Possible research topics to be undertaken in the Infrastructure & Environmet Division of the 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.
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, Prof. William Sloan (William.Sloan@glasgow.ac.uk), who will direct you towards a prospective supervisor with expertise in that area.
Stability of sediment patches in bedrock rivers
Dr Manousos Valyrakis and Porf T. Hoey
Bedrock river channels contain sediment that is transported efficiently. However, significant volumes of sediment are found in bedrock channels mostly located in patches that tend to be long-lived, particularly where their positions are morphologically-controlled. Previous experiments on plane beds have demonstrated that patch size and stability are consequent on feedbacks between patch morphology, flow hydraulics and sediment transport. However, the dynamical processes involved are yet not well understood and the bedload prediction formulas are highly empirical and with relatively poor performance. This project will extend the plane-bed work to: a) incorporate novel flume experiments with realistic bed geometries and mixed grain sizes, b) investigate the role of flow turbulence on the evolution and stability of sediment patches and c) propose a physically based predictive model for transport of sediment in bedrock channels. The aim is to use a series of carefully designed Froude-scaled experiments to measure how bed topography controls the locations and volumes of both erosion and sediment deposition, during high flow events. The experiments will be conducted in a 0.9m tilting recirculating flume at the University of Glasgow, and will use novel non-intrusive experimental equipment, namely acoustic Doppler velocimetry (ADV) and particle image velocimetry (PIV), to study feedback mechanisms between the flow and the development or disintegration of sediment patches. These measurements will be complemented with synchronously acquired high-speed photography and video imaging which will be analysed for tracking the paths of individual grains responsible for generating the formation or triggering the break-up of sediment clusters. The experimental design will use existing field data, supplemented by additional data collected for this project including laser-scanned images of river beds that will be down-scaled and 3-D printed for use in the laboratory. These experiments will aid expanding and further develop general understanding of the mechanisms of patch formation and erosion.
Investigating the effect of energetic turbulent flow structures on the transport of bed material resting on a river-bed surface
Shedding light to the dynamics of transport processes of solid particles due to the action of geophysical flows, occurring in estuarine, aeolian and other natural environments, remains one of the fundamental problems in earth-surface research, for more than half a century. Incipient motion research refers to the study of the flow conditions describing the initial stages at which the transport of solids or sediment transport begins. It finds application in a wide variety of fields ranging from hydraulic engineering, when the focus is on bridge scour protection and river bed and bank stabilization, to environmental and biological systems engineering, when dealing with river restoration, protection of fish habitat, transport of contaminated sediments and estimation of flushing flow conditions downstream of a reservoir. Traditionally, engineering practitioners and hydraulic researchers alike have employed spatially and temporally averaged criteria, such as Shields’ critical shear stress, for the identification of incipient motion of coarse bed surface material. Other researchers have recognized the role of fluctuations of the near bed turbulence and the variability of the particle characteristics and micro-particle arrangements. In addition to the significance of peaking instantaneous stresses for conditions near the threshold of motion the role of their duration has been more recently emphasized (Figure 1b and 1c). These approaches considered the role of the time integral of hydrodynamic forces, or power, above a certain threshold applied on a particle. These have been formulated into an impulse (Diplas et al. 2008) or energy criterion (Valyrakis et al. 2013) for particle-scale transport.
Constitutive modelling of the time effects on mechanical behaviour of sand
Dr Zhiwei Gao
The mechanical behaviour of sand is time-dependent. Time effects in granular materials comprise rate effects and aging effects. Rate effects include rate dependent stress-strain relation, creep (time-delayed accumulation of strain at constant stress) and stress relaxation (stress change at constant strain). The aging effects, which are used to describe changes in engineering properties (e.g., stiffness and stress-strain relation) of sand with time, could be attributable to changes in internal structure of sand associated with static fatigue at particle contacts, contact force homogenization, formation of interlocking or cementing agents and/or time-delayed particle movement. These time effects has significant influence on practical geotechnical design. For instance, long term observations showed that sand creep can induce large settlement of foundations built on sand. The settlement after construction may reach 35% of the total one. Neglecting such settlement can result in dangerous designs. Consideration of aging effects on mechanical properties of sand can lead to safer and more cost-efficient design. Abundant experimental and field tests indicate that the bearing capacity of driven piles in sand increase with time, which is known as pile setup. In some cases, the increase can reach 100% in just 3 months. This is attributable to sand aging. This project aims to develop a comprehensive constitutive model to describe time effects on mechanical behaviour of sand. The main objectives are:
(a) Development of an elasto-visco-plastic constitutive model for describing the time effects on mechanical behaviour of sand. Since the time effects on mechanical behaviour of sand cannot be described by a conventional rate-dependent model which assumes that all the time effects are due to time-delayed accumulation of strain, distinction between the rate and aging effects will be made in the proposed model.
(b) After the model is developed, it will be implemented in the finite element package Abaqus to solve practical boundary value problems associated with time-dependent mechanical behaviour of sand. Examples are back analysis on increase of bearing capacity of driven piles with time, increase of liquefaction resistance of sand with time and long term deformation of sand embankments/dams.
A method for predicting rock fall in 3D
Dr Zhiwei Gao
Rock fall is a type of landslide consisting of detachment, fall, rolling, and bouncing of rock fragments. Increasing occurrence of weather events have caused more and more rock fall hazards in both the UK and the world. Catch fence systems consisting of wire meshes, cables and supporting posts are frequently used to control rock fall and debris flow from unstable rock and soil slopes along railways and roads. These systems have been found effective and cost-efficient and there is increasing use of them. For instance, the Network Rail will invest over £5 million on installation of rock catch fences in the coming five years. To date, however, these systems have been designed primarily by empirical methods, engineering judgment, field tests and experience. Recently, geotechnical specialists and some contractors have found that certain system elements may be over-designed. Meanwhile, some systems have failed under various impact conditions, indicating that the system were not properly designed for their desired applications. One of the major reasons for the inappropriate designs is that the potential rock fall trajectory and energy were not properly estimated. Though some 2D methods have been developed for rock fall prediction, there is limit success in 3D prediction. The 2D methods are not sufficient for a real catch fence design in which the rock fall will definitely not occur in a 2D plane. This project aims to develop a method for prediction rock fall in 3D. The major objectives are:
(a) Development of a method for predicting rock fall in 3D. Randomness is one of the main characteristics of rock fall, and therefore, a statistic approach will be used to develop the method.
(b) Small scale model tests will be carried out to study the rock fall in a real site. The tests will be recorded by high speed camera.
(c) Application of the prediction method. The method will be used to predict the rock fall observed in both model tests and full scale tests.
(d) Knowledge transfer of the project. The knowledge generated in this project will be transferred to industry to improve the current design of rock catch fences.
