Results for “Computational Icing” — Page 2

NASA NTRS1992

Analysis of iced wings

A method for computing ice shapes along the leading edge of a wing and a method for predicting its aerodynamic performance degradation due to icing is described. Ice shapes are computed using an extension of the LEWICE code which was developed for airfoils. The aerodynamic properties of the iced wing are determined with an interactive scheme in which the solutions of the inviscid flow equations are obtained from a panel method and the solutions of the viscous flow equations are obtained from an inverse three-dimensional finite-difference boundary-layer method. A new interaction law is used to couple the inviscid and viscous flow solutions. The application of the LEWICE wing code to the calculation of ice shapes on a MS-317 swept wing show good agreement with measurements. The interactive boundary layer method is applied to a tapered iced wing in order to study the effect of icing on the aerodynamic properties of the wing at several angles of attack.

Cebeci, Tuncer↗

NASA NTRS2001

Validation of NASA Thermal Ice Protection Computer Codes: The Validation of Antice - Part 3

An experimental program was generated by the Icing Technology Branch at NASA Glenn Research Center to validate two ice protection simulation codes: (1) LEWICE/Thermal for transient electrothermal de-icing and anti-icing simulations, and (2) ANTICE for steady state hot gas and electrothermal anti-icing simulations. An electrothermal ice protection system was designed and constructed integral to a 36 inch chord NACA0012 airfoil. The model was fully instrumented with thermo-couples, RTD'S, and heat flux gages. Tests were conducted at several icing environmental conditions during a two week period at the NASA Glenn Icing Research Tunnel. Experimental results of running-wet and evaporative cases were compared to the ANTICE computer code predictions and are presented in this paper.

Al-Khalil, Kamel M.↗

NASA NTRS1991

A comparison of sea ice parameters computed from Advanced Very High Resolution Radiometer and Landsat satellite imagery and from airborne passive microwave radiometry

AVHRR-derived sea ice parameters from the Bering Sea are compared with those computed from nearly coincident (within 6 hr) Landsat MSS imagery and from the Aircraft Multichannel Microwave Radiometer (AMMR) flown on the NASA DC-8 in order to evaluate the accuracy and reliability of AVHRR-mapped sea-ice concentration and ice edge. Mean ice-concentration differences between AVHRR near-infrared (channel 2) and Landsat MSS data ranged from -0.8 to 1.8 percent with a mean value of 0.5 percent; rms differences ranged from 6.8 to 17.7 percent. Mean differences were larger for AVHRR thermal infrared (channel 4) ice concentrations ranging from -2.2 to 8.4 percent with rms differences from 8.6 to 26.8 percent. Mean differences between AVHRR channel 2 concentrations and the AMMR data ranged from -19.7 to 18.9 percent, while rms values went from 17.0 to 44.8 percent.

Emery, W. J.↗

NASA NTRSDate not supplied

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

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.

Computational Icing↗

NASA NTRSDate not supplied

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

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.

Computational Icing↗

NASA NTRSDate not supplied

Scalability of GlennICE in a Parallel Environment

The Glenn Icing Computational Environment (GlennICE) 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 most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for practical engineering application. With the increasing demand for applying GlennICE for more memory-intensive problems, the scalability of GlennICE has yet to be investigated. This paper is aimed at presenting a method to benchmark the scalability of GlennICE utilizing a relevant engineering problem within a parallel environment. This leads to the final goal of investigating whether an increase in the number of processors utilized results in a linear speedup of the GlennICE software.

Computational Icing, Icing, CFD, MPI↗

NASA NTRS2004

Photoionization of Benzene and Small Polycyclic Aromatic Hydrocarbons in Ultraviolet-Processed Astrophysical Ices: A Computational Study

We employed density functional theory (DFT) calculations to model the photoionization behavior of benzene and small polycyclic aromatic hydrocarbons when they are embedded in a matrix of water ice in order to investigate issues raised by recent experimental work by Gudipati and Allamandola. The ionization energies of benzene, naphthalene, anthracene, and pyrene were found to be lowered by 1.5-2.1 eV in water ice. Low-lying vertical electronic excitation energies were computed with time-dependent DFT for both neutral and ionized species and are found in both cases to be remarkably unaffected by the ice matrix. Chemical behavior in ultraviolet-photoprocessed ices is also discussed, with a focus on electron recombination and pathways leading to phenol and analogous products.

