Our Projects

In this PhD, Edgar will be focussing on developing a methodology that enables the user to rapidly and iteratively design a heat exchanger core hat meets a set of heat transfer and pressure drop requirements whilst adhering to spatial constraints.

Metal additive manufacturing (AM) is viewed as a key enabling technology for the next generation of thermal management solutions (e.g. heat exchangers). Heat exchangers, used to transfer heat between two fluids, are essential components in many engineering systems in sectors such as aerospace, automotive and energy. The harmony between AM and heat exchangers arises through the relative ease with which complex and intricate internal geometries (channels) can be produced without the need for costly fabrication stages. As such, AM heat exchangers have already established themselves as highly performant, compact and lightweight alternative to traditional heat exchanger concepts.

However, AM presents significant challenges in terms of development costs and time, particularly where iterative production might be expected. A typical, single machine facility is likely to cost in the range of £1 million, and titanium powder feedstock costs approximately £400 per kg. A heat exchanger with dimensions of 200 by 200 by 200mm would take approximately 10 days to produce. As such, to iteratively develop a new heat exchanger concept using this technology would easily exceed the £100k mark in terms of development cost.

Cellular geometries and, particularly, triply periodic minimal surfaces, have gained a lot of attention in both the literature and industry within the context of heat exchangers. These mathematically-defined geometries present various appealing properties. Most importantly, these are all cellular in nature and split the cell into two equal or unequal volumes, which remain interconnected between adjacent cells. Therefore, two different fluids can travel through the two networks and always be in close proximity (separated by a thin wall) without physically mixing.

Several challenges exist in this field, however. While these are mathematical designs and, hence, can be modified in limitless ways, they do not inherently maximise heat transfer and/or minimise pressure drop, which are the two main challenges in heat exchanger design. The authors believe that there is plenty of scope for at least some of these geometries to be altered to find more optimal designs than the default minimal surfaces as provided by the conventional equations. A part of this project involves comparing different designs of multiple minimal surfaces to provide insight into which of and how these minimal surfaces could be made optimal for specific heat transfer, pressure drop and mass constraints.

Another related but worth-highlighting gap in the literature is the overuse of CFD without sufficient experimental evidence. Most of the work involving additively manufactured heat exchangers is either industry-lead, and therefore fairly vague and opaque, or, in the opinion of the authors, academically-lead but not rigorously validated. The reason for our scepticism lies in the fact that several review papers highlight the difficulty in accurately predicting performance with CFD (which usually underestimates that pressure drop significantly) and the lack of understanding of the effect of surface roughness.

It is the intention of the authors to experimentally investigate the heat transfer and pressure drop in either all or some of the selected  minimal surfaces to enhance the knowledge base of flow patterns and behaviours in these intricate and complex geometries, characterised by varying levels of flow mixing, recirculation and turbulence. These depend on the working flow regime, which is expected to be between laminar and transitional for air.

During this campaign, the emphasis will be on surface roughness. As mentioned previously, a lot of resources are invested in the production of heat exchangers with additive manufacturing. Furthermore, two equal designs can vary in performance significantly if they are manufactured with different machines or machine settings. If surface roughness can be isolated successfully from the theory, data obtained from designs with smooth surfaces (like SLA or even within CFD) could be used to predict performance in metal-based prototypes, which take much more effort to produce.

It is expected that this research will play a role in the current trends of significant reduction in emissions in the aforementioned industries, owing to a reduced mass and therefore energy/fuel savings. In addition, enhanced performance will also help to recover and harness wasted heat within these systems. Looking further, it is thought that this could help make future aircraft propulsion and power generation systems viable, such as hydrogen fuel cells and widespread electrification.

The aim of this project is to develop a methodology that enables the user to rapidly and iteratively design a heat exchanger core that meets a set of heat transfer and pressure drop requirements whilst adhering to spatial constraints. The current vision is to combine novel heat transfer modelling with an algorithmic design approach. This will be used to automate the design of the core geometry and therefore reduce the engineering overhead and reduce the time required to reach a new proposition. A heat exchanger test bed will be designed and built to facilitate the thermofluid characterisation of the specimens as well as serve as an integral part of the design methodology. validate the modelling work but also to form an integral part of the design methodology by using it as hardware-in-the-loop.

