with a single ultrasonic surgical device.
Space and Exploration Technology
Disassembly and reconfiguration of rubble pile asteroids
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Asteroids offer to provide material resources to support a range of future space ventures, spanning metals for in-orbit manufacturing and water for in-situ production of propellant. Our prior studies have considered the dynamics of asteroid disassembly using rotational self-energy.
This project will investigate strategies to disassemble rubble pile asteroids using an N-body simulation of the physics of the rubble pile. Disassembly may be required for resource processing, or to reconfigure material for manufacturing structures such as habitats. Such strategies will include free-flying units which remove masses in a serial or parallel fashion, while the rubble pile relaxes into a new minimum energy state after each mass is removed.
Key research questions include:
- What are the physical limitations on the disassembly of rubble pile asteroids given their gravitational binding energy?
- What strategies can be devised for disassembly using either single or multiple free-flying robotic platforms operating serially or in parallel?
- Can the dynamics of binary asteroids be leveraged to initiate and engineer the flow of material between asteroids?
The project will combine mathematical modelling and simulation to investigate these research questions. Candidates should therefore have a strong aptitude for and interest in mathematical modelling and simulation. The project will be embedded within a large research group pursuing a programme of novel research on emerging space technologies.
Orbit and attitude control of femtospacecraft
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Femtospacecraft offer to deliver a broad range of new mission applications spanning space physics, Earth remote sensing and planetary science. A key issue will be the development of strategies to actively control both the orbit and attitude of such small devices.
This project will investigate novel obit and attitude control strategies based on our Mercury 3.5 x 3.5 cm femtospacecraft. The platform comprises a microcontroller with integrated communications, MEMs attitude sensing and 3-axis magnetic actuation. Key research questions include:
- What attitude control laws are suitable for resource-limited femtosatellite? This task will include both modelling, simulation and laboratory experiments
- What is the trade-off between energy/volume used and performance of the attitude control system?
- How can the orbit of a resource-limited femtosatellite be actively controlled and how can the physics of the space environment be leveraged for such tasks?
- How can spatial patterns be formed in swarms of large numbers of such devices to enable new applications of femtosatellite technology?
The project will combine mathematical modelling, simulation and some laboratory-scale testing using an air-bearing and Helmholtz cage to investigate these research questions. Candidates should have strong aptitude in mathematical modelling and simulation and an interest in pursuing laboratory experimentation. The project will be embedded within a large research group pursuing a programme of novel research on emerging space technologies.
Quantum computing for space trajectory design and optimisation
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Quantum computing one of the most important emerging technologies: a step change in our ability to solve difficult problems, in the same way conventional computers have been in the sixties. Conventional computers rely on bits, which can carry on/off information; quantum computers use quantum bits, or “qubits”, which can represent several states at once, exploiting the superposition effect of quantum theory. This allows them to work much faster than conventional computers, and adding more qubits make quantum computers exponentially faster, allowing them to solve problems that are so difficult that are out of reach for ordinary calculators.
In the space mission design, the trajectory design problem is a difficult one, even more so when multiple bodies and/or targets have to be selected from a set (e.g. multiple planetary swing-bys, multiple moon or asteroid tours, multiple satellite servicing and/or disposal): this creates a mixed combinatorial-continuous problem, where the combinatorial part is (broadly speaking) a variant of the classic Travelling Salesperson Problem (TSP), to select the sequence of bodies/targets, and in order to evaluate each sequence, a continuous optimisation sub-problem is to be solved. Quantum computing has the potential to dramatically improve the solution of this problem, my exploiting the superimposition of multiple possible paths at once.
As progress is being made into the hardware to make functional quantum computers, scaling up the number of qubits, this PhD will explore the formulation and solution of space mission design problems through a quantum computing. We aim to answer the following research questions:
- What quantum computing framework(s) can be used for space mission trajectory design?
- How can we leverage on and inject quantum computing to the space mission trajectory design problem, particularly when multiple bodies/targets are involved?
- How can trajectory design problems be encoded through a quantum algorithm?
- To what extent a full trajectory design problem can be implemented as (and take benefit from) a quantum algorithm?
Ultimately, we will assess to what extent, injecting quantum computing into the optimisation problem, we obtain a quantum advantage, both in terms of optimality of solution, and computational cost, for this specific application (narrow advantage).
The ideal candidate will have a background in computing science or similar discipline, with a strong interest in space technology and exploration, or vice-versa a background in space trajectory design with strong interest in computing science and programming.
In-orbit assembly: Robust autonomous methods for controlling robot manipulators in space
Supervisors
Dr Gerardo Aragon Camarasa (School of Computing Science)
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
With the current push towards space for both private and government organizations, and the recent increase on initiatives to the industrialization of space, there will be an important need for humans to be supported by robotic systems. Understanding and mastering the unique properties that will intervene in the robot behaviour is essential to offer a fully autonomous robotic system which will be expected to work with no human intervention while being robust, accurate and responsive.
The work will consider the different advantages of both traditional and AI-based control methodologies to support the development of a vision-based control system that is able to control a robot manipulator within the space environment during in-orbit assembly tasks. The expected outcome of this work will be a simulation environment of a suitable setup and a practical real-life implementation.
This project will engage with recent research studies on the field on autonomous robotics, building in-orbit structures, satellite assembly and support studies on manufacturing in space. This project can also engage with users beyond space, with advanced manufacturing research being a potential area to explore.
Background in either control engineering mechatronics, computing science, and/or space engineering is highly recommended. In order to be eligible to apply for the School of Engineering Scholarship, an excellent CV is required.
RESEARCH LINES
This project explores the following lines of research:
- Robotic arms for manufacturing in space
This line of research focuses on the analysis of the dynamics, kinematics, and grasping methodologies of the robotic arms while on orbit. This addresses problems related to autonomous robotics, target capture strategy, tackling a moving orbiting object, mathematical approach to the robotic arm dynamics, and contact forces. In addition, the major physical interactions while executing tasks on orbit such as building in-orbit structures, satellite assembly, and space manufacturing, will be considered.