3D Printable Granular Materials
Dr Zhiwei Gao
Granular materials are ubiquitous and vital for our everyday life. They are seen in the form of both natural and engineering materials, such as sand, sugar, food grains and powders in agricultural, pharmaceutical, energy and chemical industries. Granular materials are the second-most manipulated material in industry next to water. Sand is a typical example of granular media, and is important to a wide range of key infrastructures pertaining to the quality and safety of our daily life and the economy of many countries around the world including the UK. Many new infrastructures, such as wind turbines, high-speed railways, tunnels, pipelines and earth dams which are lifelines to the economy of the UK, will be built on/in sand. The mechanical behaviour of sand underpins the critical performance and serviceability of these structures and is a key factor to be considered in their design, construction, operation and maintenance. Until now, many aspects of the mechanical behaviour of granular materials remain mystery to Human. The particle shape is the major factor which controls the mechanical behaviour of sand, including the stiffness, shear strength and volumetric change in shear. This project aims to use 3D printing to create particles with different morphology and use them in experimental tests. The major objectives of this project are:
(a) Development of a numerical scheme for generating 3D granular particles with desired morphology;
(b) 3D printing of the granular particles;
(c) Use of the particles in triaxial compression tests to study the effect of particle shape on mechanical behaviour of granular materials.
A stable multi-physics modelling framework for the Finite Element analysis of materials and structures
Prof Chris Pearce and Dr Lukasz Kaczmarczyk
Multi-physics is one of the predominant research challenges dominating international research efforts in computational mechanics. A computationally tractable solution of strongly coupled physical systems requires the simultaneous solution of multiple fields and the interactions of these fields. Such problems frequently suffer from solution instability, resulting in non-physical and spurious results.
The project will investigate novel techniques that have the potential of guaranteeing stability for any choice of approximation space. The successful implementation, testing and demonstration of this investigation will be a major advance in the field of computational mechanics for achieving solution stability for multi-physics problems.
The project will also consider the application of this framework to materials and structures exposed to elevated temperatures, investigating the interaction between the mechanical, thermal and moisture response. The project will either consider either (a) materials and structures relevant to the nuclear industry, e.g. concrete, graphite, steel, possibly including fracture propagation, or (b) biological materials, depending on the background and interest of the research student.
This fundamental research will be implemented in our group’s FEA software (MoFEM), utilising the latest advances in scientific computing to enable the development of scalable algorithms to maximise efficient use of computer architectures.
Integrated Life Cycle Analysis Techniques to Advance Zero Carbon and Zero Waste Delivery within Smart, Public Buildings (Smart LCA 4 Zero)
The European construction sector is currently responsible for over 40% of total European energy consumption and one third of CO2 emissions and in the UK, the statistics are even higher with the Built Environment accounting for almost 50% of the UK energy requirement. In order, to reduce these figures, the European Union passed the Energy Performance of Buildings Directive in 2002 and has updated it several times since and the UK & Scottish governments have additionally passed their own legislation to promote a reduction in energy consumption within the Built Environment.
Within this context, the “Smart LCA 4 Zero” PhD research project will examine and analyse energy performance within contemporary buildings by taking a holistic, whole life cycle approach. The PhD project will develop an innovative, “user friendly”, Life Cycle Analysis technique which will be designed to dovetail into existing Building Information Management (BIM) and Life Cycle Analysis (LCA) Tools with the overarching aim of advancing the progression towards the delivery of zero carbon and zero waste construction within Public Buildings in the UK and Europe. The project will examine and analyse every stage in the procurement of a number of exemplar “low energy” buildings starting from the design stage, through to material specification and delivery, construction, performance in use and at the end of its design life - re-use or recycling proposals. The Innovative LCA Methodology developed will be tested, refined and validated through the use of extensive modelling and analysis of “real life” data from a number of carefully selected public building projects, each of which will have been designed to very high standards of energy performance and sustainable design criteria. The procurement, delivery and operation of these buildings will be analysed in depth to inform the LCA, but also evaluate the effect of any “smart” technologies and their impact on zero carbon and zero waste targets. This project has significant impact potential in that it will provide valuable whole life cycle information which will support decision making by clients and design teams wishing to understand the broad environmental impact of the new generation of “zero carbon” public buildings during their entire life span; particularly with regards to meeting UK and European climate change targets and regulations.
Geotechnical design optimization for minimum energy/carbon
Prof Simon Wheeler
The use of state of the art optimization techniques in geotechnical design has the potential to generate significant benefits in minimising energy and carbon usage in geotechnical construction. However to date this potential has not been fully exploited. This project will draw on the latest research undertaken in the TERRE consortium on quantifying carbon footprints of civil infrastructure and low carbon technologies with the aim of incorporating it into an optimization based design tool. The research will build on the established optimization based software that is able to rapidly analyse the ultimate limit state for geotechnical constructions of any geometry using computational limit analysis.
The project is a fully funded ‘industrial’ PhD based with the industrial partner (24 months) and the University of Glasgow (12 months) who will award the PhD. At present, engineers can use the industrial partner’s software to manually optimise a specific design; however this `optimisation’ is largely down to the engineer’s judgement. This project will work to: (a) examine novel approaches that can automate the optimisation process based on defined criteria, (b) provide a measure of cost/energy/carbon to be used for the optimisation goals, and (c) incorporate the effects of soil suction and vegetation into the analysis. The latter aim will involve close collaboration with a parallel TERRE project that aims to incorporate the effects of soil suction and suction control into the analysis.
The PhD will suit candidates with a strong mathematical and programming ability and provides an excellent opportunity to research cutting edge optimization techniques in the context of low carbon engineering.
The studentship is supported by an EU Marie Sklowdowska-Curie Fellowship via the School and industrial partner LimitState Ltd., and it will cover home/EU tuition fees along with providing a salary for 3 years.
To be eligible for this funding, applicants must be early stage researchers within the first 4 years of their research, that is from the date they gained the degree that entitles them to embark on PhD.
Applicants should not have resided within the UK for more than 12 months in the last 3 year period, excluding holidays.
Suction-enhanced geotechnical design through interface properties
Prof Simon Wheeler
Unsaturated soils feature significantly in geotechnical construction and yet most geotechnical design assumes either fully dry or fully saturated conditions. Harnessing soil suction as an engineering tool can lead to potentially significant design gains since suction can impart substantial strength gains to soils. This project aims to investigate the use of physical interfaces or surface layers that inhibit liquid transfer but allow vapour transfer (analogous to breathable waterproof fabrics) thereby increasing suction in the ground in the long-term and reducing the risk of full saturation. The project is a fully funded ‘industrial’ PhD based at the University of Glasgow (24 months) and industrial partner (12 months). One-dimensional experimental tests and numerical modelling will be carried out at Glasgow to investigate the performance of different sandwiched interfaces to enhance evaporation and hamper rainwater infiltration while work with the industrial partner will seek to examine the practical implications of suction-enhanced design on the design of a range of geotechnical constructions through modelling suction and control interfaces in the commercial geotechnical analysis package. The project will also involve interaction with an industrial mentor through investigation of the potential application of suction control to specific case studies including stabilisation of cut slopes and excavations.
