Engineering topics
Publications and source records attributed to Christopher Porter.
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.
In 2020, NASA’s Aeronautics Research Mission Directorate commissioned a study of the icing research area to provide a broad and comprehensive assessment of priority needs for NASA and enduring needs for the aviation community. Priority needs were those that supported four key focus areas for NASA Aeronautics—Transonic Truss-Braced Wing, Electrified Aircraft Propulsion, Small-Core Turbine Engine, and High-Rate Composite Manufacturing—as well as other priority areas, such as Advanced Air Mobility, Certification by Analysis, and Commercial Supersonic Technology. Enduring needs were the additional long-term capabilities and expertise identified by the aviation community as being critical for NASA to provide. This study is called an Analysis of Alternatives (AoA) because a large number of icing research needs were identified and analyzed to determine the highest priorities for NASA key focus areas and those that will endure into the future. This report offers a detailed description and results of the AoA study for icing research.
Computational tools have been increasing in maturity and are thus commonly used in the engineering design process. Advancements in NASA’s current state of the art computational ice accretion tool are required to tackle the icing challenges of tomorrow. GlennICE, a next generation ice accretion solver, is under development at NASA to tackle these challenges. One of the elements of this migration is transitioning from a quasi-three dimensional strip theory based ice accretion methodology to a fully three dimensional methodology. This requires construction of a method to redefine or extrude a discretized or tessellated surface geometry based on the predicted volumetric ice growth for each tessellated surface triangle. This paper describes the methodology that is employed in the GlennICE software, and assesses the performance of the method in replicating a well definied analytical test case.
This paper presents a preliminary study for the characterization of collection efficiency from icing tests conducted in the Icing Research Tunnel at NASA Glenn Research Center. A test method previously developed for measuring the attachment line maximum collection efficiency of a swept NACA 0012 airfoil model at zero angle of attack was applied to the leading-edge region of a 65%-scale version of the Common Research Model midspan wing section. A correlation for the stagnation line maximum collection efficiency as a function of the modified inertia parameter was obtained with LEWICE3D simulations utilizing a discrete number of drop diameters. It was then compared with the collection efficiency measurement data obtained in the IRT. For the experimental collection efficiency, two ice shape digitization procedures were utilized to extract 2-D chord-wise ice shape profiles, i.e., the Maximum Combined Cross Section or MCCS, and the Minimum Combined Cross Section or Min CCS, at selected span-wise locations from the 3-D scanned ice shapes. The preliminary result showed that the rime ice thickness method can be used to characterize the collection efficiency distribution, for conditions free of ice erosion, in the main ice shape region. However, a high-order statistical processing of the ice scan is needed for estimating the mean ice thickness in areas where feathers are prevalent. From the limited comparison of the experimental and LEWICE3D collection efficiency data in the CRM65 MS model leading edge area, it was shown that the attachment line maximum collection efficiency is reasonably estimated by the best curve-fit correlation in the range of modified inertia parameter tested. A tighter alignment control of the iced and cold clean model scans is needed to improve the comparison. Further evaluation of this correlation is recommended to assess its applicability for Common Research Model type swept wing icing scaling analysis.
Computational methods for ice accretion can simulate the impact of water drops and ice crystals on an aircraft surface in a Lagrangian reference frame or in the Eulerian reference frame. In the Eulerian reference frame, particles are considered a continuous fluid while in the Lagrangian frame individual particle trajectories are calculated. Methods that use the Eulerian reference frame are typically easier to develop as established modules used for continuum mechanics can be leveraged. The Eulerian systems can also be faster since the user does not have to simulate millions of particles in order to achieve good results. It is imperative therefore that a Lagrangian method optimize the release points of trajectories such that accurate solutions can be obtained while minimizing as much as possible the number of trajectories computed. This paper will present a methodology for this refinement process and demonstrate its effectiveness on sample three dimensional test cases.
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.
Numerical simulation results of fluid flow and collection efficiency of the Science Engineering Associates Inc. Multi-Element Probe (Multiwire) and Ice Crystal Detector (ICD) are presented. Fluid flow simulations were conducted using NASA's FUN3D while collection efficiency simulations were conducted using NASA's LEWICE3D software and GlennICE software. For both probes, 3D unsteady flow results were time-averaged. Simulations were computed for free steam velocities ranging from 85 to 185 m/s and freestream total pressures of 44.8 and 93.1 kPa. Collection efficiency results were computed for four spherical particle diameter sizes of 5, 20, 50, and 100 µm. GlennICE collection efficiency results for the multiwire were compared with previously published collection efficiency values calculated using LEWICE3D. Numerical collection efficiency results for the Ice Crystal Detector are presented for the first time.
Numerical simulation results of fluid flow and collection efficiency of the Science Engineering Associates Inc. Multi-Element Probe (Multiwire) and Ice Crystal Detector (ICD) are presented. Fluid flow simulations were conducted using NASA's FUN3D while collection efficiency simulations were conducted using NASA's LEWICE3D software and GlennICE software. For both probes, 3D unsteady flow results were time averaged. Simulations were computed for freestream velocities ranging from 85 to 185 m/s and freestream total pressures of 44.8 and 93.1 kPa. Collection efficiency results were computed for four spherical particle diameter sizes of 5, 20, 50, and 100 µm. GlennICE collection efficiency results for the multiwire were compared with previously published collection efficiency values calculated using LEWICE3D. Numerical collection efficiency results for the Ice Crystal Detector are presented for the first time.
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.
Computational icing tools consist of predicting two distinct problems, the dry air aerodynamics around the iced or uniced vehicle and the accretion of ice due to inclement weather. A desire exists to advance these tools such that they can be reliably used earlier in the design process to limit the need for more costly flight and wind tunnel testing. To achieve these goals the computational tools need to be benchmarked and validated against high quality experimental data sets to raise the software’s Technology Readiness Level. An ongoing collaborative effort between NASA and Boeing Commercial Airplanes is focused on obtaining this required experimental data and subsequently benchmarking and/or validating the tools that predict the aerodynamics around the iced and uniced vehicle. Currently the scope of this effort is focused on the usage of simulated ice shapes to be representative of the iced vehicle. This presentation discusses the generation of those simulated ice shapes.
This presentation provides a status update on select NASA icing research activities for the SAE AC-9C Icing Technical Committee Meeting on May 6, 2024. The updates include the following topics: (1) Propulsion Systems Lab (PSL), (2) Adaptive Icing Tunnel (AIT), (3) Ice Adhesion / Deformed Skin Adhesion Test, (4) GlennICE, (5) Efficient Quiet Integrated Propulsor, (6) Icing Research Tunnel (IRT) CFD Characterization, and (7) Supercooled Large Droplet (SLD) Research.
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.