- Approaches for controlling robotic manipulators in space
This line of research focuses on the analysis and exploration of traditional and AI-based control methodologies, intelligent control algorithms, and an integrated vision-based control system. This addresses problems related to the vision system embedded in the robot, environment simulation, and parameters such as speed, torque, vibration, and attitude disturbance.
Optimisation of inter-satellite communications
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Intersatellite links (ISLs) are telecommunication routes between different satellites which allow a swarm or constellation of satellites (or agents) to effectively become a network of relay nodes. ISLs can be used to share data amongst different nodes of a network; one possible aim is to maximise the bandwidth between two specific agents in the network, or between an agent and an external entity (e.g. a ground station in the space scenario). With these links in place, satellites in large-enough constellations can communicate with relevant ground stations in quasi-real-time, regardless of whether the ground station is in line-of-sight and/or range. It is clear that the extent of the usefulness of ISLs depends on the effectiveness of the routing strategy employed. The main difficulty in utilizing ISLs is the fact that in most satellite constellations, the network topology is time-varying; links will constantly be found/lost as each satellite progresses along its own orbit, hence the effectiveness of the routing strategy becomes key to exploiting the availability of ISLs.
This PhD will investigate distributed algorithms for the autonomous optimisation of ISLs within a satellite constellation. Previous research [http://eprints.gla.ac.uk/159120] has looked into the use of Ant Colony Optimisation, a bio-inspired technique that mimics the behaviour of ants foraging for food; the PhD will expand this research and assess and compare the use of other optimisation methods. It will also investigate the effect of constraints introduced into the network (such as unavailability of one or more nodes) and develop techniques to cope with them optimally. One of the paramount aspects to consider is that the system should be able to self-optimise itself (fully-distributed) without the need of a central controlling node. In this way, the loss of one or more agents does not prevent the swarm to continue to find optimal solutions.
The techniques developed for the satellite scenario can readily be extended to other applications with different agents, such as autonomous vehicles, drones, sensors, etc.
Background in computing science, applied mathematics and/or space engineering is highly recommended. In order to be eligible to apply for the School of Engineering Scholarship, an excellent CV is required.
Biomorphic control for micro-spacecraft swarms
Supervisors
Prof Colin McInnes
Dr James Beeley
Dr Kevin Worrall
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Early work on biomorphic autonomous spacecraft considered the use analogue circuits to mimic simple spiking neural networks. It has been shown that such biomorphic systems can demonstrate quite complex emergent behaviour and can be robust to failures. While our work on 3x3 cm PCB-satellites currently uses conventional microcontrollers, the use of biomorphic control may enable even smaller, yet capable devices.
This project will firstly investigate the use of biomorphic control for ultra-small, centimetre-scale micro-spacecraft and then further develop our ideas to consider a large networked swam of devices. Key research questions include:
- How can low-level behaviours be embedded in individual centimetre-scale micro-spacecraft; for example de-tumbling, Sun-pointing, target-pointing and orbit control?
- How can interaction between the low-level biomorphic control of members of a large swarm of such devices lead to emergent, complex high-level behaviour?
- What niche applications can be foreseen which leverage the benefits of biomorphic control while competing against the performance of conventional spacecraft swarms?
The project will combine modelling, simulation and laboratory-scale testing to investigate these research questions. Candidates should have an interest in modelling and simulation and an enthusiasm for laboratory experimentation. The project will be embedded within a large group pursuing a programme of novel research on emerging space technologies.
Energy and Sustainability
Effective Thermal Management of lithium-ion battery used in EV
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
Lithium-ion batteries are widely used in electric cars, but their efficiency and safety greatly depend on the temperature at which they operate. Therefore, a battery thermal management system (BTMS) is crucial to ensuring the safety of an electric vehicle. This research will develop a novel BTMS to investigate its cooling effectiveness through a comprehensive computational fluid dynamics (CFD) approach, coupling with structural influences in a battery pack. A data-driven approach such as machine learning could also be a potential scope to further enhance the model capability with the model validation performed by both the CFD and experimental dataset.
Investigation of Haemodynamic Significances of Vascular Diseases through Advanced Computational Methods
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
The project aims to develop robust non-invasive image-based MRI/CTA CFD models that will allow better understanding of the haemodynamic characteristics of blood flow linked to diseases in the artery causing a heart attack. We also aim to determine a physiological index called fractional flow reserve (FFR) from the simulation results to further assess the disease patterns in various vascular beds. The spiralling effect of blood on FFR will also be investigated. The research will be carried out in close collaboration with colleagues in the Institute of Cardiovascular and Medical Sciences at the University of Glasgow as well as with clinicians at hospitals. Relevant clinical data, such as CTA/4D MRI data, therefore, need to be collected, which will be assessed and used for the model development and validation. The research outcome will have significant potential to provide a better diagnostic measure and understanding of vascular diseases.
MXene-coated cathode particles for lithium-ion battery applications
Supervisors
Dr. Jun Young Cheong (JunYoung.Cheong@glasgow.ac.uk)
Prof. Mohammad Khalid (Mohammad.Khalid@glasgow.ac.uk)
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Lithium-ion batteries, since commercialisation in 1991, have been adopted in various applications (from electric vehicles to portable devices). The current challenge, especially in the industry, is to increase the loading amount of cathode materials to incur higher energy density. The capacity degradation when a thicker cathode electrode is used. Conductive coating is an effective way to increase the electrical conductivity of electrodes, which leads to enhanced cycle retention characteristics and rate capabilities at high loading amount of cathode. Nevertheless, so far interesting coating technology is yet to be explored in terms of the interface between the electrode and electrolyte.
The project aims to further our understanding of the structure-property relationship when the MXene coating is introduced in the commercially available cathode particles (such as LiCoO2, LiFePO4, LiNixMnyCozO2). MXene can be exfoliated from the MAX phase, and the MXene nanosheet then can be used to coat/cover the surface of the cathode particles, which is expected to enhance the electron transport and help preventing the side reactions between electrode and electrolyte. Both the structural analysis & electrochemical cell tests will be combined to further comprehend the structure-property relationship.