The studentship is supported by an EU Marie Sklowdowska-Curie Fellowship via the School and industrial partner LimitState Ltd., and it will cover home/EU tuition fees along with providing a salary for 3 years. To be eligible for this funding, applicants must be early stage researchers within the first 4 years of their research, that is from the date they gained the degree that entitles them to embark on PhD. Applicants should not have resided within the UK for more than 12 months in the last 3 year period, excluding holidays.
Design of a Whole Cell Biosensor for Bioavailability of Benzo(a)pyrene
Dr Caroline Gauchotte-Lindsay, William Sloan
The reclamation of contaminated land starts with efficient risk assessment that not only enables to assess the human and ecotoxicity of a site but also to determine the best remediation strategies. Polycyclic aromatic hydrocarbons (PAHs) are recognised persistent organic pollutants. They are present in crude oil and are produced during the combustion of coal and organic matter and are therefore ubiquitous soil contaminants. A few PAHs, such as benzo(a)pyrene (BaP), are recognized carcinogenic or mutagenic compounds and are currently on priority pollutant lists. BaP is the PAH of greatest interest to regulators who are primarily concerned with the bioavailable amount as it represents both the proportion that is toxic to living organisms but also determines the potential for bioremediation. The goal of the studentship is to build a synthetic organism that is tuned to specifically detect BaP and send a measurable signal to quantify its bioavailability in contaminated soils. A limited number of naturally-occurring micro-organisms have been identified as specific and efficient degraders of BaP and usually within a laboratory setting. However, in natural environments, BaP degraders also degrade other PAHs and indeed any available carbon source. Hence it is essential to characterize (1) whole –organism sensitivity to BaP and (2) pathways of metabolic priorities when the microbe is presented with a mixed carbon source. Our preliminary results, using an enrichment of a BaP degrader, N. pentaromativorans, have shown that in a mixed carbon source, although BaP was not the primary carbon source, growth was dependent on its concentration. In the first stage of this project, the student will identify the steps of the bacterial metabolic pathways that might be the most specific to BaP degradation using approaches such as metabolomics, real-time PCR. The response of these pathways to the presence of other high molecular weight PAHs will also be investigated. Then, N. pentaromativorans will be genetically modified with a luminescent reporter gene with expression dependence on the identified genes and bioluminescence responses in mixed carbon sources will be calibrated in water. The second part of the PhD will explore the appropriateness of the bioreporter for soil analysis. On one hand, because N. pentaromativorans was isolated from coastal sediments, the student will study its growth in soils (both clean and PAH contaminated) and its survival in the soil community using real time PCR and 16S rRNA sequencing. On the other hand, because fluorescence and luminescence are difficult to accurately measure in soils, novel reporter genes with non-optical signal such as the production of biomagnetite will be investigated.
Engineering energy saving water and wastewater treatment systems by guided evolution of microbial communities
Dr Stephanie Connelly and Prof William Sloan
It is estimated that as many as 2.4 billion people, more than 1 in 3 of the global population, live without access to improved sanitation and that as much as 80% of wastewater generated worldwide is released to the environment untreated. As the world population continues to grow and traditional energy and water supplies diminish, engineering new low-cost, low-energy water and wastewater treatment systems is one of the biggest challenges facing engineers today. Biological treatment processes present an attractive alternative to conventional chemical and energy intensive treatments. Indeed biological systems are currently employed across the UK and Europe for the treatment of a growing range of wastewaters. Yet, our capacity to improve energy efficiency in biological processes, and to adapt them to provide new design solutions to what is a rapidly growing problem, is hindered bylack of understanding of the complex mixed microbial communities that underpin the treatment process in these systems. Recent advances in molecular microbiology such as next generation DNA sequencing are enabling engineers and biologists to look into the mixed microbial communities in our engineered systems in detail for the first time. As such we have an opportunity to monitor, to understand, and ultimately to engineer microbial populations that work for us to achieve much needed low-cost, low-energy solutions to the water and sanitation crisis. This project aims to apply a machine learning approach to guide evolution of mixed microbial communities towards a high metabolic state whilst exhibiting minimal growth. To achieve this, we will couple cutting edge molecular biology methods and bioinformatics for microbial communitycharacterisation with mathematical modelling of mass and energy balance of microbial community metabolism. Bynaturethis work requires a multidisciplinary approach. As such, the successful applicant will be supported by supervision across the fields of civil and environmental engineering, microbial ecology and mathematical modelling. Further, hands-on training will be provided as appropriate to ensure the skills base required complements the needs of the project. The project will be based in one of the UKs best laboratory facilities for engineering biotechnologies for water and wastewater treatment, which is home to a vibrant, diverse, and supportive research team. We would encourage application from (but not restricted to) those with backgrounds in Civil / Environmental Engineering, microbiology, bioinformatics or mathematical modelling who would be willing to learn and grow in this exciting environment.
Enhancing micro-pollutant removal from drinking water by biological design
Caroline Gauchotte-Lindsay and Prof William Sloan
The release in natural waters of biologically active contaminants is a serious concern at a time when ever-increasing demand threatens water security. While many of these xenobiotic compounds have recognised ecotoxicological effects, there is a growing concern on their human toxicity too.Increasing ubiquity of micro-pollutants in natural waters opens the possibility of their presence in drinking water. Conventional drinking water treatments aim to remove pathogens, reduce turbidity and control odour and taste and the employed engineering processes reduce somewhat the load of micro-pollutants. Complete removal, however, involves high chemicals and energy demand technologies and therefore, in the current state of knowledge, their potential benefits are not worth the environmental expenditure. We are currently developing a high-science low-tech approach to intensify and control decentralised biofiltration of drinking water with Scottish Water. Treatment biotechnologies remove pathogens, nutrients and transition metals through a mixture of physical and biological processes. For instance, ammoniaoxidizing bacteria (AOB) andammoniaoxidizingarchea (AOA) carry outtransformation of ammonia via their ammonia monooxygenase (AMO) enzyme. Importantly, the AMO enzyme has broad substrate specificities and can also oxidise co-metabolically a wide range of contaminants. This property opens the possibility that the ammonia oxidising community of biological treatments can be optimised to efficiently remove both nutrients andmicro-pollutants. The aim of this project is to identify key nitrifying microbial communities and conditions to design aninncoulumfor biological filters for untargeted biotransformation of contaminants alongside ammonia removal. The student will initially run microcosms from various environments including coastal and river sediments, nitrifying activated sludge and lab-scale biological filters under nitrifying conditions spiked with ammonia and environmentally relevant loads of micro-pollutants. A suite of compounds will be selected to cover a wide range of chemical functional groups such as halogen substitutions, heterocyclic aromatic rings, alcohol, carboxyl, amide and amine groups. Using novel analytical approaches, quantitative polymerase chain reaction and targeted gene high-throughput sequencing, the nitrifiers and their cometabolic response to micro-pollutants will be characterised. Based on these results, the student will engineer a nitrifying community with the capacity to also oxidise a broad range of micro-pollutants. Through a new series of microcosms, the student will investigate removal rates of mixtures of contaminants by this seed community and their relationship to ammonia concentrations and other chemical parameters. Finally, quantitative structure-activity relationship modelling will be establish to predict degradation of untested pollutants and multiple regression analysis to recommend remedial approaches to failure (dosing of ammonia, change in pH…).
