Engineering
Aerospace
- Modelling by Computational Fluid Dynamics the flow through axial compressor or axial fans e.g. to reduce secondary flow losses by three-dimensional passage and blade shape optimization.
- Use coupled Computational Fluid Dynamics and Discrete Particle Modelling to study particle-laden flow through supersonic convergent-divergent jets, e.g. for cold jet spray coating and additive manufacturing.
- Characterize sound generated aerodynamically in bodywork cavities (e.g. wing fuel vents) and in jets (e.g. turbofan exhausts) with Large Eddy Simulations and Computational Aeroacoustics.
- Solve conjugate the conjugate heat transfer through mini-channels and micro-channels, e.g. to design low hydraulic power loss and high heat transfer rate nanofluid heat sinks for microelectronics.
- Stability and transition to turbulence of supercritical fluids in the presence of heat transfer, primarily using linear stability analysis
- Identify the regimes, at moderate Reynolds numbers, where different instabilities associated with supercritical fluids may compete.
- Gain fundamental understanding of the effect of strong variations of density and viscosity on the stability of shear flows.
- Develop and use resolvent analysis for supercritical fluids to examine how non-modal growth mechanisms (e.g. lift-up effect) are altered in these fluids, along with theoretical analyses.
- Implement robust control methods on systems that undergo external disturbances, develop effective disturbance rejection techniques, and apply them to real-world complex systems, like helicopters.
- Develop non-linear control systems and predictor-corrector based systems to enhance the response speed of a control algorithm without compromising its behavioural performance and bounds.
- Develop effective control methodologies for multi-degree of freedom systems, like robot arms, based on energy methods and energy minimization concepts.
- Analysis, modelling, and control of systems with uncertainties.
- Decentralised and scalable control design strategies for large-scale networks.
- Robustness analysis of complex and large-scale networks.
- Nonlinear systems: Lyapunov methods, input/output approaches, integral quadratic constraints (IQCs), robust and optimal control and linear parameter varying (LPV) approaches.
- Efficient analysis/synthesis method development based on convex optimisation and linear matrix inequalities (LMIs).
- Applications: multi-agent systems, modern power networks and microgrids, vehicle platoons, electrical and mechatronic systems.
Long-range signal transmission characteristics in the Antarctic region, towards safer trans-polar aircraft operations. This project requires a second supervisor to be identified at the outset of the programme.
- Develop advanced control systems for formation flying of autonomously flying rotorcraft (unmanned air systems) and test them on DJI rotorcraft both indoors, without external wind disturbance, and outdoors, with wind disturbance rejection control methods.
- Develop reconfigurable hardware in the loop control systems for fixed wing autonomous air systems, for autonomous flying outdoors.
- Develop advanced satellite attitude stabilization algorithms enabling enhanced image stability in image acquisition during dynamic attitude changes of small satellites.
- Novel Computational Fluid Dynamics (CFD) and Computational Aero-acoustics (CAA) methods and engineering software development for emerging applications in rotorcraft, propellers, and wind turbines.
- Data- or sensitivity-driven optimisation methods for urgent aerospace design problems, such as aerodynamic shape design, noise reduction, and energy consumption minimisation.
- Accurate multi-physics modelling for the emerging Advanced Air Mobility industry, with close collaborations with leading UK academia and industry, including the UK Vertical Lift Network, GKN Aerospace, and Leonardo Helicopters.
Identification of trends in asymmetric academic achievement among students with different protected characteristics and correlation with teaching practices, organizational structures, leading to positive actions towards enhanced equality, diversity, and inclusion in higher education.
- Safety-critical control-based model predictive control and Markov decision process, e.g. develop a framework to capture possible internal and external uncertainties; propose the safety-critical model predictive control method at system level; develop a decision-making framework based on Markov decision process for guaranteeing correctness; integrate and case studies, and this case studies will include but not limited to intelligent robots and autonomous vehicles.
- Optimization and learning for safety-critical control in unknown and uncertain environments. Enhance capabilities from learning and optimization tools while maintaining the safety requirements of control systems. Build a general framework for autonomous systems in such environments.
- Safety-critical control of collaborative robot. Based on the initial work on the control of collaborative robot, incorporate of safety constraints and model predictive feedback controller into the existing control scheme. Humans in the loop will be considered by using impedance control for the trajectory tracking.