Introduction of electrolyte additive for stable operation of Zinc-ion batteries
Supervisors
Dr. Jun Young Cheong (JunYoung.Cheong@glasgow.ac.uk)
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Net zero carbon neutrality is one of the central themes nowadays and development of eco-friendly energy storage system is important. Zinc-ion batteries offer great advantages in eco-friendliness, abundance, and low cost arising from the use of abundant and thermally stable aqueous electrolyte. Due to the mildly acidic nature of electrolyte, however, corrosion of Zn metal is one of the most critical issues in zinc-ion batteries. Although surface protection of Zn metal has some positive progress, more research should be dedicated towards the design of novel electrolytes.
This project aims to introduce the novel electrolyte system by introducing an electrolyte additive based on biomaterial for stable operation of zinc-ion batteries. Research will focus on sorting out the potential additives for electrolyte system based on biomaterials, assembly and electrochemical analysis of aqueous zinc-ion battery cell, and postmortem analysis to understand the mechanism behind the performance improvement arising from the introduction of electrolyte additive. Microscopic observation (using SEM, TEM, and OM) as well as physicochemical characterisations (XRD, XPS, Raman, and FTIR) are carried out to elucidate the structure-property relationship.
Modelling all-solid-state batteries (Starting from 2024 or 2025)
Supervisors
Dr. Guanchen Li (Guanchen.Li@glasgow.ac.uk)
Description
All-solid-state batteries (ASSBs) have attracted significant attention as the next-generation power supply for electric vehicles (EVs) to support a sustainable net-zero society. ASSBs can double an EV's mileage and significantly reduce the risk of battery thermal runaway. However, the lifespan of ASSBs is insufficient for EVs. Due to the rigid nature of solids, ASSBs suffer from cracking or contact loss in components (e.g., electrodes, current collectors and composite electrodes) during operation, consequently deteriorating the battery performance. Therefore, improving "mechanical compatibility" between ASSB components is necessary to extend lifespan. To accomplish this goal, we need to clarify the complex electro-chemo-mechanics and manage the stress at multiple scales to mitigate mechanical degradations in ASSB.
Objectives:
1. The student will have the unique opportunity to develop a new ASSB model, building on our latest works (e.g., Nature 2023 and Nature Materials 2021).
2. The student will be an integral part of our collaborative efforts, working with experimental groups from Oxford and UNIST (Korea) on modelling ASSB performance and failure.
3. The Multiphysics model will be used to design the next-generation ASSB.
Requirements:
1. A bachelor's or master's degree in engineering science, chemical engineering, mechanics, physics, applied maths or a related field.
2. Strong background in physics, mechanics or a related field.
3. Experience in computational modelling and data analysis.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Produce hydrogen from seawater: design and optimise next-generation electrolysers (Starting from 2024 or 2025)
Supervisors
Dr. Guanchen Li (Guanchen.Li@glasgow.ac.uk)
Description
The distinction between grey hydrogen and green hydrogen holds paramount importance in achieving net-zero carbon emissions. Grey hydrogen refers to hydrogen produced through a process called steam methane reforming, which relies on fossil fuels like natural gas as a feedstock. While widely used today due to its cost-effectiveness, grey hydrogen production emits significant amounts of carbon dioxide, thus contributing to climate change. On the other hand, green hydrogen is derived from renewable energy sources, such as wind or solar power, using electrolysers.
An electrolyser can use electricity to split water molecules into hydrogen and oxygen, emitting no carbon dioxide and thus converting renewable energy to clean fuels. As nations and industries strive to reduce their carbon footprints and transition to renewable energy sources, shifting from grey to green hydrogen is becoming increasingly imperative. However, traditional electrolysers are constrained by the need for pure water feedstock, limiting their applicability. This research aims to address this challenge by developing an electrolyser capable of producing hydrogen from seawater.
The student will simulate various processes within the electrolyser, including reactions, ion transport, bubble generation, and gas diffusion. Moreover, the student will explore the coupling of transport processes in diverse functional materials, such as solutions, polymers, porous media, composites, and beyond.
Objectives:
1. The student will develop new models for next-generation electrolysers, such as decoupled electrolysers.
2. The student will collaborate with experimental groups from the School of Chemistry on simulating electrolyser performance.
3. The Multiphysics model will be used to design next-generation electrolysers.
Requirements:
1. A bachelor's or master's degree in engineering science, chemical engineering, mechanics, physics, applied maths or a related field.
2. Strong background in physics, electrochemistry or associated areas.
3. Experience in computational modelling and data analysis.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Design an intelligent battery management system and a battery digital twin using physics-based model and data-driven algorithm (Starting from 2024 or 2025)
Supervisors
Dr. Guanchen Li (Guanchen.Li@glasgow.ac.uk)
Description
Lithium-ion batteries have been used extensively in cell phones and electric vehicles. In these devices, a battery management system monitors and controls battery operation. The battery management system uses models to estimate the battery states from simple measurements (e.g., voltage). These models tell us how much energy remains in a battery (State of Charge) and when a rechargeable battery needs replacement (State of health). An accurate physics-based model requires knowledge of the internal properties of the battery (e.g., effective ion conductivities and contact resistance at material interfaces). However, considerable uncertainties exist in these internal properties due to the manufacturing process. Data analysis is required to find proper parameters in the physics-based model for individual batteries. A model with the necessary physics and proper parameters can serve as a digital twin of a battery cell, which mirrors the battery cell's behaviour under different conditions. This digital twin can greatly support prognostics and diagnostics of batteries to enhance battery efficiency and lifespan.
As part of this project, the student will have the exciting opportunity to work with cutting-edge technology, playing a crucial role in developing micro-sensors and related models for a battery digital twin. They will be responsible for parameterising battery cells using battery testing data and designing a smart battery management system using a physics-based model and data-driven algorithm.
Objectives:
1. The student will optimise battery sensors and implement battery tests.
2. The student will analyse the battery data using physics-based models and AI algorithms.
3. 3The student will build a battery digital twin and optimise battery controls.
