Assessment of Additive Manufacturing Repeatability Through Adiabatic Effectiveness Measurements
Abstract Additive Manufacturing has demonstrated significant potential to produce components with complex geometries and small dimensions. This capability has sparked growing interest in recent years, leading to substantial efforts aimed at applying Additive Manufacturing (AM) methods to enhance film cooling techniques in turbine blade cooling systems. This work investigates the performance and repeatability of film cooling holes fabricated using a Laser Powder Bed Fusion (LPBF) technique, focusing on their cooling effectiveness. The work analyses the performance of a novel hole developed in the Design-for-Additive-Manufacturing framework. The proposed hole has a strongly three-dimensional shape with a reduced length compared to traditional holes, in order to inject the coolant further upstream on the target surface, and an expanding section inspired by the traditional fan-shaped holes. Pressure Sensitive Paints (PSP) measurements were performed for multiple flat plates housing a single row of 11 holes. The adiabatic effectiveness contours downstream of each hole were found to exhibit a different variability at each tested blowing ratio ranging between 0.25 and 2.00, especially at high blowing ratio values. A statistical analysis is performed to quantify the variability of cooling effectiveness, relating thermal performances deviations to manufacturing failure in order to assess the hole robustness across different operating conditions. Results show that, while AM enables the production of complex geometry, repeatability remains a challenge, with even a slight variation in the hole geometry strongly jeopardizing cooling performance. Moreover, the robustness in terms of film effectiveness is not constant varying the coolant conditions and reduces at high blowing ratios.
Authors
- Bruno Facchini (ORCID: https://orcid.org/0000-0003-4489-4256)
- Alessio Picchi (ORCID: https://orcid.org/0000-0003-4389-4537)
- Lorenzo Winchler (ORCID: https://orcid.org/0000-0001-7524-709X)
- Niccolò Castelli (ORCID: https://orcid.org/0009-0006-1295-7178)
- Francesco Morante
Institutions
- Baker Hughes (United States) (US)
- University of Florence (IT)
Publication Details
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1115/gt2025-152942
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00