STREAM - Snake robotics for on-engine advanced thermal mapping

Principal investigator: Kaspar ALTHOEFER
Funding source(s): Innovate UK
 Start: 01-05-2021  /  End: 31-10-2022
 Amount: £89,835
Temperature profile on turbine blade**Motivation:** Decarbonisation and higher engine efficiencies are the main drivers for aircraft propulsion over the coming three decades. Higher efficiencies can be achieved with higher firing temperature. Net Zero Carbon flight will most likely utilise hydrogen based fuels. Both pathways require the design of new more robust materials and cooling schemes to withstand the harsh thermal conditions. Hence a complete knowledge of temperature distributions within the engine will be essential for the design process of modern aircraft engines. **Solution:** Sensor Coating Systems (SCS) currently provides an enabling temperature mapping technology which assists customers to validate new designs in the aviation and power generation gas turbine industry. The technology uses a combination of temperature memory materials, advances in optical instrumentation and automation to generate digitised maps with hundreds and thousands of data points. Currently the measurements are conducted 'off-engine': the components are interrogated in a laboratory which requires the disassembly of the engine -- a costly and time consuming exercise! This project will enable the measurements to be carried out 'on-engine' ('on-wing') using a highly specialised snake-robot. The development will include the application of artificial intelligence and deep learning methods to achieve the same high fidelity data maps as obtained in the lab today. **Benefits**: Not only will the new technology enable the engine manufacturer to realise a significant reduction of testing costs,, but the technology will also accelerate the development times for greener engine designs as the digitised data will be available more rapidly and will inform the designs of next generation engines. This will be crucial for the rapid deployment of hydrogen fuelled engines. **Consortium:** SCS and Queen Mary University London (QMUL), both situated in the east end of London, are forming a highly technical and culturally diverse team to deliver this project. QMUL will provide a wealth of world leading robotics expertise with advanced machine learning methods, whilst SCS has a deep understanding of the measurement technology, associated instrumentation, end-user requirements and existing customer base. **Commercialisation and job generation:** SCS provides a measurement service to its global client base, this project will enable the company to develop a new revenue stream based on technology licensing with appropriate technical support. A successful project will see SCS staff number grow from 13 (2020) to 30-40 (2023). QMUL and SCS will form closer links to support PhD or MSc students working on the technology and provide highly-skilled employment opportunities within SCS.