Requirements:
1. A bachelor's or master's degree in engineering science, control engineering, physics, robotics, AI or a related field.
2. Strong background in data analysis, algorithms or a related field.
3. Experience in computational modelling and data analysis.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Multiscale modelling of battery hysteresis from quantum level to device level (Starting from 2024 or 2025)
Supervisors
Dr. Guanchen Li (Guanchen.Li@glasgow.ac.uk)
Description
A battery's output voltage depends on the working current and operation history. This history-dependent behaviour of batteries is known as hysteresis. In almost all commercial batteries, hysteresis would unavoidably lead to energy inefficiency with heat dissipated and complicated thermal management. The hysteresis originates from the meta-stable phases of electrode materials, which strongly relates to the atomistic-level arrangement of lithium atoms in lattices. The physics of hysteresis still needs to be fully clarified, and an efficient model still needs to be included. Today's simulation for batteries with hysteresis needs extensive tests and heavy data analysis. A fundamental understanding of hysteresis and a light physics-based model will greatly support faster battery control and better energy efficiency.
In this project, the student will embark on a journey of innovation, implementing both quantum and continuum methods to develop a cross-scale model for battery hysteresis. The student will also have the opportunity to collaborate with experiments to develop new materials using AI-assisted material simulations, paving the way for exciting discoveries in the field.
Objectives:
1. The student will develop a quantum-continuum model for batteries.
2. The student will collect hysteresis data and validate the model.
3. The student will optimise battery controls using the new model.
Requirements:
1. A bachelor's or master's degree in computational material science, quantum physics, or a related field.
2. Strong background in materials science, solid-state physics or a related field.
Preferred skill:
1. Experience in simulating material structures using e.g., density-functional theory, molecular dynamics, or Monte Carlo simulations
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Efficient thermal energy storage system utilising novel biochar-based phase change materials and nanofluids/nanoparticles
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
Thermal energy storage system is used to store heat energy, to be flexibly utilised as and when required, for any heating/cooling applications and power generation. It could potentially be integrated with a renewable energy system to significantly improve the overall energy efficiency and, amongst the various methods proposed in the literature, the use of phase change materials (PCM) in combination with nanofluids/ nanoparticles seems to provide a unique solution with improved storage capacity. However, little is known to date on the thermo-physical behaviour of this concept – which is crucially important for the development of an efficient thermal energy storage system. The proposed project aims to address this through investigation of the core thermofluids physics, with an in-depth understanding of the heat and mass transfer processes of novel biochar+PCM and nanofluids, separately and also in combination, in a thermal storage system. The effects of various parametric alternations, which will arise from the system’s operating and boundary conditions as well as from the properties of new PCM and nanofluids, will be examined both numerically and experimentally, with the goal to discover the best possible conditions for thermal storage.
Nanofluids and bio-based phase change material nanocapsules for highly efficient conversion of sunlight to heat and thermal storage
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
Thermal energy storage system is used to store heat energy, to be flexibly utilised as and when required, for any heating/cooling applications and power generation. It could potentially be integrated with a renewable energy system to significantly improve the overall energy efficiency and, amongst the various methods proposed in the literature, the use of phase change materials (PCM) in combination with nanofluids/ nanoparticles seems to provide a unique solution with improved storage capacity. However, little is known to date on the thermo-physical behaviour of this concept – which is crucially important for the development of an efficient thermal energy storage system. The proposed project aims to address this through investigation of the core thermofluids physics, with an in-depth understanding of the heat and mass transfer processes of novel Nanofluids and bio-based phase change material nanocapsules in a thermal storage system. Optical characteristics and radiation when interacting with fluid are the key part of the research questions which will be examined both numerically and experimentally, with the goal to discover the best possible conditions for thermal storage.
Waste to Sustainable Aviation Fuel (SAF)
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
Explore the potential routes of organic waste, including sludges, to sustainable aviation fuels. Various thermochemical processes such as pyrolysis, gasification, hydrothermal liquefaction, and hydrothermal canonisation could be considered, and the research will identify the best possible routes for the production of either biosyngas and/or biofuel. This will then be used to derive the optimum pathways for SAF production. The research will be inherently based on thermochemical kinetics modelling, system/subsystem level integration for process optimisation, and the potential application of machine learning to improve the prediction capability of whole processes with techno-economics and life cycle potentials. The model will need to be validated through suitable experimental and other datasets.
Novel dynamic approach for tar/CO2 cracking in thermochemical process
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
The research project will begin with a literature survey to gain comprehensive understanding of the syngas process contamination within a thermochemical process of biomass/agi-based waste/municipal solid waste, and explore the opportunities of applications of novel catalysis/plasma methods to crack tar and other species such as CO2 to useable gases / solid biochar. Complex and highly nonlinear thermochemical kinetic mechanisms of the integrated processes including catalysis/plasma needs to be understood and developed based on the elemental/ultimate analysis data of feedstock to predict the process performances with an effect from a number of important operating and boundary conditions of the integrated system. Ultimate goal is also to identify the suitable conditions through a detailed sensitivity study of the process that leads to the optimum process performance consider a detailed techno-economic/life-cycle assessment. Energy/exergy efficiency of the whole integrated process will also be investigated, and the model will be validated and further characterised through suitable experimental data as well as through detailed reactor scale CFD (computational fluid dynamics) simulation.
Integrated Solar Thermal Energy and Storage
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
This research project involves numerical, computational (such as CFD) and experimental investigations of a solar integrated thermal energy system and its storage. The team has been working on the development of novel solutions for this application, such as the concept of hybrid phase change material (PCM) and nanofluids as well as biochar-based stable PCM. The study will focus on the investigation of applications of these hybrid materials with the aim of improving their robustness in solar as well as any low-thermal energy storage. Several specific objectives of the project include:
-Study and analyse the thermal characteristics of a combined hybrid PCM for solar application. It involves the preparation of the material, DSC experiments and thermal imaging.
