CFD for Capsule Design
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GlennICE 2.2 Capabilities and Results
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. This paper will document the current capabilities for version 2.1 of this software and provide example cases with comparison to available experimental data.
Icing↗
GlennICE 2.2 Capabilities and Results
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. This paper will document the current capabilities for version 2.1 of this software and provide example cases with comparison to available experimental data.
Icing↗
GlennICE Manual 4.1.0
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.
Icing↗
Improvements to GlennICE Collection Efficiency Algorithm
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. This paper will document recent improvements that reduce the number of trajectories needed to converge on collection efficiency. These improvements are documented using example cases with complex geometries.
Aircraft Icing↗
Improvements to GlennICE Collection Efficiency Algorithm
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. This paper will document recent improvements that reduce the number of trajectories needed to converge on collection efficiency. These improvements are documented using example cases with complex geometries.
Aircraft Icing↗
SmaggIce User Guide
SmaggIce (Surface Modeling And Grid Generation for Iced Airfoils) is one of NASNs aircraft icing research codes developed at the Glenn Research Center. It is a software toolkit used in the process of aerodynamic performance prediction of iced airfoils. It includes tools which complement the 2D grid-based Computational Fluid Dynamics (CFD) process: geometry probing; surface preparation for gridding: smoothing and re-discretization of geometry. Future releases will also include support for all aspects of gridding: domain decomposition; perimeter discretization; grid generation and modification.
Baez, Marivell↗
Further Refinement of the LEWICE SLD Model
A research project is underway at NASA Glenn Research Center to produce computer software that can accurately predict ice growth for any meteorological conditions for any aircraft surface. This report will present results from version 3.2 of this software, which is called LEWICE. This version differs from previous releases in that it incorporates additional thermal analysis capabilities, a pneumatic boot model, interfaces to external computational fluid dynamics (CFD) flow solvers and has an empirical model for the supercooled large droplet (SLD) regime. An extensive comparison against the database of ice shapes and collection efficiencies that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. The complete set of data used for this comparison will eventually be available in a contractor report. This paper will show the differences in collection efficiency and ice shape between LEWICE 3.2 and experimental data. This report will first describe the LEWICE 3.2 SLD model. A semi-empirical approach was used to incorporate first order physical effects of large droplet phenomena into icing software. Comparisons are then made to every two-dimensional case in the water collection database and the ice shape database. Each collection efficiency condition was run using the following four assumptions: 1) potential flow, no splashing; 2) potential flow, with splashing; 3) Navior-Stokes, no splashing; 4) Navi r-Stokes, with splashing. All cases were run with 21 bin drop size distributions and a lift correction (angle of attack adjustment). Quantitative comparisons are shown for impingement limit, maximum water catch, and total collection efficiency. Due to the large number of ice shape cases, comprehensive comparisons were limited to potential flow cases with and without splashing. Quantitative comparisons are shown for horn height, horn angle, icing limit, area, and leading edge thickness. The results show that the predicted results for both ice shape and water collection are within the accuracy limits of the experimental data for the majority of cases.
Wright, William B.↗
Validation Results for LEWICE 3.0
A research project is underway at NASA Glenn to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from version 3.0 of this software, which is called LEWICE. This version differs from previous releases in that it incorporates additional thermal analysis capabilities, a pneumatic boot model, interfaces to computational fluid dynamics (CFD) flow solvers and has an empirical model for the supercooled large droplet (SLD) regime. An extensive comparison of the results in a quantifiable manner against the database of ice shapes and collection efficiency that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. The complete set of data used for this comparison will eventually be available in a contractor report. This paper will show the differences in collection efficiency between LEWICE 3.0 and experimental data. Due to the large amount of validation data available, a separate report is planned for ice shape comparison. This report will first describe the LEWICE 3.0 model for water collection. A semi-empirical approach was used to incorporate first order physical effects of large droplet phenomena into icing software. Comparisons are then made to every single element two-dimensional case in the water collection database. Each condition was run using the following five assumptions: 1) potential flow, no splashing; 2) potential flow, no splashing with 21 bin drop size distributions and a lift correction (angle of attack adjustment); 3) potential flow, with splashing; 4) Navier-Stokes, no splashing; and 5) Navier-Stokes, with splashing. Quantitative comparisons are shown for impingement limit, maximum water catch, and total collection efficiency. The results show that the predicted results are within the accuracy limits of the experimental data for the majority of cases.