The theoretical ecology of microbial communities in engineered systems
Prof William Sloan and Dr Stephanie Connelly
Naturally occurring microbial communities are ubiquitous fundamental catalysts in nature. They inhabit almost every environment on Earth from the deep subsurface to the upper atmosphere and play an essential part in the Earth’s biogeochemical cycles. Many years of empirical research has taught us that these barely visible communities can be exploited for the benefit of man. However, our fundamental understanding of how the communities form, evolve and function is poor, which limits our potential to make radical leaps in new emerging technologies for cleaning the environment, power generation, fighting climate change and in health. This has the potential to change. Modern molecular methods, powerful imaging technologies and microfluidics are giving us unprecedented insights into the composition and functions of microbial communities. The University of Glasgow is almost unique in the world in having a group of researchers who are attempting to encapsulate these new observations into theoretical frameworks using mathematics. They are already demonstrating the worth of mathematical microbial ecology in applications to, for example, microbial fuel cells, hydrogen production from algae and corrosion by biofilms.
We are looking for a self-motivated scientist with a strong mathematical background to undertake a PhD on the fundamental ecology of microbial communities. The research will involve both mathematical modelling and experimentation. The research will be motivated by important engineering applications and tackle questions like:
• Can we predict the behaviour of predatory bacteria and their prey such that they can be deployed to remove biofilms in drinking water systems?
• Biomass produced in biological treatment of wastewater is very difficult to get rid of. Can we simultaneously model the metabolic rate, growth and energy dissipation of bacteria and hence maximise both metabolic rate and energy dissipated to minimise growth of biomass?
• Diversity of microbes promotes stability of function in engineered biological systems. Can we predict the diversity and stability of systems before we build them?
Next generation of traffic management strategies via the connected vehicle initiative
The widespread availability of traffic data (urban big data initiatives) now provides real-time measures of effectiveness that allows objective traffic control and measurable improvements in the efficiency of traffic networks. Most cars now are equipped with vehicle automation features, including (automatic) cruise control and collision avoidance, while there is an increasingly research on self-driving cars from Tesla to Google, and Uber and others. In particular, the recent advantages in vehicle automation and communication technology enable Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) cooperation for improving traffic and control systems in real-time. This research focuses on the investigation of how real-time data from heterogeneous media sources and vehicle automation technologies can be used to provide better monitoring of the traffic networks, which consequently could lead to the development of the next generation of traffic control strategies.
Mobility as a Service (MaaS) and Sharing Economy
In developed countries there has been a consistent downward trend in the percentage of young people owning a driving licence. Nowadays, transport is increasingly seen not as a physical asset to purchase like a car. Instead, all transport services from vehicles to buses to rail to bikes will be provided as a single multi-modal service available on demand, i.e. Mobility as a Service (MaaS). MaaS currently encompasses a wide range of services, businesses, and target markets in sharing economy and cooperativism. This includes demand responsive transport, flexible public transit (e.g. shared rides, and bike sharing), express, crowd-sourced urban delivery services, or real-time parking services. Major car manufacturers are currently investing in vehicle automation, car sharing, and rentals, while smartphone apps for on demand mobility are very popular among young people. This project will investigate and develop a platform for studying the impacts of introducing various MaaS systems and connected/autonomous vehicles in our cities and demonstrating where further efficiencies might be achieved, particularly in sharing economy, land use, and traffic management.
Smart Connected Transportation Systems: Modelling, Simulation, Optimization, and Novel Big Data
Dr Wei Liu and Dr Konstantinos Ampountolas
Information and Communication Technologies (ICT) have been constantly evolving on an almost daily basis, and become a pervasive aspect of our lives. This is particularly true when it comes to transport and how people travel. Particularly, connected transport systems (CTS) in smart cities are emerging, which utilise technologies in wireless communications, positioning, digital maps, and data processing to enable personal wearable devices, mobile devices, vehicles, and smart infrastructures to exchange information with each other and to provide users with enhanced mobility. At the same time, development in vehicles automation allows vision for connected self- driving vehicles in the future smart roads and parking lots. A recent example is the on-going large- scale deployment of a Connected Electric Autonomous Vehicles system in the City of Columbus, USA.
The development of CTS holds great potential to improve efficiency and sustainability of the transport sector via reducing congestion, avoiding cruising-for-parking, reducing energy consumptions and urban vehicle emission, etc. However, these cannot be fully achieved unless the major challenges and opportunities regarding CTS have been well understood and addressed. Firstly, CTS can significantly change the way in which people travel and people behave in the system (e.g., mode choice, route planning), as well as the interaction between vehicles and infrastructures and traffic flow. Therefore, new modelling and simulation techniques, especially those can accommodate vehicle-to-vehicle and vehicle-to-infrastructure communications, are in need. Secondly, the application of connected-systems (e.g., in City of Columbus) coupled with wide-spreading smart and wearable devices offer novel big data availability. These data sources should be analysed and utilised in an innovative way (e.g., integrated analysis of different sources of data), and help improve planning and operations of CTS.
Development of a novel osmotic membrane bioreactor for energy-neutral anaerobic wastewater treatment
Dr Xue Jin and Prof William Sloan
The United Nations estimates that the world produces around 1,500 cubic kilometers of wastewater annually, of which more than 80% is untreated. On average, treating 1 m3 of sewage consumes ~0.5-0.6 kWh of energy, ranking the fourth most energy intensive sector in the UK. With the increasing concern over declining quality of natural water bodies, greenhouse gas emission and the escalating price of fossil fuels, the conventional paradigm of sewage treatment needs a step-change. There is a rapidly expanding global water market in creating and delivering low energy and environmentally sustainable sewage treatment technologies which are required not only for enhanced treatment efficiency but also resource exploitation. Compared to energy-intensive aerobic counterparts, anaerobic sewage treatment processes are more attractive due to their low energy consumption and sludge production and their production of bioenergy. However, it is crucial to pre-concentrate dilute sewage before anaerobic digestion in order to achieve improved treatment efficiency and energy recovery. In this project, we propose to develop a novel osmotic membrane bioreactor for energy-neutral anaerobic wastewater treatment. The whole system is highly attractive in terms of treating wastewater to meet the further stringent water quality standards, reduced footprint and reduced energy costs. More importantly, it has the potential to make sewage treatment a net energy producer. This project will focus on simplified systems where we can build models of water flux, pollutant removal and biogas production in response to key variables (e.g., membrane materials, wastewater/draw solutions composition, temperature, reactor configuration). Design and operation guidelines of the system will also be established.
