Objective
The headline objective of this project is to develop a suite of advanced sensors, instrumentation and related systems in order to contribute to the development of the next generation of green and efficient gas turbine engines (AAT.2012.1.1-3&4).
Sensors are a vital enabling technology for gas turbines and are critical to validation of design tools, new products, engine control, and health monitoring. The limitations of sensors in terms of survival temperature, accuracy, stability, and degradation limit where measurements are made during development and the operating ceiling of the gas turbine. Engines are run with safety margin in order to safeguard components against mechanical failure. Consequently, they are not run at their most optimal, which impacts overall efficiency. For example, a 10C uncertainty on turbine entry temperature changes the specific fuel consumption by 0.2%. Also a 0.2mm change in turbine tip clearance changes the specific fuel consumption by 0.4%. It is believed that with better sensing techniques, in excess of 500,000 tonnes of kerosene could be saved per annum, which equates to a CO2 saving of over 1.5 millions tonnes. Despite some successes in recent research, it has become clear that the capability gaps are not closing quickly enough. Further research in to sensors and instrumentation is, therefore, absolutely essential if the capability gaps are to be filled at an adequate rate.
The STARGATE project intends to target these critical gaps and create the biggest impact possible within the constraints of the Call budget. The project will develop a range of advanced new sensors for high temperature gas path, surface, and structural measurements. The project also contains some detailed studies on wireless sensing. The sensors will be validated using both laboratory and rig trials to define their performance against specific targets. The project is being lead by Meggitt UK and includes 5 of the EU’s foremost gas turbine manufacturers.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Call for proposal
FP7-AAT-2012-RTD-1
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Funding Scheme
CP-FP - Small or medium-scale focused research projectCoordinator
CV7 9JU Coventry
United Kingdom
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Participants (15)
N1 9FX London
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15827 Blankenfelde-Mahlow
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75015 Paris
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46181 Trollhaettan
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80333 Munchen
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1640 Sint-Genesius-Rode
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1752 Villars S Glane
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OX11 0QX Didcot
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91120 Palaiseau
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CB2 1TN Cambridge
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412 96 Goteborg
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CV1 5FB Coventry
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DE24 8HP Derby
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97074 Wurzburg
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LE11 3TU Loughborough
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