Wright, William B.↗
Exploration of Uncertainty in Glacier Modelling
There are procedures and methods for verification of coding algebra and for validations of models and calculations that are in use in the aerospace computational fluid dynamics (CFD) community. These methods would be efficacious if used by the glacier dynamics modelling community. This paper is a presentation of some of those methods, and how they might be applied to uncertainty management supporting code verification and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modelling are discussed. After establishing sources of uncertainty and methods for code verification, the paper looks at a representative sampling of verification and validation efforts that are underway in the glacier modelling community, and establishes a context for these within overall solution quality assessment. Finally, an information architecture and interactive interface is introduced and advocated. This Integrated Cryospheric Exploration (ICE) Environment is proposed for exploring and managing sources of uncertainty in glacier modelling codes and methods, and for supporting scientific numerical exploration and verification. The details and functionality of this Environment are described based on modifications of a system already developed for CFD modelling and analysis.
Thompson, David E.↗
Thermal environment around the Space Shuttle with hot-gas jets for ice suppression
To prevent prelaunch ice formation on the external tank of the Space Shuttle, the final selected approach is to heat the surrounding air with vertical hot-gas jets located at the launch pad. This approach was considerably more cost-effective than other ice suppression methods considered, although its feasibility was not easily discernible due to the complex flowfield interactions. This paper describes how the use of vertical jets was first evaluated with the aid of a computational fluid dynamics (CFD) technique. An existing general-purpose CFD program (PHOENICS) was used to predict the thermal environment around the Shuttle under various jet configurations and wind conditions. The program accounts for effects of buoyancy, turbulence, and structural obstructions in the flowfield. The computed results showed physically plausible and consistent trends. The wind wake effects were found to be significant, and normally resulted in higher temperatures on the leeward side of the tank. High wind conditions were found to be more severe than calm wind conditions. The use of four jets with two different temperatures was identified as a promising option in which the air temperatures were raised sufficiently to prevent ice formation on the external tank, without excessive increase in Orbiter surface temperature. The use of the numerical model also facilitated the selection of test configurations and a test matrix for verifying the approach. Selected results of an experimental verification (by using a 2 percent scale model in a wind tunnel) are also presented.
Singhal, A. K.↗
Ice Accretion Modeling using an Eulerian Approach for Droplet Impingement
A three-dimensional Eulerian analysis has been developed for modeling droplet impingement on lifting bodes. The Eulerian model solves the conservation equations of mass and momentum to obtain the droplet flow field properties on the same mesh used in CFD simulations. For complex configurations such as a full rotorcraft, the Eulerian approach is more efficient because the Lagrangian approach would require a significant amount of seeding for accurate estimates of collection efficiency. Simulations are done for various benchmark cases such as NACA0012 airfoil, MS317 airfoil and oscillating SC2110 airfoil to illustrate its use. The present results are compared with results from the Lagrangian approach used in an industry standard analysis called LEWICE.
Kim, Joe Woong↗
Subsonic Maneuvering Effectiveness of High Performance Aircraft Which Employ Quasi-Static Shape Change Devices
This paper represents an initial study on the use of quasi-static shape change devices in aircraft maneuvering. The macroscopic effects and requirements for these devices in flight control are the focus of this study. Groups of devices are postulated to replace the conventional leading-edge flap (LEF) and the all-moving wing tip (AMT) on the tailless LMTAS-ICE (Lockheed Martin Tactical Aircraft Systems - Innovative Control Effectors) configuration. The maximum quasi-static shape changes are 13.8% and 7.7% of the wing section thickness for the LEF and AMT replacement devices, respectively. A Computational Fluid Dynamics (CFD) panel code is used to determine the control effectiveness of groups of these devices. A preliminary design of a wings-leveler autopilot is presented. Initial evaluation at 0.6 Mach at 15,000 ft. altitude is made through batch simulation. Results show small disturbance stability is achieved, however, an increase in maximum distortion is needed to statically offset five degrees of sideslip. This only applies to the specific device groups studied, encouraging future research on optimal device placement.
Montgomery, Raymond C.↗
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↗
Characterization of Large Drop Velocity in the NASA Icing Research Tunnel
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.