While lead time and development costs are a major priority in this project, the trade-off with high performance and efficiency must be managed successfully. Due to its unparalleled versatility when producing geometries, AM allows for highly efficient geometries that, while more expensive to produce than traditional heat exchanger designs, could noticeably reduce the running costs of the systems to which they will pertain. Therefore, the ideal version of this methodology would also enable engineers to produce an optimal heat exchanger design for any given application, although this will likely be limited to a parametric optimisation algorithm – an optimal version of a specific heat exchanger concept. A semi-empirical methodology is thought by the researchers to be the most appropriate way of achieving the desired accuracy of thermal modelling and, thus, minimise the probability of expensive and time-consuming alterations to the heat exchanger design (or even a complete design overhaul).

Howard's PhD will investigate the influence that current ripple has on a Lithium-ion battery cell when it is applied on top of the DC current used to charge/discharge the cell.

Aim:

Objectives:

Classifying road users based on their characteristics allows researchers and policy makers to make general distinctions between different types of road users who may have different needs. The classification vulnerable road user (VRU) is frequently used to describe road users who are not protected by the frame of a vehicle and considered to be high-risk (e.g., motorcyclists, cyclists, or pedestrians). However, there is a body of research challenging this classification, highlighting the emphasis it places on road users as ‘vulnerable’ rather than the vulnerabilities caused by external factors, such as infrastructure design and the behaviour of other road-users. Although this critique is not new, the issues identified in this critical literature are not coherently addressed in empirical work involving these road users that uses the VRU construct and forms assumptions based on it.

This PhD research will explore alternative approaches to categorising road users, particularly those considered vulnerable, and using these categories to understand road-user interactions through modelling and analysis. The aim of the project is to develop a theory to understand road user vulnerability from a complex systems perspective. The project comprises three phases: a theoretical phase to develop the conceptual foundations for the approach, an experimental phase to identify important road user characteristics, and a modelling phase, to verify and iterate the theory developed in phase two and explore relevant metrics and investigate the dynamics of how vulnerability changes as a function of its component parts.

The first phase will examine how the VRU classification is understood across disciplines, explore VRU behaviour and power differentials on the road, and evaluate how the classification is currently operationalised in modelling and analysis. This will involve conducting a scoping literature review.

The second phase will employ mixed methods and use secondary census and transport use data, route planning analysis, and photo ethnography to understand the factors that can act as ‘hinge points’, where VRUs change their route or mode of transport.

A subsequent study will systematically analyse existing approaches used to interpret VRU behaviours and intentions in transport modelling and predictive systems and how the factors identified in study one are incorporated.

This initial work provides a foundation to understand the state of the art, identify important factors that influence VRU behaviour, and identify priorities and metrics to be used in modelling. The aim of this phase is to analyse the processes and power dynamics underlying road user behaviours in a way that can be implemented in empirical modelling methodologies.

The third phase of this research will focus on theory development and simulation. Here, the theoretical processes identified in phase 2 will be formalised into causal models outlining the expected relationships between different elements of vulnerability and their link to behaviour. These models will then be tested and iteratively refined through agent based modelling. The aim of this phase is to explore the validity of the theory proposed and identify potential tipping points or critical factors that can influence road user behaviour based on changes in vulnerability.

As a result of increased electrification within the automotive industry and energy sector, the demands from electric machines have never been greater. Therefore, reducing the cost and size of these machines whilst maximising their power capabilities is crucial. A prime opportunity to achieve these targets is through accurate real-time thermal modelling of key motor components, such as the end windings and permanent magnets.

Such a model would enable the measurement of difficult or inaccessible locations within the motor, without the need for expensive sensors. Therefore, the power density of a given machine could be increased as the large safety margin, which exists due to temperature uncertainties within the machine, could be reduced. Additionally, this could enable electric machines to be downsized, whilst still meeting the required power ratings for a given application.

The motivation for this project is broadly to address the aforementioned benefits a real-time thermal model could enable; however, it is more precisely motivated by the current lack of agreement, robustness, and implementation of methods currently proposed within the literature. Comprehensive reviews of the topic outline drawbacks and benefits to many different modelling techniques, including machine learning, reduced order thermal networks, state observers, and hybrid approaches. Although no single method is yet to prevail as a favourite, most methods revolve around lumped capacitance modelling.  