- Robust control of mobile robots with sensors in complex environments containing communication imperfections, uncertainties, and physical constraints. Develop a robust control strategy that makes mobiles robots able to resist these disturbances and still converge to the optimal point which satisfies local feasibility constraints.
- Linearised stability models for rotating boundary layers, over cylinders and cones, with combinations of non-isotropic surface roughness, non-Newtonian viscosity, and fluid inhomogeneity (nanofluids).
- Computational Fluid Dynamics simulations of medical devices in collaboration with the Institute of Precision Medicine.
Biomedical Engineering
- Advanced Biological Signal Processing
- Real-time digital signal processing and ECG analysis for atrial fibrillation, ventricular arrhythmia risk assessment, and heart rate variability.
- Utilizing intelligent algorithms and advanced techniques to improve catheter ablation targeting in persistent atrial fibrillation. Body surface potential mapping.
- Application of Machine Learning and AI to Enhance Diagnostics and Predictive Analytics in Cardiology.
- Innovative Techniques in Cardiac Health Monitoring:
- Wearable medical devices and remote monitoring systems
- Virtual reality (VR) and immersive technologies
- Machine Learning and AI related to sensor processing, molecules, behaviour
- Biochemical sensing
- Biomedical Engineering with novel technologies
- Neuroscience, VR and behaviour.
- Numerical investigation of model hearing systems. In particular, insect auditory systems
- Construction of highly-accurate numerical methods for the approximate solutions of elliptic (steady-state) equations in engineering
- Diffuse-interface type two-phase flow problems
- Numerical investigation of micro-circulation of blood in humans
- Diamond and related Materials
- Antibacterial and antifungal materials
- Electronic devices and sensors for harsh environments
- CVD and PVD thin films and coatings for advanced functional applications.
Digital Manufacturing and Management
I work on constitutive model development for powders and particulate materials. My research includes multi-scale and multi-physics modelling problems for compaction, powder flow and additive manufacturing, using Finite Element and Discrete Element based methods, and Machine Learning. I focus on product/process design and manufacturability of complex formulated products, such as pharmaceuticals, food, detergents. I am the Head of the Digital Manufacturing and Management Research Group.
Professor Dong is a Fellow of Royal Academy of Engineering, the Deputy Head of the School of Engineering.
He is an outstanding engineer who has made pioneering and significant contributions in solidification modelling, as well as via the university responsibilities he has held. He was a RAEng Research Chair and a Director of EPSRC Doctoral Training Centre in Innovative Metal Processing at University of Leicester. He is internationally renowned for solidification modelling and its application in metals and has made unique contributions to the metals industry. His work has been exploited in various sectors, including in aerospace by Rolls-Royce, energy by the Welding Institute and steel by Materials Processing Institute. He has played a key role in establishing international partnerships between UK and China, India and South Africa.
His current research involves: Processing of aerospace materials, Digital manufacturing, Machine learning for process engineering.
Shiladitya is the Director of Materials Innovation Centre (MatIC). He is an innovative technology specialist with significant experience in the industrial development and application of specialised coatings, materials and corrosion mitigation methods. He has published over 100 scientific papers (Journal papers conference proceedings, book chapters, and technical articles) in the field of coatings advanced materials and corrosion, and has developed methodologies and test protocols that are currently used in Industry. He joined the University of Leicester in 2018 (0.5FTE) after a decade in Industry-focused research at TWI. He has a PhD (as a Gates Scholar) in Materials Science and Metallurgy from the University of Cambridge, a CEng from the Engineering council UK, and is a Fellow of the Institute of Materials, Minerals and Mining, UK. He is currently the Vice-Chair of the European Federation of Corrosion (EFC) WP9 (Marine Corrosion), and the Chair of AMPP Annual Conference 2024 symposium on Thermal and Cold Spray Coatings. In addition, he is also a member of the Journal of Thermal Spray Technology Best Paper Award Committee. Over the last 15+ years, he has written and contributed to several successful research proposals with a total value of over £20M.
