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At least 37 records · Page 2

GlennICE Simulation of 24, 28 and 36 Inch Diameter eVTOL Propellers in Forward Flight

Flow solutions and water collection results are presented for three different propeller sizes. Flow solutions were generated using the NASA FUN3D software, and water collection was simulated using NASA GlennICE software. The geometries considered represent experimental articles that have been tested in the NASA Icing Research Tunnel. Each configuration has four blades. For the experiment, the same spinner centerbody is used for each propeller size. The different sized blades are similar for radii larger than about 40% of total span. Operating conditions were chosen to match operating points where experimental data was collected. Results are presented for both single bin simulations, as well as 7-bin Langmuir D distributions. For 80 microns MVD the Langmuir D distribution showed small differences compared to the single bin. For 15 microns MVD the Langmuir D distribution had a larger impact, especially on the spinner. In the experiment, the centerbody was unchanged as propeller size was changed. In this paper, additional simulations were completed with the 36 inch case perfectly scaled down to 24 and 28 inch. The perfect geometric scaling allows for an assessment of the effect of constant centerbody size on the results. While slight differences in pressure distribution on the propeller are visible between scaled and non-scaled centerbody, the effect seems quite minimal regarding water collection. All simulations were run very cold to ensure rime ice, since handling runback water in the non-inertial frame is beyond the scope of the present work. Ice shapes were generated using a single time step growth. The total mass on the blade and spinner was generally underpredicted for 15 microns MVD, and overpredicted for 80 microns MVD. When comparing ice shapes at operating conditions the numerical results produce very similar ice shapes.

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↗

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↗

GlennICE Simulation of 24, 28 and 36 Inch Diameter eVTOL Propellers in Forward Flight

Flow solutions and water collection results are presented for three different propeller sizes. Flow solutions were generated using the NASA FUN3D software, and water collection was simulated using NASA GlennICE software. The geometries considered represent experimental articles that have been tested in the NASA Icing Research Tunnel. Each configuration has four blades. For the experiment, the same spinner centerbody is used for each propeller size. The different sized blades are similar for radii larger than about 40% of total span. Operating conditions were chosen to match operating points where experimental data was collected. Results are presented for both single bin simulations, as well as 7-bin Langmuir D distributions. For 80 microns MVD the Langmuir D distribution showed small differences compared to the single bin. For 15 microns MVD the Langmuir D distribution had a larger impact, especially on the spinner. In the experiment, the centerbody was unchanged as propeller size was changed. In this paper, additional simulations were completed with the 36 inch case perfectly scaled down to 24 and 28 inch. The perfect geometric scaling allows for an assessment of the effect of constant centerbody size on the results. While slight differences in pressure distribution on the propeller are visible between scaled and non-scaled centerbody, the effect seems quite minimal regarding water collection. All simulations were run very cold to ensure rime ice, since handling runback water in the non-inertial frame is beyond the scope of the present work. Ice shapes were generated using a single time step growth. The total mass on the blade and spinner was generally underpredicted for 15 microns MVD, and overpredicted for 80 microns MVD. When comparing ice shapes at operating conditions the numerical results produce very similar ice shapes.

Aircraft Icing↗

An Automated Refinement Process for Particle Trajectory Methods in GlennICE

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.

William B Wright↗

An Automated Refinement Process for Particle Trajectory Methods in GlennICE

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.

William Wright↗

Roughness Parameter Optimization of the McClain Model in GlennICE

Aircraft icing remains a significant threat to aviation safety. Software that predicts the impingement and ice accretion on full aircraft geometries and aircraft components are in demand and NASA Glenn is committed to produce software that meets this need. One of the key parameters affecting an accurate prediction of iced geometry is the effect of ice roughness on the heat transfer coefficient. While many efforts have been made to implement the roughness in the flow solver, this report takes a correlation for roughness height distribution that is based on experimental measurements and demonstrates how to relate those measurements to an augmentation to the heat transfer coefficient provided by the flow solution. The outcome of this effort was the calibration of defaults for user supplied parameters to this correlation through comparison with 95 large glaze conditions from experiment by adjusting user-supplied parameters in the roughness augmentation equation.