Furthermore, testing found within the literature is based on datasets in strict laboratory conditions, often with simplistic test cycles. This brings into question the models’ robustness and feasibility if implemented onto a real-world system, namely in automotive contexts. This is further reinforced as many publications rely on a pre-recorded experimental dataset for machine learning, parametrisation, and testing. Finally, this experimental dataset, much like many others in the literature, uses a relatively low speed (6000 rpm) liquid cooled motor, hence internal phenomena resulting from high-speed motors may have not been captured and other cooling methods are not understood.

The scientific impact of this project will be to enable downsizing of electric machines in testing and automotive applications. These machines are currently restricted by large thermal safety margins due to temperature uncertainties within the motor. Additionally, by modelling the temperature within the machine, the cost of test bed systems can be reduced by circumventing the requirement for expensive sensors in poorly accessible locations (e.g., rotor magnets).

Finally, Ryan's project seeks to increase the flexibility of modelling machines with differing geometry and cooling systems, reducing the cost and time associated with parameterising the model, whilst delivering reliable and accurate results.

With no natural sources of pure hydrogen, The UK must resort to manufacture using steam-methane reformation which also produces carbon dioxide.

For hydrogen to play a part in our journey to net zero transport, all current and future production will need to be low carbon. This requires a separation process such as pressure swing adsorption. Hydrogen purity is required at 99.95% for combustion and 99.99% for fuel cell applications. Porous materials can use the adsorption phenomena to exclude gases passing through a column to get pure hydrogen. These include silica, zeolites, and more recently, research has turned to the high-surface area and customisable family of metal-organic frameworks (MOFs). With 100,000s MOFs currently stored in databases, a computational study can expedite the discovery of next-generation materials for the decarbonisation of hydrogen manufacture. The overall aim is to optimise a new method of materials screening to find promising materials, quickly. These will be tested using a mix of computational and experimental studies for application of gaseous separation in pressure swing adsorption.

Elisabetta's PhD proposes the use of solid oxide fuel cells (SOFCs) for the direct conversion of hydrogen storage vectors such as ammonia to electrical energy. SOFCs have several advantages over PEM, including, multi-fuel capability, resilience to poisoning from fuel impurities and lower use of precious metal catalysts.  These systems, however, require a “defects and flaws” control on the structural and functional properties of their ceramic electrolytes because of their high variability of the strength, and their relatively low toughness, which are some of the point of interests of this research project.  

Chemical molecules such as ammonia have the potential to be excellent hydrogen storage vectors for aviation fuels. They do not require high pressure containment but still achieve very high hydrogen storage densities arising from the hydrogen stored within their chemical structure. Ammonia is also good at conducting and absorbing heat, making it good for energy acquisition while also avoiding the formation of “coke” and other residues that hydrocarbons leave behind under extreme temperatures. This substance is also much easier to store as a liquid because, under this form, it only needs to be kept at  -33 degC, which is very close to the temperature at cruising altitude.  The release of the hydrogen, however, requires a catalytic conversion and ppm levels of ammonia are a poison for PEM fuel cells, and for this reason, a SOFC is required.

The project proposes the (1) characterisation and (2) optimisation of SOFCs for usage in aerospace electric propulsion applications. Characterisation of the cells will focus on cycle efficiency of different fuels (Ammonia, hydrocarbons, H2), the internal chemistry/catalysers used and their behaviour under certain operating conditions. Optimisation will be on structural integrity of electrolytes and fuel cell weight reduction, power transfer efficiency, and possible thermal management of waste heat.

UK surface transport emissions have overshot the sixth carbon budget by 224 MtC, requiring emission cuts ten times those saved during the COVID-19 pandemic. Improvements in the quantity, quality, and speed of Travel Demand Management (TDM) implementation is urgently needed if the UK is to meet its target to reduce car miles by 9% before 2035. 

Employers can act as a bridge between their employees and broader transport policy goals by providing a social context and communicating norms. Employers control the physical and social environments of their employees, shaping their employees’ modal choice. Workplace Travel Plans (WTPs) are long-term TDM strategies developed by organisations to manage their staff’s commutes. They are flexible, cost-effective, (relatively) rapid, and publicly acceptable.