My research interest focus on designing and building mechatronics systems for automation. This can include but is not limited to:
- Process automation
- Prototype design and construction for novel (manufacturing) processe
- Selection and assembling of components
- Retrofitting and reengineering (manufacturing) equipment
- Wireless sensor networks for IoT and wearables sensors
I had experience in a variety of fields such as:
- Composites manufacturing
- Bespoke motion systems
- Industrial robotics and Cobots
- Designing, analysing and implementing equipment to work under about 40G of Earth's gravity within geotechnical centrifuges
- Multi-robot systems allocation algorithms for highly flexible manufacturing
Green Energy and Transportation
Professor Ljiljana Marjanovic-Halburd
- Energy and the Built Environment
- Low carbon building design and operation
- Sustainable buildings and infrastructure
- Advanced Superconducting Machines for power generation and transportation systems.
- Metamaterials for the energy, medical imaging, and defence sectors
- Electrical Machines Design and Optimization
- Control Management and Optimization of Power Networks
- Large Scale Optimization of Renewables from micro to macro scale
- Renewable energies (solar, wind, fusion): Machine design, optimization, control systems, and project deployment.
- Power Electronics Prognostics and Health Monitoring
- Intelligent Power Electronics Modules and Active Gate Drives
- Power Electronics Packaging, Sensing, Reliability and Qualification
- Self-Monitoring and Resilient Control for eTransportation
- DC/DC Power Converters
- Radio wave propagation over the sea and prediction of distortions to radio signals due to the solar wind
- Data-relaying techniques for mobile ad-hoc networks and autonomous vehicles.
- Li-Fi technology
- Modulation techniques for communications systems such as Orthogonal Frequency Division Multiplexing (OFDM)
- Sustainable aviation electrification systems & technologies.
- Energy management strategies and integrated control systems in aviation/transport electrification.
- Smart grid planning and operation with transport integration, such as in airports, vehicle charging, etc.
- Hydrogen-based propulsion technologies and design framework for future sustainable aviation.
- Artificial intelligence-based design of motor drive or power electronic systems.
- Advanced intelligent control and maintenance for electrical power systems onboard all transportation platforms.
- Multi-agent-based modelling and simulation for air-traffic planning and management
- Communications and cooperation between robots / autonomous systems.
Mechanics of Materials
- Modelling the microstructural evolution of structural materials (zirconium, titanium, steel alloys) under high temperatures and stresses.
- Mechanical modelling of geophysical processes, especially faults and magmatic intrusions such as sills and dykes
- Mechanical modelling of brittle materials in compression, especially porous rocks.
- Mechanical modelling of biophysical processes, especially related to the mechanics of the human lung.
- Application of deep machine learning in material processing - you will learn and develop artificial intelligence techniques such as transfer deep machine learning to optimise material processing in order to enhance material performance under extreme conditions.
- Development of digital twin for manufacturing processes - you will learn and develop digital twining techniques such as Bayesian interference to reduce wastage and improve efficiency in modern digital manufacturing process.
- Virtual design of medical implants - you will learn and develop modern numerical methods such as the finite element method and Monte Carlo simulations to resolve challenging issues such as eliminating rare events that are critical to the long-term safety of any medical implants.
- Designs advanced alloys for optimal performance in energy-efficient automotive, fusion, and aerospace applications.
- Applies thermodynamics, kinetics, and mathematical modelling with a focus on structural materials such as steel, nickel, cobalt-based superalloys, zirconium, and titanium alloys.
- Utilises microstructural and mechanical advanced characterisation techniques, enabling a nuanced understanding of material behaviour.Applies machine learning and neural networks to predict and optimise the mechanical properties of materials, contributing to the development of materials with enhanced performance and reliability.
- 3D (2D + time/temperature/pressure) and 4D (3D+time/temperature/pressure) characterization and modelling of metal-graphite composite microstructures, especially in case of alloys used in large wind turbines and advanced maritime engines.
- Phase transformations metals, intermetallics and non-metals during thermos-mechanical processing.
- Characterization and modelling the functional behaviour in high temperature shape memory alloys, especially NiTi, ZrCu and NiMn base alloys.
- Characterization and modelling of functional behaviour in ferromagnetic shape memory alloys for solid state refrigeration
- Understanding microstructure-property correlations in Nickel, Cobalt, Iron and Aluminium base alloys using advanced in situ X-rays, neutrons and electron.