Incipient entrainment of coarse grains due to wind gusts: a new framework for aeolian transport
Dr Manousos Valyrakis and Dr Hossein Zare-Behtash
Particle entrainment due to air at low mobility conditions is important in a range of processes relevant to applied research themes ranging from aeolian sediment transport mechanics to particle technology (e.g. pneumatic transport). Until recently, challenges in accurately measuring particle displacement have hindered progress in identifying the relevant mechanisms responsible for this. This study, suggests a novel set of appropriate particle transport experiments in a wind tunnel designed to better identify the processes of aeolian transport of coarse particles due to turbulent gusts in wind flows. A laser interferometer will be used to measure the angular displacement of a fully exposed particle resting on a horizontal, aerodynamically roughened bed surface. Specifically, the minute displacements (rocking) to full dislodgement events (rolling) of the particle will be detected and monitored simultaneously with high frequency and highly accurate flow diagnostic equipment such as particle image velocimetry (PIV). This will allow for the motion of the exposed grain to be both deterministically as well as statistically linked to the aerodynamic forcing on the grain. Parameters such as variation, frequency, duration, amplitude, time between displacements will be investigated and discussed and connected to specific coherent flow structures and gust properties, as well as stochastically via the probability of exceeding an appropriately chosen threshold criterion. Following this framework the flow conditions for which entrainment can occur can be identified and appropriately parameterised for transport at low mobility rates.
Transport of sediment past instream vegetation in turbulent rivers
Dr Manousos Valyrakis and Dr Thorsten Balke
The dynamical processes involved in the transport of sediment due to turbulent flows past live instream vegetation in riverbeds are yet not well understood and predictive bedload formulas are lacking. This project aims to extend the current understanding of transport processes to: a) incorporate novel flume experiments with realistic bed geometries, live instream vegetation and mobile mixed grain sizes, b) investigate the role of flow turbulence on the transport processes and c) propose a physically based predictive model for transport of sediment that considers the pertinent parameters of live vegetation. The aim is to use a series of carefully designed flume experiments with novel tools to allow monitoring of transport, during a range of flow events from above threshold to high flows. The experiments will be conducted in a 0.9m tilting recirculating flume at the University of Glasgow, and will use novel non-intrusive experimental equipment, namely acoustic Doppler velocimetry (ADV), particle tracking velocimetry (PTV) and particle image velocimetry (PIV), to study feedback mechanisms between the flow, live vegetation elements and the mobile particles and how this interaction changes, at higher flow rates. These measurements will be complemented with synchronously acquired high-speed photography and video imaging which will be analysed for tracking the paths of individual grains responsible for generating the formation or triggering the break-up of sediment clusters. These experiments will aid expanding and further develop general understanding of the mechanisms of sediment transport past live vegetation, due to turbulent flows.
Optimization of hydrokinetic energy generation systems
Dr Manousos Valyrakis, Dr Marco Vezza and Prof Paul Younger
This project will be at the interface of water and energy research. A comprehensive assessment study of existing hydrokinetic technologies will be initially undertaken. After the preliminary technico-economic assessment of current hydrokinetic systems (involving information collection, critical analysis of various features, as well as financial viability analysis, and considering a categorization depending on the core operational principles, scope of application as well as positive and negative impacts), the major features of select technologies will be considered for optimization. A “coarse-level” optimization of central features of the select technologies will be done initially analytically, considering alternative designs to the existing systems. A more detail assessment and optimization will follow by means of detailed computational fluid dynamics simulations (CFD) targeting at optimal performance of the selected technologies for the range of operational conditions (potentially considering real life sites, as case studies for implementation and demonstration of these designs). Other factors will also be considered, such as effectiveness and ecological safety of the system (e.g. compatibility with fish passages amongst others).
Live monitoring and detection of toxic algal blooms in surface water bodies
Dr Manousos Valyrakis, Dr Xue Jin and Prof David Cummings
This project aims to address the challenge of monitoring freshwater and marine waters quality particularly for the detection of Harmful Algal Blooms (HABs). These are of extreme significance to Scotland, the UK and the rest of the world as they pose a potential threat to fish and subsequently human’s health (as a consumer) and the economy (impacting adversely the aquaculture industry). HAB’s can occur naturally, but also can be intensified by human activities directly or indirectly. This multidisciplinary project aims to shed light to the highly variable (both spatially and temporally) dynamics of algal blooms, by using a new methodological and technological approach to monitor and sense algal species growth in real time. In particular, a novel hybrid “multi-tool” and “smart-sensor” will be used to detect surrogates for algal growth (such as pressure, temperature, pH and turbidity amongst others), across the water column and under a range of well-controlled laboratory conditions. The hybrid sensor device will be calibrated for a range of water quality and hydrodynamic flow regimes at the Water Engineering Lab. The prototype device will be combined with a telemetry system for automated data acquisition to enable fast and accurate measurements during real-time field-testing at sites of interest.
Liquefaction of sand with fines
Dr Tom Shire (email@example.com)
Liquefaction causes the ground to undergo dramatic reductions in strength and stiffness and commonly occurs in sandy soils subject to shaking by earthquakes. An example of the hazard posed by liquefaction is the 2011 Christchurch earthquake, which caused 185 deaths and lead to damage totalling an estimated $40 billion.
The processes which cause liquefaction, such as an increase in water pressure in the pores of the sandy soil, operate at the grain-scale. To develop more effective risk assessment procedures these grain-scale processes must be better understood. Liquefaction is particularly poorly understood for sandy soils containing fines and this will be the focus of this project.
This project will use discrete element modelling (DEM), a numerical method which allows detailed analysis of granular materials to be carried out at the grain/particle scale. It is effectively a virtual laboratory test which allows a wide range of variables unavailable to experimentalists to be measured. The open source DEM code LAMMPS (http://lammps.sandia.gov/) will be used and this will be coupled with lattice-Boltzmann methods to simulate the particle-fluid interaction which leads to liquefaction. LAMMPS is designed for use with high performance supercomputers such as the national supercomputer ARCHER and Archie-West at Glasgow University. DEM simulations will be carried out for a range of sandy soil states with varying amounts of finer material and the results will be used to answer the following questions:
- What are the fundamental grain-scale mechanisms which cause liquefaction of sands with fines?
- How well do current theories derived from experimental work (e.g. Rahman and Lo, 2011) capture the mechanics of liquefaction?
