NASA Glenn Icing Research Tunnel: 2019 Cloud Calibration
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Icing↗
Engineering topics
Emily Timko
Publications and source records attributed to Emily Timko.
NASA Icing Update
NASA icing research summarizes work in the following areas: facility updates for the Icing Research Tunnel and Propulsion Systems Laboratory, engine icing, and simulation & experimental tools.
Icing↗
Analysis of Supercooled Large Drop Velocity Measurement in the NASA Icing Research Tunnel
An experiment was conducted in the Icing Research Tunnel (IRT) at the NASA Glenn Research Center to measure the velocity of supercooled large drops (SLD) in the test section of the tunnel. Previous experiments in the IRT suggested that supercooled large drops passing through the test section of the tunnel do not move at the same velocity as the surrounding air flow. The difference between drop velocity and tunnel air velocity is called slip velocity. The slip velocity is important for determining the exact nature of SLD icing simulation in the IRT. It can impact the ice growth process because of its effect on drop cooling rate during transit from the spray bars to the test section. It can also affect the amount of splashing that occurs upon impact. Slip velocity is an important flow parameter to determine how far the current facility capabilities can be extended into the SLD regime. Initial measurement data analysis of the drop velocities indicates that drops with diameter larger than about 100 to 200 µm experience velocity slip.
SLD↗
Statistical Process Control and Analysis on the Water Content Measurements in NASA Glenn’s Icing Research Tunnel
The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts. Data are presented to display the control capability to meet defined liquid water content specifications of the IRT with the Multi-Element Sensor mounted in the center of the test section.
Statistical Process Control↗
Characterization of Large Drop Velocity in the NASA Icing Research Tunnel
This presentation presents experimental work conducted in the Icing Research Tunnel at NASA Glenn Research Center to characterize the velocity of large drops in the tunnel test section. Some icing spray clouds with large-sized drops were generated with Mod1 nozzles at low nozzle air pressure of 2 to 4 psig for various tunnel air speeds. Drop diameters and drop velocities were measured via high-resolution imaging with a Particle Imaging Particle Tracking Velocimetry probe developed by Artium Technologies. The probe was mounted at four different locations aligned with the centerline of the test section from near the end of the contraction to the constant height test section part of the tunnel. CFD analyses were performed. It showed that the probe head geometry affects the local air flow between the prongs and in front of the probe. Initial analysis of the air velocity data during the test also indicated that the probe mounting stand has blockage effect on the local tunnel air velocity measurement by a Pitot static probe affixed on the mounting plate. Those findings were later verified in the Icing Research Tunnel using a new Pitot probe design with a linear motion system to measure the local tunnel air velocity with and without the probe. As a result, additional drop trajectory simulations as airflow moving towards the probe head were run for a Langmuir-D 7-bin drop size distribution of a spray cloud with a nominally large value of medium volumetric diameter. The simulation results helped identify a critical drop-size threshold of 300 µm above which the velocities of larger drops are not affected by the adverse pressure gradient generated by the probe head due to their large drop inertia. From the dimensional analysis of the drop velocity measurement data obtained, it showed that at the tunnel test section reference location a generalized empirical correlation was developed for the non-dimensional drop velocity as a function of the non-dimensional corrected drop diameter independent of the actual spraybar pressure settings and the tunnel air speeds. The generalized curve-fit correlation showed that the drop velocity was universally asymptotic to about 86 percent of the corresponding tunnel air speed at the test section reference location for the largest drop diameter captured by the probe. Further evaluation of this correlation is recommended to assess its applicability for Supercooled Large Drop icing scaling applications in the Icing Research Tunnel.
SLD↗