-Numerical modelling for an in-depth investigation of charging and discharging behaviour and thermohydraulic characteristics under steady and dynamic conditions, considering the live metrological data in various selected zones in different parts of the world.
Super ultra-low NOx combustion of hydrogen/ammonia fuels for decarbonisation of heating/transport systems
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
A transition from carbon-based fuels to low-carbon/carbon-neutral alternatives such as hydrogen/ammonia/hydrogen-blend fuels has been identified as an important strategy for decarbonising the heating/transport sectors including aviation. However, when compared to any other hydrocarbon fuel, hydrogen/ammonia combustion in a typical system is significantly challenging, and is often affected by a number of factors such as flame destabilisation/instability, flammability limit, heat transfer characteristics. Another significant problem in a hydrogen based combustion system is NOx production, and while a lean mode operation is favourable, a conventional lean burner may be more susceptible to flame destabilisation. To address these challenges, this project aims to develop a next-generation efficient, low-cost and NOx-free combustion system for hydrogen/ ammonia-based fuels, taking into account the challenges of heat/transport (e.g. LGV/Marine/Aviation) decarbonisation. For the development of burner design and examination of its performance under various operating and fuel circumstances, the research methodology will integrate advanced numerical and CFD techniques. The ultimate goal is to find the best flame and burner configuration, providing the best performance while also maintaining a super ultra-low NOx target. The numerically predicted results will be validated through experimental data as well as other methods.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Hydrogen production from biomass and municipal solid waste – net-negative emission technology
Supervisors
Prof. Manosh C Paul (Manosh.Paul@glasgow.ac.uk)
Description
The UK Government's recent Ten Point Plan for a Green Industrial Revolution emphasised the critical importance of low/zero carbon hydrogen in achieving the "net-zero" emission target by 2050. However, this is significantly challenging when the global hydrogen production is mostly dependent on fossil fuels. There is a considerable potential to use municipal solid waste (MSW) and biomass waste as a fuel (renewable) resource to generate hydrogen, and when combined with CCUS (carbon capture, utilisation and storage), it has the potential to provide negative emissions. This research project aims to develop and implement novel technical approaches for producing net-negative emission hydrogen from MSW/biomass waste. The research methodology will integrate robust thermochemical kinetics with numerical and CFD (computational fluid dynamics) methodologies, all of which will be supported and confirmed by experiment.
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
The food-water-bioenergy nexus for remote villages: Design, economics, and environmental impacts
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Sustainable food, water, and energy supplies for remote villages remain a great challenge in some developing countries. The development of self-sustaining food, water, and energy systems serves as one of the promising solutions and is receiving an increasing attention in recent years. This project will be based on typical remote villages in several developing countries and aims to develop bespoke concepts of feed-water-bioenergy nexus according to the environmental and resource background of villages. Biochemical (e.g., anaerobic digestion and aerobic digestion) and thermochemical bioenergy technologies (e.g., pyrolysis and gasification) will be included in the system design. The nexus will be optimised using multi-objective methods such as large-scale mixed-integer linear and nonlinear programming. The economic and environmental feasibility of the nexus will be evaluated using cost-benefit analysis and life cycle assessment.
Comparison of centralized and decentralized bioenergy systems for municipal solid waste treatment: Economic, environmental, and social impacts
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Sustainable management of municipal solid waste (MSW) has become one of the major challenges for megacities. Gasification, anaerobic digestion, and pyrolysis serves as environmentally friendly bioenergy technologies for MSW treatment. It could convert carbonaceous MSW into valuable products such as biogas, bio-oil, synthesis gas, biochar, etc. Biogas, bio-oil and synthesis gas could be further converted into electricity and heat, while biochar has been recognized as an effective carbon abatement tool upon its application in soil. Decentralized energy supply has been regarded as an important component of future smart grid systems. However, decentralized energy production could be economically challenging considering the economy of scale. This project will compare the economic, environmental, and social performance of centralized and decentralized bioenergy systems in both developed and developing countries. Different system and supply chain configurations will be proposed, and a decision support tool will be used to make the comprehensive comparison from the perspectives of different types of stakeholders (i.e. policy makers, investors, and consumers).
Multi-scale modelling of hydrogen geological storage
Supervisor
Dr Yihuai Zhang
Description
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This PhD project presents an exciting opportunity to be at the forefront of research in sustainable energy. As the world transitions to greener energy solutions, hydrogen storage plays a pivotal role in this paradigm shift. This project, focusing on the multi-scale modelling of hydrogen geological storage, aims to develop innovative models that can accurately predict the behaviour of hydrogen in various geological formations. Objectives:
Requirements:
Opportunities:
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Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Next-Generation Digital Rock Physics
Supervisor
Dr Yihuai Zhang
Description
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We are excited to offer a PhD position in the groundbreaking field of Next Generation Digital Rock Physics. This project aims to revolutionise our understanding of rock properties and behaviours using advanced digital simulation techniques. The research will focus on developing and applying state-of-the-art digital models to analyse and predict rock physics phenomena, which are crucial for applications in geosciences, petroleum engineering, and environmental science. Objectives:
Requirements:
Opportunities:
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Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Investigate the Methodology and Mechanisms for Fast Mineral Trapping in Carbon Geosequestration
Supervisor
Dr Yihuai Zhang
Description
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Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Opportunities in gasification and combustion engineering
Supervisors
Dr Manosh C Paul
Dr Nader Karimi
Dr Siming You
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Production of carbon neutral fuels is an essential step in reducing carbon emissions to atmosphere and mitigation of the global warming. Gasification is a key technology in realising this ambition and is therefore under intensive development worldwide. The School of Engineering at the University of Glasgow has a strong track record in the field of gasification and combustion engineering, with a number of ongoing collaborative projects focusing on biomass, waste and underground coal gasification. Gasification, which is a partial oxidation process, usually takes place at temperature 450-1350°C with very little air or oxygen, by which carbonaceous sources of energy are converted to synthesis gas (syngas) which ideally should comprise a well combination of hydrogen (H2) and carbon monoxide (CO). However, currently there is a lack of clear understanding of the gasification thermochemical processes (such as drying, pyrolysis, combustion and reduction) which lead to the production of impurities and emissions. A key research question that will be addressed in this PhD project is how to get the gasification process robust enough, thus enabling to produce sufficiently clean syngas from various feedstocks. How to reduce/remove the tar formation? Also how to make it CO2 neutral/negative? These are the challenging questions to be addressed through the project. The student will contribute to the development of advanced thermochemical as well as computational fluid dynamics (CFD) based techniques to first understand the gasification processes and then investigate how to improve the processes through systematic parametric optimisations. Gasification experiment will be performed to validate the modelling results, and combustion performance of produced syngas will also be investigated for potential downstream applications leading to the efficient generation of combined heat and power.