SLD↗
Characterization of the Ignition Over-Pressure/Sound Suppression Water in the Space Launch System Mobile Launcher Using Volume of Fluid Modeling
The Space Launch System (SLS) Vehicle consists of a Core Stage with four RS-25 engines and two Solid Rocket Boosters (SRBs). This vehicle is launched from the Launchpad using a Mobile Launcher (ML) which supports the SLS vehicle until its liftoff from the ML under its own power. The combination of the four RS-25 engines and two SRBs generate a significant Ignition Over-Pressure (IOP) and Acoustic Sound environment. One of the mitigations of these environments is the Ignition Over-Pressure/Sound Suppression (IOP/SS) subsystem installed on the ML. This system consists of six water nozzles located parallel to and 24 inches downstream of each SRB nozzle exit plane as well as 16 water nozzles located parallel to and 53 inches downstream of the RS-25 nozzle exit plane. During launch of the SLS vehicle, water is ejected through each water nozzle to reduce the intensity of the transient pressure environment imposed upon the SLS vehicle. While required for the mitigation of the transient pressure environment on the SLS vehicle, the IOP/SS subsystem interacts (possibly adversely) with other systems located on the Launch Pad. One of the other systems that the IOP/SS water is anticipated to interact with is the Hydrogen Burn-Off Igniter System (HBOI). The HBOI system's purpose is to ignite the unburned hydrogen/air mixture that develops in and around the nozzle of the RS-25 engines during engine start. Due to the close proximity of the water system to the HBOI system, the presence of the IOP/SS may degrade the effectiveness of the HBOI system. Another system that the IOP/SS water may interact with adversely is the RS-25 engine nozzles and the SRB nozzles. The adverse interaction anticipated is the wetting, to a significant degree, of the RS-25 nozzles resulting in substantial weight of ice forming and water present to a significant degree upstream of the SRB nozzle exit plane inside the nozzle itself, posing significant additional blockage of the effluent that exits the nozzle upon motor start leading to detrimental effects. The purpose of the CFD simulations were to i) characterize the location of the IOP/SS water after it is ejected from the IOP/SS nozzles, ii) characterize the interaction of the IOP/SS system with the HBOI system and iii) characterize the interaction of the IOP/SS water with the RS-25 nozzles and the SRB nozzles.
West, Jeff↗
Advancing Test Capabilities at NASA Wind Tunnels
NASA maintains twelve major wind tunnels at three field centers capable of providing flows at 0.1 M 10 and unit Reynolds numbers up to 45106m. The maintenance and enhancement of these facilities is handled through a unified management structure under NASAs Aeronautics and Evaluation and Test Capability (AETC) project. The AETC facilities are; the 11x11 transonic and 9x7 supersonic wind tunnels at NASA Ames; the 10x10 and 8x6 supersonic wind tunnels, 9x15 low speed tunnel, Icing Research Tunnel, and Propulsion Simulator Laboratory, all at NASA Glenn; and the National Transonic Facility, Transonic Dynamics Tunnel, LAL aerothermodynamics laboratory, 8 High Temperature Tunnel, and 14x22 low speed tunnel, all at NASA Langley. This presentation describes the primary AETC facilities and their current capabilities, as well as improvements which are planned over the next five years. These improvements fall into three categories. The first are operations and maintenance improvements designed to increase the efficiency and reliability of the wind tunnels. These include new (possibly composite) fan blades at several facilities, new temperature control systems, and new and much more capable facility data systems. The second category of improvements are facility capability advancements. These include significant improvements to optical access in wind tunnel test sections at Ames, improvements to test section acoustics at Glenn and Langley, the development of a Supercooled Large Droplet capability for icing research, and the development of an icing capability for large engine testing. The final category of improvements consists of test technology enhancements which provide value across multiple facilities. These include projects to increase balance accuracy, provide NIST-traceable calibration characterization for wind tunnels, and to advance optical instruments for Computational Fluid Dynamics (CFD) validation. Taken as a whole, these individual projects provide significant enhancements to NASA capabilities in ground-based testing. They ensure that these wind tunnels will provide accurate and relevant experimental data for years to come, supporting both NASAs mission and the missions of our government and industry customers.
wind tunnel testing↗
Interactive Software System Developed to Study How Icing Affects Airfoil Performance (Phase 1 Results)
SmaggIce (Surface Modeling and Grid Generation for Iced Airfoils), which is being developed at the NASA Glenn Research Center at Lewis Field, is an interactive software system for data probing, boundary smoothing, domain decomposition, and structured grid generation and refinement. All these steps are required for aerodynamic performance prediction using structured, grid-based computational fluid dynamics (CFD), as illustrated in the following figure. SmaggIce provides the underlying computations to perform these functions, as well as a graphical user interface to control and interact with them, and graphics to display the results.
Choo, Yung K.↗