Woon, D. E.↗

NASA NTRS2024

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↗

NASA NTRS2000

Software Released by LEWICE 2.0 Ice Accretion Software Development Project

Computational icing simulation methods are making the transition from the realm of research to commonplace use in design and certification. As such, standards of software management, design, validation, and documentation must be adjusted to accommodate the increased expectations of the user community with respect to accuracy, reliability, capability, and usability. With this in mind, in collaboration with Glenn's Engineering Design and Analysis Division, the Icing Branch of the NASA Glenn Research Center at Lewis Field began a software improvement project focused on the two-dimensional ice accretion simulation tool LEWICE. This project is serving as an introduction to the concepts of software management and is intended to serve as a pilot project for future icing simulation code development. The LEWICE 2.0 Software Development Project consisted of two major elements: software management and software validation. The software management element consisted of identifying features of well-designed and well-managed software that are appropriate for an analytical prediction tool such as LEWICE and applying them to a revised version of the code. This element included tasks such as identification of software requirements, development and implementation of coding standards, and implementation of software revision control practices. With the application of these techniques, the LEWICE ice accretion code became a more stable and reliable software product. In addition, the lessons learned about software development and maintenance can be factored into future software projects at the outset. The software validation activity was an integral part of our effort to make LEWICE a more accurate and reliable analysis tool. Because of the efforts taken to extensively validate this software, LEWICE 2.0 is more robust than previous releases and can reproduce results accurately across several computing platforms. It also differs from previous versions in the extensive quantitative comparisons of its results with a data base of ice shapes that were generated in Glenn's Icing Research Tunnel. The results of the shape comparisons were analyzed to determine the range of meteorological conditions under which LEWICE 2.0 is within the repeatability found for ice shapes obtained from experiments. These comparisons show that the average variation of LEWICE 2.0 from experimental data is 7.2 percent, whereas the overall variability of the experimental data is 2.5 percent. The LEWICE 2.0 Software Development Project resulted in the release, at the recent Icing Branch LEWICE Workshop, of a more useful and robust analysis tool than was previously available to the icing community. The lessons learned from this project will be applied to the Icing Branch s future software development efforts.

Potapczuk, Mark G.↗

NASA NTRSDate not supplied

Scalability of GlennICE in a Parallel Environment

GlennICE (Glenn Icing Computational Environment) is a comptational 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 most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for tractability in a practical engineering application. Although studies have demonstrated a reduction in the amount of work (memory footprint) required, research has yet to systematically investigate the effects of scaling GlennICE. This paper sets out to benchmark the scalability of GlennICE within a parallel environment and investigate if an increase in the number of processors result in a linear speed up.

Computational Icing↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

Integrated Icing Analysis of the D8 "Double Bubble" and the Hybrid Wing Body

A computational icing analysis utilizing LEWICE3D was performed for two next generational aircraft, the D8 “Double Bubble” and the Hybrid Wing Body (HWB). These two geometries were exposed to a variety of simulated clouds spanning the Appendix C and O regimes. Integrated results indicate that the Appendix O clouds generate a significantly higher water catch rate than Appendix C clouds as large radius of curvature components are susceptible to the highly ballistic large droplets found in Appendix O. Classically unprotected components, such as the nose/fuselage, may require anti-icing protection in configurations such as the D8 and HWB that generate lift from these components, dramatically increasing the size, extent, and power requirements of ice protection systems. Integrated results also indicate inclusion of the splashing model can significantly affect predicted water catch rates.