- How can analysis techniques be given a more fundamental scientific basis?
The focus of this project is liquefaction but it should appeal to all engineers and physicists interested in granular materials. Therefore, in addition to civil engineers, applications from students from other disciplines (e.g. mechanical and chemical engineering, physics and applied mathematics) are welcomed.
Effect of climate on internal erosion of dams and flood defences
Dr Tom Shire (firstname.lastname@example.org)
Climate change will lead to hotter, dryer summers interrupted by intense rainstorms and wetter winters with a dramatic increase in peak river flows. Dams and flood defences constructed from soil fill are critical public infrastructure and climate change will mean they have to perform under more extreme conditions than ever before.
Internal erosion is one of the two main causes of failure in embankment dams and their foundations, and the main cause of failure in ageing dams. Most studies into internal erosion have concentrated on the conditions immediately after construction. The effect of climate over time (wetting and drying cycles) remains poorly understood.
This PhD project will use state of the art laboratory testing in internal erosion to study the effect of wetting and drying cycles on fill materials. This will be combined with other advanced geotechnical testing and characterisation of the soil fabric at the microscopic scale to shed new light on the effect of climate on dams and flood defences.
Funding is available for UK and settled EU students: https://www.findaphd.com/search/ProjectDetails.aspx?PJID=86460&LID=2252
The future of mobility with connected/automated vehicles
Dr. Konstantinos Ampountolas
The recent advantages in vehicle automation and communication technology enable Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) cooperation for improving traffic and control systems in real-time. Today cars are equipped with vehicle automation features, including (adaptive or traffic- aware) cruise control and collision avoidance, while there is an increasingly research on self-driving cars from Tesla to Google, Uber and others. This research will investigate how real-time data from heterogeneous media sources and vehicle automation technologies can be used to provide better monitoring of the traffic networks, which consequently could lead to the development of the next generation of traffic control systems.
Phylogeny-aware metrics for microbial community assembly driven by ecological and evolutionary principles
Dr Umer Zeeshan Ijaz (http://userweb.eng.gla.ac.uk/umer.ijaz)
Professor William T. Sloan (https://www.gla.ac.uk/schools/engineering/staff/williamsloan/)
Microbial community surveys often involve alignment and generation of phylogenetic trees using Operational Taxonomic Units (OTUs) or alternatively, Single Nucleotide Variants (SNVs) as an OTU-free approach using different marker genes(16S/18S rRNA, ITS region etc.). These phylogenetic trees in conjunction with species abundances on a sample space are usually employed in distance metrics (such as Unifrac distances) to ascertain geometric sources of variation (e.g., PERMANOVA test) against extrinsic meta data. Recently, phylogenetic-aware alpha diversity measures have seen their utility in exploring stochastic and deterministic nature of microbial community assembly to delineate environmental pressures (e.g., NTI/NRI metrics). This is usually done by looking at how clustered/dispersed the phylogenetic tree is. Indeed, our recent work  has shown a switch from competitive to environmental drivers of microbial communities in longitudinal Chicken cecum profile creating a window of opportunity for human pathogens such as Campylobacter to appear. Other recent methodological developments include phylogenetic beta diversity variants such as β-NTI/ β-NRI  and various statistical moments on the phylogenetic trees . In view of these recent developments, the main aims of the PhD project are:
a) to consolidate the existing literature on phylogeny-aware metrics for microbial community analyses (borrowed from the latest in numerical ecology);
b) to further develop information theoretic approaches looking at community assembly from a phylogenetic point of view at different granularity (from species to genera to families to taxa up the hierarchy) and by doing so assessing anomalies in the commonly used reference taxonomies;
c) to incorporate models of molecular evolution in phylogeny aware metrics;
d) to develop approaches for concordance of multiple phylogenetic trees all derived from different marker genes (or primers pairs), but for the same sample space;
e) and to develop mathematical/statistical models on phylogeny that give an account of microbial community resilience to external perturbations by presence/absence of specific clades.
The project team also has a vast experience in developing mathematical and statistical models to explain community assembly in microbial communities, for instance, exploration of neutral community assemblage fitting Neutral Community model for prokaryotes to the distribution of microbial taxa (Professor Sloan) , and recent work involving Dr Ijaz on fitting the Unified Neutral Theory of Biodiversity with Hierarchical Dirichlet Process (NMGS package ). The prospective student, ideally someone with a computational background: will become part of Environmental’Omics lab within the Water & Environment group (School of Engineering); will be given access to high-performance computing facility maintained at Dr Ijaz’s lab; and will be provided numerous datasets from existing and past microbial community studies to test their methods. Further, programming experience in R is required as the secondary aim of the project is to port the developed methods to microbiomeSeq package (http://userweb.eng.gla.ac.uk/umer.ijaz/projects/microbiomeSeq_Tutorial.html) that both Dr Ijaz and Professor Sloan are contributing to.
 U. Z. Ijaz. Comprehensive longitudinal microbiome analysis of chicken cecum reveals a shift from competitive to environmental drivers and a window of opportunity for Campylobacter. Frontiers in Microbiology, 9:2452, 2018. DOI: 10.3389/fmicb.2018.02452
 J. C. Stergen et al. Stochastic and deterministic assembly processes in subsurface microbial communities. ISME, 6:1653-1664, 2011
 C. Tsirogiannis and B. Sandel. PhyloMeasures: a package for computing phylogenetic biodiversity measures and their statistical moments. Ecography, 39(7):709-714, 2016.
 W.T. Sloan et al. Quantifying the roles of immigration and chance in shaping prokaryote community structure. Environ Microbiol 8: 732–740, 2006.
 K. Harris et al. Linking statistical and ecological theory: Hubbell's unified neutral theory of biodiversity as a hierarchical Dirichlet process. Proceedings of the IEEE, 105(3):516-529, 2017.
A first order conservation law framework for solids, fluids and fluid structure interaction
Dr. Chun Hean Lee (email@example.com)
The computational analysis of fluid structure interaction phenomena is widely used these days for a wealth of industrial and physical applications. In particular, the field of biomechanics has observed a surge over the last decade in the application of these computational techniques for the modelling of biological tissues (i.e. heart valves) interacting with biological fluids (i.e. blood). Some of these problems are highly challenging, requiring the modelling of highly deformable (nearly incompressible) solids immersed within a surrounding incompressible Newtonian viscous fluid. In this case, a fast and robust computational framework becomes essential for a successful simulation.
Building upon very recent discoveries (i.e. first order conservation law for solid dynamics) made by the supervisory team, the objective of this PhD is the further development of a novel 3D computational framework with significantly improved properties with respect to the current state of the art. Initial implementation has been carried out in Matlab platform, with very promising results in some extremely challenging solid dynamics problems. Interestingly, the methodology will borrow concepts from Computational Fluid Dynamics and apply them to Computational Solid Dynamics in a way that will greatly enhance the robustness and accuracy of the simulations, with the final aim to handle fluid-structure interaction.