The candidate should have a strong academic background in mechanical, chemical or aeronautical engineering, or applied physics and mathematics. For further information please contact Dr Manosh Paul (Manosh.Paul@glasgow.ac.uk).
Performance improvement of thermal energy systems
Supervisors
Dr Manosh C Paul
Dr Nader Karimi
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Flow transition with thermal energy transport is a common phenomenon which occurs in almost every energy engineering system e.g. in cooling electronic devices, heat exchangers, solar thermal energy, nuclear reactor, thermal energy storage, and so on. This may occur in different flow conditions e.g. laminar, turbulent, with/without influence of any external effects such as the gravitational force. Understanding the transportation process of heat and mass energy is thus crucially important for improving the performance of any thermal engineering systems. This proposed PhD project aims to study the various flow phenomena which may be complex at some conditions/applications due to the interaction between the system’s operation and energy transportation. The research will therefore initially focus on the development of highly advanced computational fluid dynamics (CFD) based numerical methods with the aim to investigate those complex phenomena. Most recently in-house developed advanced large eddy simulation (LES) and direct numerical simulation (DNS) codes will be extended further, thus allowing investigation of the fundamental aspects of the problem associated with the fluid mechanics and heat transfer. The research may also be extended further by utilising an alternative fluid such as nanofluid to investigate the performance against a base fluid (e.g. air, water). This will further involve the study of multi-phase flow with an effect of a combination of the various fluid conditions such as particle size and concentration of nanofluid. A possible extension of the study will be the investigation of phase change martial/heat pipe technology for efficient heat energy storage application – one of the key energy strategies for the UK Government.
The candidate should have a strong academic background in mechanical, chemical or aeronautical engineering, or applied physics and applied mathematics. For further information please contact Dr Manosh Paul (Manosh.Paul@glasgow.ac.uk).
Thermochemical extraction of high value products from biomass
Supervisors
Dr Ian Watson
Dr Julian Dow
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Biomass and waste feedstocks represents a significant opportunity to produce sustainable sources of energy whilst extracting valuable platform chemicals using biorefinery concepts. The work will undertake novel approaches to extract liquid biooils using a range of thermochemical based processes and investigate applications that optimise the end energy and product yield. Thermochemical treatments include: torrefaction, pyrolysis and gasification. Process modelling will be done to determine the impact of feedstock and process treatment on the end product and will be supported by experimental work to identify novel applications of extracts.
Materials and Manufacturing
Architected Carbon-Based Electrodes Derived from 3D Printing for Supercapacitor Applications
Supervisors
Dr. Jun Young Cheong (JunYoung.Cheong@glasgow.ac.uk)
Prof. Shanmugam Kumar (Msv.Kumar@glasgow.ac.uk)
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Additive Manufacturing, commonly known as 3D Printing, is emerging as a highly promising and scalable technology for fabricating intricate 3D porous architectures. These structures have a wide range of applications due to their tuneable surface area density and mechanical/functional attributes. While significant research has explored the use of 3D cellular structures in fields such as drug delivery and actuators, there remains a gap in understanding the structure-processing-property-performance relationships of 3D-printed architected electrodes, particularly after they undergo heat treatment processes like pyrolysis and calcination.
This project aims to investigate the electrochemical performance and properties of carbon-based electrodes derived from 3D printing, followed by subsequent heat treatment. The study will focus on the mechanical and morphological properties required for these electrodes to function as free-standing components. Additionally, the project will evaluate the capacitance retention and performance at various scan rates (current densities) in both conventional asymmetric and symmetric supercapacitor systems, assessing their feasibility for supercapacitor applications.
This research offers a unique opportunity for the candidate to gain expertise in materials design and innovation, as well as in the electrochemistry of advanced energy storage systems.
Mechanical assessment of the NASICON-based solid electrolyte for Li-based solid-state batteries
Supervisors
Dr. Jun Young Cheong (JunYoung.Cheong@glasgow.ac.uk)
Prof. Mohammad Khalid (Mohammad.Khalid@glasgow.ac.uk)
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
As the flammeability of lithium-ion batteries hinder their application for the practical utilisation, much research has taken place for the replacement of lithium-ion batteries with the next-generation solid state batteries. One key factor to consider is the sustainable development of the solid electrolyte. Na Super Ionic Conductor (NASICON) is one of the most promising solid electrolyte candidates for Li metal batteries, attributed to its suitable ionic conductivity. Nevertheless, mechanical properties of NASICON and their relation to the electrochemical performance still have much room for further improvement.
The project aims to further our understanding of the structure-property relationship by examining the NASICON-type solid electrolyte for solid state batteries. Especially, the calendaring step optimisation is necessary to realise the suitable contact between the electrode and electrolyte, which will be the key aspect of the study. Mechanical properties of the pristine NASICON solid electrolyte and its contact feasibility with the electrode will be investigated in light of electrochemical performance and properties. It includes the optimal point of contact between the NASICON solid electrolyte and anode/cathode, which can lead to stable operation for a long term and at various temperatures.
Multi-objective optimisation methods for minimising tardiness, electricity consumption and cost in dynamic job shops
Supervisors
Dr Ying Liu
Prof Yun Li
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirements to reduce their emissions. Most reported work on reducing manufacturing energy consumption focuses on the need to improve the efficiency of resources (machines).The potential for energy reducing at the system-level has been largely ignored. At this level, operational research methods can be employed as the energy saving approach.