- Real and reciprocal imaging of microstructure evolution during thermo-mechanical processing of intermetallics and non-metals.
- Understanding the evolution of microstructure in natural high temperature – high processes processes such as vesiculation in magmas during eruption
Bo obtained a BSc degree from Beihang University between 2003 and 2007, specialising in Materials Engineering. He then carried out his PhD in Department of Engineering at University of Bristol, between 2007 and 2011, followed by taking two Post-doctoral Research Associate posts in 2011 in Bristol’s High Temperature Centre and then in 2013 in Materials Performance Centre at University of Manchester. In 2015, Bo moved to a Lectureship at Coventry University, being promoted to Senior Lecturer in 2017. He was awarded a 5-year EPSRC Early-career Fellowship in Nuclear Fission in 2018. Bo became a Professor of Engineering Materials at University of Leicester in March 2019.
Nuclear Engineer with a Ph.D. in Mechanical Engineering with over 10 years experience in R&D in the nuclear industry. His main research focus is on surface integrity, especially in chemically aggressive environment. He has good experience in hybrid machining (ultrasonics) and HPC of refractory metals, ceramics, and in general difficult to machine materials. Certified XRD operator, with experience also in other advanced investigative techniques (SEM, laser microscopy, etc).
I am developing Pulse Reverse Plating technique to allow electrodeposition of any metallic matrix nanocomposite coating. The technique requires design of bath chemistry to meet a set of homegrown criteria. So far we have demonstrated the technique in cobalt, nickel and copper electroplating systems.
I have developed a powder metallurgical processing route to make compacts with high concentrations of nanoparticles which may then be added to magnesium and aluminium casting alloys to produce dramatic increase in strength and ductility. This will allow lightweighting of components which is attractive to auto and aerospace sectors. I have a new interest in the development of lightweight brick fascia materials for the construction industry. I am originally a chemist and have successfully transitioned to materials. I have a broad interest in surfaces and coatings and their interaction with the environment.
I am a mechanical engineer focused on materials science failure analysis mechatronics and A.I. Got my undergraduate degree from the University of West Attica (formerly known as T.E.I. of Piraeus). Following that I obtained my MSc degree in Advanced Industrial Manufacturing Systems from Kingston University and started my PhD research at the University of Leicester in 2014. I also did my Post-Doc in Leicester and now I have joined the School of Engineering as a lecturer. I am very keen on exploring multiple aspects of engineering and collaborating with academics from multiple disciplines in the University. I believe that mentally and academically challenging subjects and research are the best way to grow and improve. I always look forward to what the future holds.
Computational multiscale and multiphysics modelling of different material systems including polycrystalline solids, rubber and rubberlike materials biological tissues
Understanding fundamental material science of advanced thermoelectric materials, design and development of novel Space Nuclear Power systems, as well as advanced spectroscopy and microscopy.
Thermofluids
- Thermomechanical energy storage systems
- Combined energy networks
- Development of exergy and exergoeconomic analysis methods
- Design and optimisation of cooling systems for high-pressure die tools for aluminium casting to achieve uniform cooling using lattice structure inserts
- Develop a topology optimisation model to generate cooling channels in 3D-printed casting tools.
- Flow structure and analysis of fluid flow on shrouded inversed blades for micro wind turbines and rotating machines using flow visualisation, PIV and CFD.
- Liquid film break-up and spray characterisation of rain for soiling and water management on electric vehicles using advanced laser measurement techniques and CFD.
- Optimisation of micro axial wind focus turbine for low wind speed sites.
- Sustainable biofuels, including biodiesels (methyl esters) and bio aviation fuels (biojet).
- Laser-based diagnostic techniques in fluids, including PIV, LII, LIF, laser extinction and LDA.
- Soot formation and emission from combustion.
- Novel nano material synthesis in flame environments
- Modelling air and particle flow in human airways (pollutants, drug delivery), for healthy and diseased human lungs.
- Experimental and CFD modelling studies of swirling flows for combustion, turbomachinery and aftertreatment applications.
- Experimental and modelling studies of flow and heat transfer in multi-channel devices (catalysts, filters, heat exchangers).
- Development and experimental validation of new modelling techniques for a range of industrial applications (such as filtration or swirling flows).