The recruited PhD candidate will become a member of an active research group working on the development and application of cutting edge computational techniques for large strain solid dynamics, fluid structure interaction and computational multi-physics.
Traditional low-order finite element formulations are typically employed in Industry when simulating complex engineering large strain fluid structure interaction problems. However, this approach presents a number of well-known shortcomings, namely: (1) unable to accurately capture the initiation and propagation of strong discontinuities in solids/fluids, (2) a reduced order of convergence for strains and stresses, (3) poor performance in nearly incompressible solids and (4) numerical artefacts in the form of shear/bending locking, volumetric locking and spurious pressure modes.
The aim of this thesis is to develop a unified computational framework for the numerical analysis of fluid structure interaction problems. In this work, a very competitive vertex centred finite volume algorithm will be employed. The solid-fluid coupling conditions on the interface will be solved via a physically based Riemann solver. In addition, for problems involving extremely massive deformations, it may be necessary to re-adapt the mesh to maintain both the mesh quality and the solution accuracy.
The sister project, in collaboration between Swansea University and University of Glasgow, will focus on the development of OpenFOAM finite volume solver for fluid structure interaction. Details of this collaborative project can be found at the following link: https://www.lacan.upc.edu/ProTechTion/wp-content/uploads/2018/02/ESR6-SU-UPC-ESI.pdf
- To have a strong undergraduate and MSc degree (or equivalent) in Engineering, Mathematics, Physics or a related field
- To have an enthusiastic attitude to conduct research, being hard-worker and critic
- To have a strong background in nonlinear continuum mechanics
- To demonstrate experience with numerical methods (Finite Volume/Finite Element)
- To have a good knowledge of some programming languages such as Matlab and/or C/C++
- To demonstrate experience with parallel programming
Cost-effective Sensors for Rapid Monitoring of Water Quality
Dr Zhugen Yang (firstname.lastname@example.org)
Water contamination with microbial organisms is a global issue. Even with well-operated drinking water treatment systems, such as those available in Scotland and Europe, drinking water distribution systems are vulnerable to episodic pathogen intrusion (from pressure losses, repairs or rain-induced run-off of dirty water from agriculture). Contaminations also impact upon remote, rural local distribution systems with decentralised facilities, such as those present in many low and middle income countries (LMICs), as well as remote areas of ‘developed’ countries (such as in villages the Highlands in Scotland).
In this project, low-cost, deployable biosensor devices (lab-on-paper) will be developed for the online monitoring of water quality to address such global water contamination issues. Using a paper-microfluidic sensor, similar in its size to a pregnancy test, we will develop rapid, sensitive and easy-to-use sample-to-answer testing devices which can be widely deployed to identify multiple pathogens in drinking water and track their source. These novel devices will also help identify microbial and human contamination patterns and dynamics, and in doing so enabling industry to “adopt new and more productive ways of working.”
Working with Scottish Water and other industry partners, we aim to translate this new understanding on the dynamics and transportation of microbial contamination into effective monitoring strategies and remediation processes, to maintain "sustainable communities and sustainable homes”. In future, our platform will also enable source tracking and monitoring in the wider environment around agricultural processes, including the emergence of antibiotic resistant genes (a major global challenge).
The project aims to create impact within society by enabling the early detection and tracking of microbial water contamination, through the development, validation and deployment of a rapid, low cost, easy-to-use and portable sensor based on a newlab-on-a-paperplatform. We will work together with our industrial partner, Scottish Water and use the project to expand and strengthen links with Division of Biomedical Engineering within The School of Engineering and with The School of Geographical and Earth Sciences within the university. The project will also involve cross-college collaborations into the MVLS.
By enabling the tracking of the source of contamination, we will better understand the pollution pathways, thus leading to improved treatment strategies, as well as the development of surveillance and early warning systems. The project will also have impact beyond the direct implementation of the devices, where the new understanding of the dynamics of transport pathways will enable new research on complex ecotoxicological fluxes, with the potential to provide information on the fate of (for example) drug resistant organisms in the environment and how urban and agricultural practices could impact this.
As a pathway to demonstrate the applicability of the innovations, we will validate the techniques developed with our industry partner Scottish Water in the field. Our close collaboration will ensure that the developments are relevant to the end-users requirements, de-risking their translation. In practice, the impact will be realised through the development of commercial devices and intellectual property, the delivery of which will have additional economic impacts.
Mathematical modelling of Natural microbial communities
Dr. Rebeca Gonzalez-Cabaleiro (email@example.com).
Complex communities of microorganisms have the potential to catalyse industrial processes in a cheap and sustainable way. However, there is a lack of understanding on how microbial populations evolve and how different species collaborate or compete for the available resources in the environment. If we cannot understand these interrelationships, we cannot engineer them.
The Water and Environment Research Group at the University of Glasgow aims to understand in a deeper way, microbial communities that are of interest for the biotechnological industry and for remediation of waters or soils. For doing so, we aim to develop and use mathematical models that will link with the experimental work currently develop in the group. In particular, with Individual-based models (IbMs), where the growth of each of the microbial individuals of the community is described, we can study the relationship of the different microbial species, their position in the community and their survival capacity (https://www.nature.com/articles/nrmicro.2016.62). We aim to use IbMs as a platform where we can program and see the growth, decay and evolution of each of the microbial species of a population and how their activity changes the environmental conditions affecting other microorganisms present in the same system.
The PhD candidate will work at the frontiers of biology and chemistry using mathematics and programming as tools. She/he must have a passion for bioprocess engineering but also for mathematical modelling. An interest and knowledge on MATLAB programming will be appreciated. She/he will work in close collaboration with other PhD candidates that are engineering the process at laboratory scale and with industrial partners. Internships to other European Universities will be considered.
Improving the dynamic response of reinforced concrete structures
Dr Peter Grassl (firstname.lastname@example.org)
Critical infrastructure, such as bridges, high rise buildings and nuclear reactors, should be designed to resist extreme loading events in the form of blast and high-speed impact. Reinforced concrete structures subjected to dynamic loading exhibit complex failure processes, whereby the response of connections between members are often critical for the resilience of the entire system. Understanding how the performance of structural members and their connections can be improved is highly desirable so that resilient structures can be designed.
The aim of this project is to investigate how cementitious materials can be enhanced by tuning fibres and other inclusions to create materials with exceptional mechanical properties. For these new materials, we aim to develop damage-plasticity constitutive models together with small scale physical experiments. Nonlinear finite element techniques for dynamic analysis of structures together with the new constitutive models will be used to assess the effect of the new materials on the failure process of structural members.