Only 11% of organisations in the private sector currently have a WTP and this must increase to 56%, all else equal, if the UK is to achieve target its Net Zero targets of reducing car miles by 9% before 2035. WTPs can be secured from large employers using the planning process, but not from SMEs, who employ 61% of the UK population. At SMEs the motivations of one or two key decision-makers in SMEs are crucial in the decision to adopt innovations – yet we know very little about what drives their voluntary adoption. Behaviour change interventions could target these key decision-makers to adopt a WTP, catalysing widespread change in travel behaviour.

This thesis focuses on three problem areas in achieving scalable demand mitigation; what is the opportunity for SMEs to contribute to modal shift? What factors can explain voluntary workplace travel plan adoption? Under what conditions could a tipping point in the adoption of workplace travel plans be created? By addressing these questions, this research aims to contribute to achieving a social tipping point in mobility behaviour, ultimately accelerating the transition to sustainable mobility behaviours.

Paloma's PhD will investigate the multifunctional performance of structural batteries. The PhD will focus on the use of synchrotron techniques to measure fibre scale mechanical properties of both anodes and cathodes during charge cycling, accumulation of microscale damage and understanding of ion intercalation patterns within the anode. Paloma will progress to understand similar properties under axial fatigue loading.

Structural batteries combine the load bearing and electrochemical storage capabilities of carbon fibres (CFs), offering significant opportunities for weight saving in aerospace and automotive applications. Recent research has showcased the potential of polyacrylonitrile (PAN) based CFs for structural battery anodes, and LiFePO4 coated carbon fibres as cathodes. Both anode and cathode fibres are embedded in a biphasic Structural Battery Electrolyte (SBE), composed of a liquid electrolyte phase for high ionic conductivity, and a porous stiff polymer matrix for mechanical performance. The resulting carbon fibre-polymer composite structure has the high specific strength/stiffness required for lightweight structural applications, and the high ionic conductivity required for battery functionality.

Optimisation and design of the multifunctionality of such systems requires an understanding of the coupling of physical phenomena, including thermal, electro-chemical and mechanical processes. In particular, quantifying the mechanical response at different charge states is crucial in the reliable use of these systems in structural applications. In order to achieve this, the project aims are twofold and iterative:

The first aim is the construction of a comprehensive multiphysics model on MSC Marc of a structural battery composite in order to predict the multifunctional performance of structural batteries in various load cases. MSC Marc is an advanced non-linear FEA solver capable of solving multiphysics problems. This will commence with the development of a multiphysics Representative Volume Element (RVE), to couple electrochemical, thermal and mechanical phenomena. Following this, the RVE overall properties may be used to define larger scale modelling. These simulations will supply an enhanced understanding and facilitate the improved design of structural batteries with the ultimate goal of unlocking their significant potential for reducing carbon emissions.

In order to define both the physical parameters and constants present in the multiphysics model, characterisation of material properties is required on a multiscale basis; quantification of individual structural battery components in isolation, and at the full composite level. In order to achieve this, the project will utilise a broad spectrum of experimental methods at different length scales; from the length scale of the fibre (10's of microns) using synchrotron techniques, to the microscale using nanoindentation and other methods.

Additionally, it is key to include assessment of individual component interactions at the multiphysics level. The scope of the project will focus on quantification of the property descriptor coefficients relating charge/electro-chemical load to mechanical response as required to embed this response into multiphysics simulations. In parallel, quantification of the property descriptor coefficients relating mechanical load to electro-chemical response will thereby fully encapsulate the structural battery system.

Thomas’ PhD project is centred on enhancing the construction of structural batteries made from carbon fibre. His research involves examination of the electrochemical performance of individual electrodes subjected under different conditions.

Thomas is looking into atomic modelling of the carbon fibre anode to understand the structural changes that occur during charging (in partnership with the University of Virginia). Additionally, he is investigating the extent of lithiation of coated carbon fibre cathode materials (collaboration with Chalmers University).

The primary emphasis of Thomas' research lies in comprehensively understanding the structural changes occurring in each electrode across different conditions and evaluating their respective electrochemical performance. This ground-breaking work promises to contribute valuable insights to the field of carbon fibre-based structural batteries.