Aircraft Icing↗

Analysis of Ice Mass Growth Over Time on the CRM65 Midspan Hybrid Model

The Aeronautics Research Mission Directorate at NASA is developing and applying tools to enable future technologies towards sustainable flight. Aircraft icing has been identified as a potential barrier to entry into service for innovative designs necessitating improvements to computational ice accretion tools. NASA is developing the Glenn Icing Computational Environment (GlennICE) to address deficiencies in the computational modeling capabilities of previously developed ice accretion solvers. To benchmark and improve the ability to model highly three-dimensional ice accretion, high quality validation data against experimental data is required. The CRM65 Midspan Hybrid geometry was previously tested at the NASA Icing Research Tunnel to generate experimental data for swept wing geometries typical for commercial transport aircraft. As a part of a 2018 icing test campaign, experimental data characterizing the relationship between ice accretion time and ice mass growth was obtained and can be leveraged for use in validation of computational tools. The desire for computational ice accretion solvers to predict ice shapes profiles accreted experimentally has often overshadowed the comparison to the mass and bulk volume of ice accreted. To address this deficiency, an analysis is presented in which GlennICE is applied to simulations of the CRM65 Midspan Hybrid model tested in the NASA Icing Research Tunnel. Results from the computational fluid dynamics simulations compared favorably to the experimental pressure coefficient data, thus validating the modeling setup. The experimental data showed excellent repeatability for the 15.0 minute accretion time. The comparisons between the experimental and computational ice mass over time showed good agreement up to 10.0 minutes after which the ice mass was underpredicted. The experimental ice mass was largely linear with some nonlinear data. The bulk volume of ice accreted experimentally compared well to GlennICE for the scanned ice shapes and mean combined cross section ice shapes, but was underpredicted for the maximum combined cross section ice shapes at longer accretion times. The experimental minimum combined cross section, mean combined cross section, and maximum combined cross section profiles when compared to GlennICE show good agreement for the mean combined cross section up to 15.0 minutes. The analyses show that with a single-shot method, GlennICE currently underpredicts the ice mass for longer accretion times, is not able to match the bulk volume of the maximum combined cross section due to dominating scallop features, and future work is required to generate a more generalized ice bulk density model.

Icing↗

Analysis of Ice Mass Growth Over Time on the CRM65 Midspan Hybrid Model

The Aeronautics Research Mission Directorate at NASA is developing and applying tools to enable future technologies towards sustainable flight. Aircraft icing has been identified as a potential barrier to entry into service for innovative designs necessitating improvements to computational ice accretion tools. NASA is developing the Glenn Icing Computational Environment (GlennICE) to address deficiencies in the computational modeling capabilities of previously developed ice accretion solvers. To benchmark and improve the ability to model highly three-dimensional ice accretion, high quality validation data against experimental data is required. The CRM65 Midspan Hybrid geometry was previously tested at the NASA Icing Research Tunnel to generate experimental data for swept wing geometries typical for commercial transport aircraft. As a part of a 2018 icing test campaign, experimental data characterizing the relationship between ice accretion time and ice mass growth was obtained and can be leveraged for use in validation of computational tools. The desire for computational ice accretion solvers to predict ice shapes profiles accreted experimentally has often overshadowed the comparison to the mass and bulk volume of ice accreted. To address this deficiency, an analysis is presented in which GlennICE is applied to simulations of the CRM65 Midspan Hybrid model tested in the NASA Icing Research Tunnel. Results from the computational fluid dynamics simulations compared favorably to the experimental pressure coefficient data, thus validating the modeling setup. The experimental data showed excellent repeatability for the 15.0 minute accretion time. The comparisons between the experimental and computational ice mass over time showed good agreement up to 10.0 minutes after which the ice mass was underpredicted. The experimental ice mass was largely linear with some nonlinear data. The bulk volume of ice accreted experimentally compared well to GlennICE for the scanned ice shapes and mean combined cross section ice shapes, but was underpredicted for the maximum combined cross section ice shapes at longer accretion times. The experimental minimum combined cross section, mean combined cross section, and maximum combined cross section profiles when compared to GlennICE show good agreement for the mean combined cross section up to 15.0 minutes. The analyses show that with a single-shot method, GlennICE currently underpredicts the ice mass for longer accretion times, is not able to match the bulk volume of the maximum combined cross section due to dominating scallop features, and future work is required to generate a more generalized ice bulk density model.

