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| Funder | Innovate UK |
|---|---|
| Recipient Organization | Big Sky Theory Ltd |
| Country | United Kingdom |
| Start Date | Nov 01, 2024 |
| End Date | Jan 31, 2025 |
| Duration | 91 days |
| Data Source | UKRI Gateway to Research |
| Grant ID | 10130713 |
Big Sky Theory (BST) is developing airborne meteorological collection methods and understanding whilst harnessing emerging technology, optimising flight profiles and enhancing post processing.
Working alongside the National Physical Laboratory (NPL) and TUV SUD National Engineering Laboratory (NEL), BST plans to address the fundamental hurdles of airborne data collection using UAVs. Whilst commercially available sensors exist, a lack of research, development, test and evaluation continues to hamper drone-mounted employment techniques.
The Analysis 4 Innovators (A4I) mini-project will span 3 months and include design, assembly, integration, simulation, flight trials and analysis prior to the development of a processing, exploitation and dissemination methodologies. Upon project completion BST will launch a new service providing a range of Use Cases for timely, accurate and low uncertainty airborne meteorological data.
Successful integration onto a UAV is a critical enabler. Through a dedicated literature review of current practices, combined with expert industry know-how, BST will create and integrate an ultra-sonic anemometer ready for trials. The design goal is to reduce vibration, torque and pendulum effect which are known to cause erroneous data and second order effects to linked systems.
Harnessing cutting-edge information technology, BST will join the NEL in researching aircraft induced turbulence and rotor wash via the application of Computational Fluid Dynamics Modelling (CFDM). This stage of the project is designed to de-risk field-work whilst also creating an assured baseline of understanding related to the quadcopter aircraft. The CFDM will identify the required displacement of the sensor in relation to the rotors and an optimised operational configuration.
To validate the CFDM results, BST and the NPL will deploy to a test site to fly the computationally derived configuration as part of a continuous improvement operational evaluation plan. The lessons identified and know-how will be fed back into the software to support post processing analysis.
BST will provide an assured meteorological service to a wide range of Use Cases. The sensor output is a critical enabler in Methane plume mapping, an ongoing project for BST and NPL. Once integrated onto the aircraft and proven through trials, BST will include the sensor within future emissions inspection services.
In addition to Methane management applications, the meteorological capability can support UK forecasting, forestry, renewable energy and agriculture.
This is a truly exciting project exploring and exploiting airborne operations. BST remains committed to the pursuit of innovation through validation and the safe, effective and efficient application of UAV technology.
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