Using Artificial Intelligence to study variations in gas turbine performance.
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Using Artificial Intelligence to study variations in gas turbine performance.
CoPED ID
811dba0e-c945-40ae-a33b-6606b5352ca1
Status
Active
Value
No funds listed.
Start Date
Sept. 23, 2020
End Date
Sept. 29, 2024
Description
Artificial Intelligence (AI) allows the rapid processing of images. In the context of gas turbines this means that scans and video imaging of engine parts could be automatically assessed for variations in shape that can have significant impact of fuel consumption and engine life. In this project, data from Rolls-Royce will be combined with the latest AI and data mining tools, CAD descriptions, geometry morphing and 3D analysis codes to inform engineers on the impact of variations in geometry on engine performance. The aim is both to design parts that are more resistant to performance degradation and also to inform service teams of the best repair and replacement strategies for engines currently in use.
| University of Southampton | LEAD_ORG |
| Rolls-Royce plc | STUDENT_PP_ORG |
| David Toal | SUPER_PER |
| Joshua Bamford | STUDENT_PER |
Subjects by relevance
- Data mining
- Motors and engines
- Computer-aided design
- Gas turbines
- Gas engine
- Imaging
Extracted key phrases
- Gas turbine performance
- Artificial Intelligence
- Engine performance
- Engine part
- Performance degradation
- Engine life
- Use
- Variation
- Late AI
- Datum mining tool
- Rapid processing
- Significant impact
- Geometry morphing
- 3d analysis code