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Measurement of Liquid Water Content for Supercooled Large Drop Conditions in the NRC’s Altitude Icing Wind Tunnel
ISSN: 0148-7191, e-ISSN: 2688-3627
Published June 10, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
As a result of new regulations pertaining to the airworthiness of aircraft exposed to in-flight icing conditions where maximum water drop size is greater than 100 microns (referred to as Supercooled Large Droplet (SLD) conditions), updates are required to the test facilities and simulations that will enable manufactures to certify their products under these new rules. While a number of facilities report achieving some of the conditions specified in the new regulations, questions remain as to the suitability of the instrumentation used to measure the Liquid Water Content (LWC) and drop size distributions of the SLD icing cloud. This study aims to provide baseline LWC data through ice accretion measurement techniques on a NACA 0012 airfoil and rotating cylinders of varying diameters. This forms part of a collaborative effort between the NRC, NASA Glenn and the Italian Aerospace Research Centre (CIRA), to examine the suitability of current instruments in accurately measuring LWC in clouds where SLD conditions are present.
Calculation of LWC’s from leading edge airfoil ice thickness measurements on the NACA 0012 airfoil were within ±10% of the tunnel LWC setting over the full range of MVD’s tested (20μm to over 300μm). When using rotating cylinders of varying size to measure LWC, it was found that smaller diameter cylinders underestimated LWC of icing clouds containing larger drop diameters compared to the tunnel setting whereas LWC measurement from larger cylinders provided values within 10% of the tunnel setting across the range of MVD’s tested.
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CitationOrchard, D., Clark, C., and Chevrette, G., "Measurement of Liquid Water Content for Supercooled Large Drop Conditions in the NRC’s Altitude Icing Wind Tunnel," SAE Technical Paper 2019-01-2007, 2019, https://doi.org/10.4271/2019-01-2007.
Data Sets - Support Documents
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