Effects of manufacturing tolerances on double-wall effusion cooling

Journal article

As aeroengine designers seek to raise turbine entry temperatures for greater thermal efficiencies, novel cooling schemes are required to ensure that components can survive in increasingly hotter environments. By utilizing a combination of impingement cooling, pin-fin cooling, and effusion cooling, double-wall effusion cooling is well equipped to achieve the high metal cooling effectiveness required for such challenges while keeping coolant consumption at an acceptably low level. However, this high performance can drop off within the variability of common manufacturing tolerances, which can also expose cooling schemes to issues such as hot gas ingestion. This paper uses an experimentally validated low-order flow network model (LOM) to assess the cooling performance of a double-wall effusion cooling scheme employed in a high-pressure turbine nozzle guide vane, subject to the variability of geometric parameters set by their manufacturing tolerances. The relative significance of each geometric parameter is examined by varying it individually and comparing the effects on the cooling performance. A Monte Carlo analysis is then conducted to assess the likelihood of performance variation for a baseline design. Finally, multiple optimization studies are conducted for the cooling scheme, with the simultaneous objectives of reducing coolant usage and maximizing the design tolerances to reduce manufacturing cost, all while maintaining acceptable metal cooling effectiveness and backflow margins.

Authors: van de Noort, M; Ireland, PT; Telisinghe, JC

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: American Society of Mechanical Engineers
• Journal: Journal of Turbomachinery
• Volume: 146
• Issue: 1
• Article number: 011009
• Publication date: 2023-10-31
• Acceptance date: 2023-08-31
• DOI: 10.1115/1.4063731
• EISSN: 1528-8900
• ISSN: 0889-504X
• Language: English
• Keywords: FFR; double-wall effusion cooling; Monte Carlo analysis; flow networks; heat transfer and film cooling; manufacturing tolerances; genetic algorithm optimisation