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ECR Research Fund - Funded Research Projects

The ECR Research Fund is designed to be a flexible research fund for ECRs to support small activities that either supports and develops existing research activities, or develops ECR skills further. Research activities should be aligned with the objectives of the Supergen ORE Hub, further details of which can be found HEREand funded research is directed at offshore wind, wave or tidal energy research. Multi-disciplinary or multi-sectoral proposals are also welcomed. The maximum award size within each ECR Research Fund call is limited to £5,000 per ECR (direct costs only).

Details of future ECR Research Fund calls will be announced through the Supergen ORE Hub’s ECR Network mailing list and website in the future. 

Supergen ORE Hub - First ECR Research Fund Call, October 2019 - Funded Research Projects

We are pleased to announce that the Supergen ORE Hub awarded almost £47,000 to eight Early Career Researchers from our ECR network in our first round of ECR Research Fund allocations. Congratulations to all who were successful in this first funding round. A summary list of the first round of ECR research projects can be found below. Full reports, blogs and slide packs will be published here once they are available. 
 

This industrially-supported (by EA Technology®) research case describes the key role of dynamic braking systems (DBS) in protection of offshore windfarms. It highlights the revolutionary breakthrough in development of high voltage wide-bandgap (WBG) power quantum devices and proposes design of DBS switches with WBG devices to reduce the size, weight and cost of the DBS systems and pave the way for more cost-effective implementation of offshore wind farms. The case aims to build an entry-level lab-scale 5 kV DBS switch with WBG devices and report to ORE Hub the effectiveness of DBS protection units with WBG devices under grid-scale stress levels.

 

This project aims at reducing the cost of energy from Offshore Wind Turbines through novel design and innovation. As wind turbines grow larger to reduce the levelized cost of energy, their blades grow more slender and require significantly thicker airfoils (>30%), specifically towards the root region. Such airfoils however, have reduced maximum lift and are very prone to flow separation. In addition to reduced performance, this also reduces turbine life span, as fatigue loads become crucial. One solution to the challenges caused by the use of very thick traditional airfoils is the use of flatback airfoils. Flatback profiles have blunt trailing edge (TE) and provide higher lift and reduced sensitivity to tripping. There is still limited research on them however, especially with regards (a) to how blunt the TE can be before it is actually detrimental and (b) the possibility for dynamic flow control. The objectives of this project are: 1. To investigate the aerodynamic performance of an airfoil with very thick TE (20% chord) at high Reynolds number (Re ≈ 2M) 2. To investigate the unsteady wake characteristics of the same airfoil with the use of combined unsteady pressure and velocity measurements using microphones and hot wires 3. To examine the possibility of dynamic control of airfoil performance

 

A commitment to a green energy future requires new engineering systems that reduce the cost of environmentally-friendly power generation. Larger wind turbine sizes is one of the most straightforward and effective ways to reducing the wind power generation costs. However large turbines are subject to significant aeroelastic effects from turbulence and gusts. Novel modelling techniques are needed to both accurately simulate such effects and serve as a basis for smart rotor concepts, where low-power and low-maintenance blade-mounted flaps are controlled to reduce fluctuating loads on the blade structure. This will enable savings in blade stiffness and weight, and more importantly huge savings in other components such as drive-train and tower. The ultimate goal is to develop technologies that will facilitate the introduction of larger and lighter wind turbines, along with a substantial reduction in the unit cost for energy production. Areas of focus include aeroservoelastic modelling of smart rotor including control surfaces, model reduction, control design and simulations.

 

This research project aims to develop a graphene nanoplatelets (GNPs) self-sensing structural health monitoring (SHM) system for adhesively bonded joints of fibre-reinforced plastics (FRP). Upon addition of GNPs, the epoxy adhesive becomes electrically conductive. Damage of the GNPs reinforced adhesive layer can be detected by measuring the change of electric signal using Arduino microcontroller. A low power Bluetooth wireless communication system will transmit the structural health signal to a computer. This system can monitor blades at the joints, which can dramatically reduce operational costs, increase reliability and sustainability of turbines.

In Europe, 80% of offshore wind resource is located in places with water depth greater than 60m. This amounts to a potential European capacity of 4000GW, at water depths that are greater than fixed foundation devices can exploit. Floating offshore wind turbines therefore have great potential, both as a source of renewable energy for the UK and as an export market. This project aims to investigate floating offshore wind turbine (FOWT) foundation designs that have the potential to achieve significant cost reductions. This project targets the use of carbon-fibre textile reinforced concrete (CTRC) for floating platforms, where use of a concrete floating foundation allows the majority of supply and logistical activities to be local. A novel self-sensing technique that utilises the contact resistance at the connections of the carbon fibre tows in the mesh was proposed. The main impact of the project will be demonstration of the technical feasibility of self-sensory concrete foundations for floating offshore wind farms, and their potential to reduce construction, deployment, and inspection costs

 

Assessing the likelihood of collisions between deep-diving seabirds and tidal stream turbines is a main component of environmental impact assessments (EIA). Existing models rely on existing measurements of diving behaviour in non-energetic environments, even though diving behaviour in tidal stream environments is probably different. They also do not consider variations in feeding strategies among sites, even though foraging strategies depend on physical conditions and prey communities. These shortcomings are linked to the challenges of recording animal behaviour in tidal stream environments. The resultant uncertainty in EIA can delay or prevent installations, hindering commercial development. Most attempts to overcome these challenges focus on developing technological approaches such as biologging and hydroacoustics, even though these methods are fundamentally unsuitable and/or impractical. The proposed project uses existing knowledge of vulnerable species (black guillemot, European shag) to adapt conventional approaches (shore-based surveys and fish traps) and provide information relevant for the assessment of collision risk in Shetland, UK. Specifically, this information is used to understand whether and why diving behaviour of vulnerable species differs among locations, improving existing models of collision risk and reducing uncertainty in EIA

 

Computational models are generally used for the strategic planning of the O&M activities of offshore renewable farms. However, these models rely on information retrieved a priori, based on existing literature or previous experiences, with little consideration for the data obtained through sensors installed on the devices. The proposed activity aims at exploring the combined use of strategic tools and operational data, highlighting the benefits of including the information obtained from condition monitoring instrumentation at an early stage in the computer-aided definition of the O&M strategy. Despite the approach is valid for most offshore renewable technologies, this activity will put major emphasis on specific solutions for floating offshore wind turbines.

 

 

The research stay at Johns Hopkins University (USA), with Professor Charles Meneveau, will aim to (i) analyse the impact of relative submergence and device separation in tidal arrays’ hydrodynamics and (ii) develop the necessary knowledge and computing skills to start in the field of wind turbine farm simulation. For this research, Large-Eddy Simulations (LES) will be performed using the state-of-the-art Digital Offshore FArm Simulator (DOFAS), being its current version mostly tailored to tidal turbines. DOFAS allows to investigate with great level of detail the complex turbulent flow developed in offshore farm by means of LES and the fluid-structure interaction using an actuator line method to represent the turbines’ rotor, capable of calculating the structural loads.