786 Projects, page 1 of 158
The unmanned aerial vehicles (UAVs) are new types of user equipment connected to cellular networks with promising revenue through additional new subscribers and use cases, especially for aviation sector. In addition, UAVs are accepted as an extension to base stations by boosting coverage, spectral efficiency and user quality of experience. In this context, the main aim of this project is to provide high quality of data link and smooth UAVs connectivity into cellular network infrastructure. The UAVs allow rapid deployment of a multi-hop communication backbone in challenging environments with applications for public safety, delivery and monitoring. Therefore, Unmanned aerial vehicles (UAVs) can be used as complementary infrastructure to provide wireless services for the ground users or they may require wireless connectivity from the ground for a safe and reliable operation. This PhD project aims to study several UAV use-cases covering 5G core networks and to validate UAV/UTM connectivity KPIs for supporting such challenging. The project will drive UAV and 5G networks to a win-win position, on one hand by showing that 5G is able to guarantee UAV vertical KPIs, and on the other hand by demonstrating that 5G can support challenging use-cases that put pressure on network resources. To achieve that we will look to study of where 5G can add value to improve the existing UAV connectivity.
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Tufting is a form of Z-direction reinforcement of composite materials which involves the use of a needle to push a thread through the thickness of a laminate. As the needle retracts, the thread is left, resulting in fibres in the Z direction of an otherwise planar fibre architecture. The dry preform is subsequently infused with thermosetting resin and cured. This new technology for the reinforcement of composite structures shows promising signs of efficient delamination crack retardation (crack between the different plies) and increased damage tolerance. As for any other through the thickness reinforcement, the gain in delamination resistance is accompanied by a knock-down in the in-plane properties of the laminate. Based on the PI's experience on other through the thickness reinforcement technology (namely Z-Fiber pinning), the current project aims to develop predictive modelling tools for the failure of tufted structures appropriate to use in the context of component optimisation. To achieve this objective, it is necessary first to characterise the crack bridging mechanisms of the tufts under different loading conditions. Meso-scale samples will be designed, manufactured and tested to determine the energy absorbed by each tuft. Simultaneously, the reduction of in-plane strength and stiffness will be measured for various tufting density. The bridging characteristics data will be implemented in finite element models and validated against test coupons (delamination tests).Different modelling strategies for the failure of tufted laminates will be tested. A tool that will be used for the prediction of the behaviour of more complex structures based on finite elements will be implemented and an optimisation procedure for the location and density of reinforcement will be developed. Finally, the fully developed tool will be adapted to other forms of through thickness reinforcement (i.e. Z-pinning) and the relative effectiveness of the technologies will be compared.On completion of the project, new methods of testing of 3D composites will be available and tools for the numerical simulation of the behaviour of composite structures containing through the thickness reinforcement will be produced and validated. The use of these tools in the context of optimisation of the location of the Z-direction binders will be illustrated and validated by the simulation, manufacture and testing of structural elements.
Brief definition of research project: The UK water network includes pipes of different materials, diameters and ages. These pipes are buried in different soils and have different external factors influencing their resilience. We know that ground movement breaks pipes, but due to the complexity of the environment and pipe network, predicting the number of bursts, and particularly where they are most likely to occur, remains very challenging. Based on the location, height and canopy of the 28 million trees within our study area, you will calculate areas of 'tree influence' on soil moisture, and use these to predict highly local ground movements. It is expected that the incorporation of the new tree datasets into infrastructure-environmental models will enhance our ability to predict the location of burst pipes. Taking a large, historic 10 year, case study in the Anglian Water region, this will be the first time environmental-water infrastructure models based on soil, weather and tree variables will have been developed and tested on this scale. You will test the relationships hypothesised using a range of statistical methods to assess the relative contributions of the infrastructure and environmental variables to each infrastructure failure. The changing impact of trees on local soil moisture under future climates will also be modelled. Due to the age and variable integrity of the UK water network, this work will be of national importance in as it will help to focus the limited resources available for repair and replacement in the areas which will deliver the maximum benefit in reducing leakage and associated energy costs, collateral damage to nearby infrastructure, and minimising the potential impact of failures to both humans and the environment.
The falling costs and the extremely high yield of genomic data from next generation sequencing (NGS) technology made it the method of choice for studying complex plant genome species. Using NGS, we are now able to produce more than one billion sequencing reads within the timeframe of a few days, which has paved the way forward for tens of thousands of biological events and environmental stress responses in parallel. In order to maximise benefit from these rapid advances in sequencing technologies, Next-generation sequencing demands next-generation phenotyping. For this reason, Cranfield University and Agri-Epi Centre have recently acquired a state-of-the-art phenotypic platform installed within a purpose-built glasshouse facility as part of a £5.5m investment. The glasshouse hosts a LemnaTec multi-sensor platform (only two other similar platforms exist worldwide) that allows for real-time assessment of crop parameters through RGB, hyperspectral, fluorescence and thermal cameras and a 3D laser scanner. This platform will allow to monitor, in real-time, the genotypic responses for various plant varieties across a number of environmental stresses and soil conditions.