Job shops are widely used in the manufacturing industry, especially in small and medium enterprises. In the future, the uncertainty within the system will be increased as the result of mass customisation and personalisation. Optimisation techniques to solve the uncertainties and maintain the robustness of the manufacturing system will become increasingly important.
Reducing the electricity consumption in a dynamic job shop will be studied in this research. Existing dynamic scheduling algorithms will be extended to reduce the electricity consumption and improve productivity for job shops where the components arrive at the production system at randomly distributed times. This will extend the applicable range of the developed multi-objective optimisation methodology to include stochastic manufacturing systems which are widely used in the real manufacturing world.
Thus, in this project, meta-heuristics based optimisation approaches which include electricity consumption as an objective to minimise when uncertainties such as machine breakdown occur in the production system at randomly distributed times will be developed. Reinforcement learning will be used to identify the pattern of uncertainties in the manufacturing system.
Artificial Intelligence based multi-objective optimisation dispatching rules for energy management in flexible manufacturing systems
Supervisors
Dr Ying Liu
Prof Yun Li
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Energy is one of the most vital resources for manufacturing. In the last 50 years, the consumption of energy by the industrial sector has more than doubled and industry currently consumes about half of the world’s energy.
Flexible job shops are widely used in the manufacturing industry, especially in small and medium enterprises. For instance, original equipment manufacturers in the aerospace industry usually employ the flexible job shop manufacturing system for their capability to satisfy the increasingly diversified customer demands. In the future, the requirement on the system flexibility will be increased to adapt mass customisation and personalisation. On-line decision making for the flexible manufacturing system will become increasingly important.
The main goal of this project is to address the multi-objective flexible job shop scheduling problems with reducing energy consumption and its related cost as part of the objectives. Electricity consumption and electricity cost reduction have not been well investigated in the multi-objective scheduling approaches for a typical flexible job shop manufacturing system. The lack of a more fundamental energy saving oriented flexible job-shop model and its related scheduling techniques is a significant gap in the current research which needs to be addressed.
A dispatching rule is a rule that prioritises all the jobs that are waiting for processing on a machine, which is widely used in the manufacturing system for decision support, especially for the on-line environment. The prioritisation scheme may take into account the job’s attributes, the machines’ attributes as well as the current time. Compared to exact algorithms and meta-heuristics, dispatching rules are easy to implement and fast to calculate, and can be used in real time to schedule jobs. In other words, dispatching rules usually can deliver reasonably good solutions in a relatively short time.
Thus, in this project, dispatching rules which include electricity consumption as an objective to minimise when jobs arrive at the flexible production system at randomly distributed times will be developed. Techniques like genetic programming will be used to construct the composite dispatching rules. Reinforcement learning will be used to identify the electricity consumption pattern of assets in the manufacturing system.
Manufacturing and properties of titanium porous structures
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Open-cell titanium alloy porous structures (foams) are attractive materials for applications such as sound damping, heat exchange, impact energy dissipation and tissue engineering. The structures with periodic unit cells can be manufactured via additive manufacturing (3D printing) such as selective laser melting (SLM). The combined slurry coating and powder metallurgy approach can produce porous structures with irregular unit cell topologies. It has been a challenge to select the appropriate manufacturing route for titanium porous structures as different routes lead to dissimilar final properties.
This project aims to comparatively evaluate the properties of titanium porous structures fabricated by the different manufacturing processes. Research will focus on both additive manufacturing for periodic unit cell topologies and slurry coating with powder metallurgy for irregular topologies. Mechanical, thermal, and/or acoustic properties of porous structures will be quantitatively characterised and compared. In particular, the effect of processing parameters will be investigated to improve the manufacturing processes. Numerical simulation such as FE, CFD will also be used to explore the properties of titanium porous structures.
Deformation and failure micromechanisms in additive manufactured (3D printed) metals
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Additive manufacturing (3D printing) of metals is one of the significant research focuses in the Materials and Manufacturing Group. Selective laser melting (SLM) has been successfully used to manufacture lightweight metallic structures with complex geometries, such as microlattice structures, which can potentially be used in aerospace components and biomedical implants. Despite the numerous investigations on bulk mechanical properties of SLM metals, there is a scarcity of research on the underlying deformation and failure micromechanisms that determine the bulk behaviour.
This project aims to investigate the underlying micromechanisms on the deformation and failure process of metals (e.g., titanium alloy, aluminium alloy and stainless steel) made by the SLM technique using advanced experimental characterisation approaches such as in-situ SEM. Research will focus on how the microstructure and micro-texture in SLM metals in very small length scales affect the micromechanisms on both the elastic and plastic deformation behaviour. The constitutive behaviour for SLM metals will also be formulated for FE modelling of SLM components to predict their service performance.
Thermoforming of advanced thermoplastic composites
Supervisor
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Advanced composites are attracting a huge amount of interest in the automotive sector where government legislation on emissions means that light-weighting is now a primary driver in the design process. Due to their enhanced damage tolerance, fast production times and potential recyclability, advanced thermoplastic composites are of particular interest. However, current computer aided manufacture modelling tools for these materials are inaccurate and the lab time required to characterise their forming behaviour for input into computer simulations is prohibitive. The goal of this project will be to predict the comprehensive forming mechanics of advanced thermoplastic composites directly from the matrix rheology and fibre volume fraction of the composite, a capability that will lead to significant reductions in design and manufacture costs, facilitating the wider use of advanced thermoplastic composites in the automotive sector and ultimately contributing to a greener economy. With the skills and experience gained during the project, can expect excellent employment opportunities in both the aero and automotive sectors.