Icing↗

Three Dimensional Surface Redefinition Method for Computational Ice Accretion Solvers

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 defined analytical test case.

Computational↗

Three Dimensional Surface Redefinition Method for Computational Ice Accretion Solvers

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.

Computational↗

Comparison of Aircraft Icing Growth Assessment Software

A research project is underway to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has been performed, including additional data taken to extend the database in the Super-cooled Large Drop (SLD) regime. The project shows the differences in ice shape between LEWICE 3.2.2, GlennICE, and experimental data. The project addresses the validation of the software against a recent set of ice-shape data in the SLD regime. This validation effort mirrors a similar effort undertaken for previous validations of LEWICE. Those reports quantified the ice accretion prediction capabilities of the LEWICE software. Several ice geometry features were proposed for comparing ice shapes in a quantitative manner. The resulting analysis showed that LEWICE compared well to the available experimental data.

Wright, William↗

Plans for Ice Crystal Icing Tests Using a 3D Heated Test Article at the NASA Icing Research Tunnel

This presentation describes the plans for ice crystal icing and supercooled water icing tests to be conducted in Fall/Winter 2021 at the NASA Icing Research Tunnel. A test article, whose geometry is representative of an inter-compressor duct and strut region of a turbofan engine, has been designed and fabricated for the study of ice crystal icing physics tests. The Simulated Inter-compressor Duct Research Model (SIDRM) will have the ability to heat surfaces to simulate the warm surfaces of the inter-compressor duct within an engine. The test article is instrumented with heaters, heat flux gauges, thermocouples, and pressure taps to measure icing behavior. The aim of these tests is to generate ice shapes on the SIDRM test article under well-characterized conditions. The results of the testing with the SIDRM model will be used to provide icing physics and validation data for development of the engine icing simulation capabilities in GlennICE, the 3D ice prediction tool. This is intended to be a presentation only, and does not have an accompanying paper.

ice-crystal icing↗

Description of Cloud Characterization and Icing Test for a 3D Heated Test Article at the NASA Icing Research Tunnel

This paper describes the cloud characterization and icing tests conducted with a 3D heated test article in Winter/Spring 2022 at the NASA Icing Research Tunnel. The intent is to present analyzed results from these recently conducted tests in a future technical paper. The test article, whose geometry is representative of an inter-compressor duct and strut region of a turbofan engine, has been designed and constructed to study the physics of supercooled water icing and ice crystal icing. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, a scale to measure ice mass, and other instruments will aid in characterizing the icing behavior. The aim of these tests is to generate ice accretions on the SIDRM test article under well-characterized conditions. To that end, a suite of instruments was utilized to characterize the ice crystal clouds at the test section in a separate test series. The icing measurements collected during the SIDRM model tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assess the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost effective way.

Ice crystal icing↗

Description of Cloud Characterization and Icing Tests for a 3D Heated Test Article at the NASA Icing Research Tunnel

This paper describes the cloud characterization and icing tests conducted with a 3D heated test article in Winter/Spring 2022 at the NASA Icing Research Tunnel. The intent is to present analyzed results from these recently conducted tests in a future technical paper. The test article, whose geometry is representative of an inter-compressor duct and strut region of a turbofan engine, has been designed and constructed to study the physics of supercooled water icing and ice crystal icing. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, a scale to measure ice mass, and other instruments will aid in characterizing the icing behavior. The aim of these tests is to generate ice accretions on the SIDRM test article under well-characterized conditions. To that end, a suite of instruments was utilized to characterize the ice crystal clouds at the test section in a separate test series. The icing measurements collected during the SIDRM model tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assess the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost effective way.