Computational modeling of soft tissue biomechanics
Dr. Ankush Aggarwal (email@example.com)
Almost 30% of all deaths globally are related to cardiovascular diseases, and most of these are related to changes in the stiffness of tissues making up the system. There is an urgent need for new computational tools that can help detect, understand, and treat these diseases. There are three projects available related to this broad topic:
1. Image-based evaluation of cardiovascular health
2. Computational model development for endothelial cells response to combined loading
3. Uncertainty quantification and design of experiments for soft tissue mechanics
A common theme in these projects is to use an interdisciplinary approach to develop computational models and tools, and then use these tools to develop a new understanding of the soft tissue biomechanics.
During these projects, students will have opportunities to:
• Learn about advanced topics, including nonlinear finite element analysis, bio-chemo-mechanical modeling of cells, nonlinear mechanics, image analysis, optimization, and uncertainty quantification
• Interact within the Glasgow Centre for Computational Engineering with other researchers (GCEC) and across departments with biomedical scientists, clinicians, statisticians etc.
• Present research results at workshops and conferences
• Publish papers in high-quality journals
• Develop interdisciplinary skills that allow you to work at the interface of engineering and biological science
Influence of climate on unsaturated soils: laboratory testing and modelling
Professor Simon Wheeler (Simon.Wheeler@glasgow.ac.uk)
The School of Engineering of the University of Glasgow is seeking a highly motivated graduate to undertake an exciting 3/3.5-year PhD project entitled ‘Influence of climate on unsaturated soils: laboratory testing and modelling’ within the Infrastructure and Environment Division.
Climate change will lead to more droughts and hotter summers, leading to larger drying and wetting cycles in unsaturated soils. This project will seek to improve our understanding of how these processes will affect the likelihood of geotechnical hazards such as landslides.
Laboratory testing including an advanced triaxial apparatus and modelling with the leading Glasgow Coupled Model will be used to improve our understanding of how suction and anisotropy will affect the geotechnical behaviour of unsaturated soils. The researcher carrying out this project will develop a deep knowledge of unsaturated geotechnics which would be valued by industry as well as high level practical laboratory and problem solving skills.
For an informal discussion or for further information on this project, potential applicants are encouraged to contact Dr Tom Shire or Professor Simon Wheeler:
Particle tracking in PEPT using machine learning
Dr. Andrew McBride
Positron emission tomography (PET) is a nuclear imaging technique commonly used in nuclear medicine to produce three-dimensional images of functional processes within the body. PET scanners and their underlying algorithms have been adapted to explore the complex flow exhibited by granular systems. In positron emission particle tracking (PEPT), one particle within the system is tagged with a radionuclide. The radionuclide undergoes β+ decay, during which a position and a neutrino are produced. When the position comes into the neighborhood of an electron in the surrounding medium, an annihilation event occurs resulting in the emission of back-to-back photons. The PET scanner detects this pair of back-to-back photons and a line of response is constructed. After sampling over a small time increment, an algorithm determines the position of the particle from multiple lines of response. The trajectory of the particle in 3D space can then be reconstructed.
PEPT provides valuable insight into a range of industrial processes. Examples include the mixing of pharmaceutical powders and the milling of rock. A key assumption is that the behavior of the whole system can be described by that of an individual particle tracked for a sufficiently long time. The ability to track more than one particle simultaneously is therefore of significant value.
The algorithms used to reconstruct the trajectory of a single particle are relatively mature. Recently work has been done to track multiple tagged particles. This provides a far richer data set but presents many challenges. The objective of this research project is to apply recent advances in machine learning to track multiple particles within a laboratory-scale tumbling mill. The generated algorithm should be robust and efficient. Granular flow simulations, using the discrete element method, will be used to augment the experimental data set.
PhD in Computational Engineering
Prof. Paul Steinmann (firstname.lastname@example.org)
Computational Engineering delivers sophisticated modelling and simulation tools to predict the behaviour of complex, real-world systems. CE has a pervasive impact on engineering design and discovery-led scientific research. Postgraduate studies in CE will equip you with the skills to solve the engineering challenges of the future.
The Glasgow Computational Engineering Centre (GCEC)is an EPSRC-supported research centre-based at the University of Glasgow. We provide a coherent focus and point of interaction for fundamental and applied research in CE. As a team of ten academics, we have exciting opportunities for motivated and talented students who want to solve challenging and relevant problems across the spectrum of science and engineering.
For more information on the research areas of the GCEC and information on our team, visit www.gla.ac.uk/research/az/gcec/
Enhancing slope stability with capillary barriers
Prof. Simon Wheeler
Climate change will lead to more extremes of weather, including both droughts and heavy rainfall. This will lead to increased risk of landslides and slope instabilities, as droughts produce cracking of surface soils, providing easier access for infiltrating water during subsequent periods of heavy rain. Infiltrating water dissipates negative pore water pressures (suctions) within the slope and brings the soil from an unsaturated state to a saturated condition, resulting in increased risk of slope failures.
This project will involve advanced numerical modelling of slopes incorporating capillary barriers, to investigate whether these barriers could be effective in reducing rainwater infiltration to the underlying soil, allowing suctions and unsaturated conditions to be maintained and hence enhancing stability. The numerical modelling, employing the CODE_BRIGHT finite element software for multi-physics modelling in unsaturated materials, will include soil-atmosphere interactions, state-of-the art constitutive modelling of water transport in granular soils (including water film flow at low degrees of saturation) and the impact on slope stability. While the project will predominantly involve numerical modelling, key conclusions may be validated by physical model testing in the laboratory.
The project forms a continuation of previous research funded by the EU.
Profiling active nitrifiers with single cell resolution
Dr Cindy Smith
Prof. Huabing Yin
Nitrification is a central process in the global nitrogen cycle driven by microorganisms. Once assumed a simple oxidation of ammonia to nitrite and then nitrate by two separate but reliant groups of microorganisms, recent work has revealed a myriad of complexities including complete nitrification within a single organism. A complete understanding of the organisms and environmental drivers of nitrification is essential to inform not only ecosystem functioning in the face of climate change but also to deliver sustainable agriculture and environmental biotechnologies. A significant barrier to current understanding is the inability to directly link nitrification activity to the responsible microorganisms within complex microbial communities. We propose to develop a state-of-the art microfluidics platform to label, sort and subsequently identify nitrifiers from within complex environments based on their activity with single cell resolution. The approach exploits the autotrophic nature of nitrifiers that use CO2as their carbon source. By supplying the microorganisms with a heavy labelled 13C isotope a characteristic Raman shift is generated. This Raman shift can be used to sort active from inactive cells. The aim of this PhD research project is to develop this state-of-the-art platform combining Stable Isotope Probing (SIP), Resonance Raman (RR) and Raman Activated Cell Sorting (RACS) (SIP-RR-RACS) to sort active and inactive nitrifier. Cell sorting can then be coupled to sequencing approaches to further explore he identify and metabolic capabilities of the active organisms under a range of experimental conditions.