Engineering topics
Publications and source records attributed to Zaid Sabri.
This manual is intended to provide the information necessary for an applications engineer to configure, compile, and execute the GlennICE software. The intent of this document is not to detail the algorithms of the software. The intent of this document is to detail how a user can interact and configure the algorithms of this software in order to produce a desired simulation.
GlennICE (Glenn Icing Computational Environment) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations.
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.
This paper presents experimental work conducted in the Icing Research Tunnel at NASA Glenn Research Center to characterize the velocity of large drops in the test section. Some icing spray clouds with large 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 in the measurement area of the probe 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 next to the stand. Those findings were later verified in the Icing Research Tunnel using a new pitot-static 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 were performed with the airflow moving towards the probe head with a Langmuir-D 7-bin distribution cloud containing large drops. The simulation results helped identify a critical drop-size threshold of 300 μm above which the velocities of larger drops are negligibly 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.
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.
The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.