Ice crystal icing, heated test article, engine ici↗

Icing Physics Studies Using the 3D SIDRM Test Article: Aerodynamic and Supercooled Liquid Icing Analysis

In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation capability. Experimental data is required for development of icing physics models and simulation validation. To that end, this paper presents the analysis of the supercooled liquid icing data subset from tests conducted in 2022 at the NASA Icing Research Tunnel that studied both supercooled water and ice-crystal icing. The test article that was utilized replicated 3D geometrical features of an inter-compressor duct and strut region of a turbofan engine. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with pressure taps, heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, and a scale to measure ice mass were utilized to characterize the icing behavior. The aim of these tests was to generate ice accretions on the SIDRM test article under well-characterized supercooled liquid icing and ice crystal icing conditions. This paper discusses measurements related to aerodynamic testing and supercooled liquid icing tests that were conducted. Aerodynamic measurements were analyzed and compared to computational simulations and were found to be in good agreement for the range of airspeeds (50 to 230 knots) and angles of attack (0 to 4°) tested. Various parametric sweeps were conducted during the supercooled liquid icing portion of the test entry (cloud median volumetric diameter ranged from 15 to 90 µm, total air temperature from -3 to -17 °C, angle of attack from 0 to 4°, and accretion time from 5 to 20 min). These sweeps were performed to measure that parameter’s impact on ice accretion size, location (icing extent), characteristics (such as glaze/rime ice and shedding behavior), and test article surface temperature. Analysis of the test data showed that clouds composed of larger drops, colder air temperatures, smaller angles of attack, and longer spray times were the primary parameters that resulted in accretions with greater ice mass. Test article angle of attack and cloud droplet size influenced the location of ice accretion as these two parameters directly impact collection efficiency. With respect to icing characteristics, total air temperature dictated icing type, and smaller cloud drop size along with warmer air temperatures resulted in greater amounts of ice shedding. Surface temperature increased during ice accretion from the release of latent (fusion) heat, where total air temperature and cloud drop size impacted the amount of surface temperature change. The icing measurements collected during the SIDRM tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assesses the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost effective way.

supercooled liquid icing↗

Computational Icing Analysis on NASA’s SIDRM Geometry to Investigate Collection Efficiency

Computational icing analysis results were compared to experimental icing tunnel data including aerothermal (e.g. dry air) and supercooled water droplet rime-ice conditions from tests conducted in early 2022 at the NASA Icing Research Tunnel (IRT). The Simulated Intercompressor Duct Research Model (SIDRM) test article was used in this study, and its geometry represents the inter-compressor duct region of a turbofan engine. The test article’s purpose is to study the physics of supercooled water icing and ice crystal icing. This study compared three different icing codes: FENSAP-ICE (Eulerian approach), LEWICE3D (Lagrangian approach), and GlennICE (Lagrangian approach). All three icing codes were conducted on SIDRM’s complex body flow-field and compared to different experimental supercooled water rime runs. The test article instrumentation (pressure taps, thermocouples, etc.) and 3D laser scans of final ice shapes were used to compare against the different icing code simulations. The overall objectives are to understand how the icing codes handle capturing collection efficiency on the complex test article’s unheated surfaces. In the aerothermal cases, pressure tap readings matched the CFD results, but dry air CFD underpredicted thermocouple readings. Collection efficiency results from all three icing codes matched well together on the main body leading edge, main body slope, and the strut leading edges. All three icing codes underpredicted the final ice shape using a single-shot constant ice density approach, with more difficulty coming from the strut leading edge ice shape due to the swept wing like flow field. NASA’s overall goal for this effort is to develop computational icing tools to assist in the design and certification of engines for flight in icing conditions.

Supercooled icing, SIDRM, aerodynamics, computatio↗