Virtual manufacture with advanced carbon composites: from manufacture to structural optimisation
Supervisor
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Composite materials are an exciting and fast-moving research topic. Developments in this area are driving economic growth and transforming society in a number of fundamental ways; from the reduction of carbon emissions through light-weighting, to the development of multi-functional smart composites that can self-sense and self-heal damage for low-cost in-service maintenance. This project will focus one of the most promising fully-automated low cost manufacture techniques in manufacturing advanced composites, namely, sheet thermoforming. For the PhD student, the crux of the project will be to develop a mapping interface allowing fibre angle predictions following sheet forming to be fed into subsequent mechanical simulations for structural analysis and for the prediction of warpage due to thermally generated residual stresses. The student will gain expertise in composite manufacturing, computational modelling and material characterisation. Computational modelling will involve FEA and coding in Matlab and python. Once the mapping algorithm is implemented, genetic algorithms will be used to optimise structural performance (minimise mass) and control warpage. With the skills and experience gained during the project, can expect excellent employment opportunities in both the aero and automotive sectors.
Machine Learning for Digital Manufacturing
Supervisors
Funding
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The studentship is supported by the Apollo Tyres Ltd, and it will cover overseas tuition fees and provide a stipend at the UKRI rate for 3.5 years (est. £16,062 for session 2022/23).
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Description
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The James Watt School of Engineering of the University of Glasgow is seeking a highly motivated graduate to undertake an exciting 3.5-year PhD project entitled ‘Machine Leaning for Digital Manufacturing’ within the Systems, Power and Energy Division. Increasing demand for the development of high-performance tyres with complex designs has spurred a revolution in their manufacture and design. However, challenges still exist in the processing of these tyres concerning quality attributes, rework reduction and cured tyre scrap reduction. These inherent challenges can be avoided by implementing algorithms to detect defects and modulate process parameters in real time. In this proposed research, several algorithms, with a focus on machine learning methods, will be explored to systematically tackle the three main stages of the manufacturing process: material design, process parameter configuration, and in situ anomaly detection. The successful candidates will have background in data science, machine learning, artificial intelligence, and their applications for advanced manufacturing systems. Candidates must possess an MS/MEng degree in materials science or engineering, mechanical engineering, polymer science and engineering, chemical engineering or a closely related discipline, and demonstrate documented potential for outstanding research. We seek applicants who are well-versed in the mathematical, statistical, and algorithmic foundations of artificial intelligence (AI) and have interest and experience in applying machine learning to problems of modelling, design, optimization and discovery of engineered products, materials and systems. To effectively engage with the advanced materials and 3D printing lab at Glasgow, experience and/or background in manufacturing (including 3D printing), characterization, modelling, design and testing of composite materials is desired. Apollo Tyres Ltd is an international tyre manufacturer and the leading tyre brand in India. The company has a total of 7 manufacturing units in India, Hungary and The Netherlands. The company markets its products under its two global brands – Apollo and Vredestein, and its products are available in over 100 countries through a vast network of branded, exclusive and multi-product outlets. This is a great opportunity to partner with one of the most exciting companies in the tyre manufacturing industry and work with leading professionals and world-class manufacturing facilities, production lines, research & development centres and supply chain centres. The students will have access to Apollo Tyres global manufacturing infrastructure, data and Apollo employees. Student, in addition to working under the supervision of academic supervisor at the University of Glasgow, will collaborate with a company supervisor, who will mentor and support data gathering and research hypothesis. All business-related expenses and required equipment will be supported by the company. Please note that this application is to gain admission to our PGR programme, and an offer of admission may be issued before a decision on this Scholarship is made. Candidates applying for this Scholarship will most likely have an interview/discussion with the supervisor before any decision is made. How to Apply: Please refer to the following website for details on how to apply: http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/. |
Data-Driven Digital Twins for Smart Manufacturing
Supervisors
Funding
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The studentship is supported by the Apollo Tyres Ltd, and it will cover overseas tuition fees and provide a stipend at the UKRI rate for 3.5 years (est. £16,062 for session 2022/23).
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Description
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Increasing demand for the development of high-performance tyres with complex designs has spurred a revolution in their manufacture and design. However, challenges still exist in the processing of these tyres concerning quality management, process optimization, energy consumption, asset maintenance, product design, rework reduction, cured tyre scrap reduction and supply chain management. These challenges can be overcome by focusing on digitization while making use of the availability of new data streams, both experimental and model-based, as well as their processing via digital twins. Specifically, in this project, with an objective of enhancing productivity, digital twins will be developed to optimize processes, design high performance products, and enable production of quality products, while monitoring the individual components of the production line. The integration of digital twins in tyre manufacturing will improve productivity and reduce costs. Our primary focus will be on the extruder. The project aims to develop digital twin initially for an extruder and then extent it to multiple extruders, exploring process optimization, predictive maintenance and quality attributes. The successful candidate will have particular interest in engineering applications of artificial intelligence in the field of polymer engineering & composites, applications of machine learning, usage of big data, the IoT, and the implementation of an Industry 4.0 approach in manufacturing industries. Candidates must possess an MS/MEng degree in materials science or engineering, mechanical engineering, polymer science and engineering, chemical engineering or a closely related discipline, and demonstrate documented potential for outstanding research in digital driven manufacturing processes and digitalization in product development. To effectively engage with the advanced materials and 3D printing lab at Glasgow, experience and/or background in manufacturing (including 3D printing), characterization, modelling, design and testing of composite materials is desired. Apollo Tyres Ltd is an international tyre manufacturer and the leading tyre brand in India. The company has a total of 7 manufacturing units in India, Hungary and The Netherlands. The company markets its products under its two global brands – Apollo and Vredestein, and its products are available in over 100 countries through a vast network of branded, exclusive and multi-product outlets.
This is a great opportunity to partner with one of the most exciting companies in the tyre manufacturing industry and work with leading professionals and world-class manufacturing facilities, production lines, research & development centres and supply chain centres. The students will have access to Apollo Tyres global manufacturing infrastructure, data and Apollo employees. Student, in addition to working under the supervision of academic supervisor at the University of Glasgow, will collaborate with a company supervisor, who will mentor and support data gathering and research hypothesis. All business-related expenses and required equipment will be supported by the company. How to Apply: Please refer to the following website for details on how to apply: http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/. |