Computational,Icing,Integrated↗

NASA NTRS2013

Modeling Commercial Turbofan Engine Icing Risk With Ice Crystal Ingestion

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that have been attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was degraded engine performance, and one or more of the following: loss of thrust control (roll back), compressor surge or stall, and flameout of the combustor. As ice crystals are ingested into the fan and low pressure compression system, the increase in air temperature causes a portion of the ice crystals to melt. It is hypothesized that this allows the ice-water mixture to cover the metal surfaces of the compressor stationary components which leads to ice accretion through evaporative cooling. Ice accretion causes a blockage which subsequently results in the deterioration in performance of the compressor and engine. The focus of this research is to apply an engine icing computational tool to simulate the flow through a turbofan engine and assess the risk of ice accretion. The tool is comprised of an engine system thermodynamic cycle code, a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor flow path, without modeling the actual ice accretion. A commercial turbofan engine which has previously experienced icing events during operation in a high altitude ice crystal environment has been tested in the Propulsion Systems Laboratory (PSL) altitude test facility at NASA Glenn Research Center. The PSL has the capability to produce a continuous ice cloud which are ingested by the engine during operation over a range of altitude conditions. The PSL test results confirmed that there was ice accretion in the engine due to ice crystal ingestion, at the same simulated altitude operating conditions as experienced previously in flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict ice accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. The PSL test has helped to calibrate the engine icing computational tool to assess the risk of ice accretion. The results from the computer simulation identified prevalent trends in wet bulb temperature, ice particle melt ratio, and engine inlet temperature as a function of altitude for predicting engine icing risk due to ice crystal ingestion.

Jorgenson, Philip C. E.↗

NASA NTRS2014

Modeling of Commercial Turbofan Engine With Ice Crystal Ingestion: Follow-On

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that have been attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was degraded engine performance, and one or more of the following: loss of thrust control (roll back), compressor surge or stall, and flameout of the combustor. As ice crystals are ingested into the fan and low pressure compression system, the increase in air temperature causes a portion of the ice crystals to melt. It is hypothesized that this allows the ice-water mixture to cover the metal surfaces of the compressor stationary components which leads to ice accretion through evaporative cooling. Ice accretion causes a blockage which subsequently results in the deterioration in performance of the compressor and engine. The focus of this research is to apply an engine icing computational tool to simulate the flow through a turbofan engine and assess the risk of ice accretion. The tool is comprised of an engine system thermodynamic cycle code, a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor flow path, without modeling the actual ice accretion. A commercial turbofan engine which has previously experienced icing events during operation in a high altitude ice crystal environment has been tested in the Propulsion Systems Laboratory (PSL) altitude test facility at NASA Glenn Research Center. The PSL has the capability to produce a continuous ice cloud which is ingested by the engine during operation over a range of altitude conditions. The PSL test results confirmed that there was ice accretion in the engine due to ice crystal ingestion, at the same simulated altitude operating conditions as experienced previously in flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict ice accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. In a previous study, analysis of select PSL test data points helped to calibrate the engine icing computational tool to assess the risk of ice accretion. This current study is a continuation of that data analysis effort. The study focused on tracking the variations in wet bulb temperature and ice particle melt ratio through the engine core flow path. The results from this study have identified trends, while also identifying gaps in understanding as to how the local wet bulb temperature and melt ratio affects the risk of ice accretion and subsequent engine behavior.

Jorgenson, Philip C. E.↗

NASA NTRS2014

Modeling of Commercial Turbofan Engine with Ice Crystal Ingestion; Follow-On

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that have been attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was degraded engine performance, and one or more of the following: loss of thrust control (roll back), compressor surge or stall, and flameout of the combustor. As ice crystals are ingested into the fan and low pressure compression system, the increase in air temperature causes a portion of the ice crystals to melt. It is hypothesized that this allows the ice-water mixture to cover the metal surfaces of the compressor stationary components which leads to ice accretion through evaporative cooling. Ice accretion causes a blockage which subsequently results in the deterioration in performance of the compressor and engine. The focus of this research is to apply an engine icing computational tool to simulate the flow through a turbofan engine and assess the risk of ice accretion. The tool is comprised of an engine system thermodynamic cycle code, a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor flow path, without modeling the actual ice accretion. A commercial turbofan engine which has previously experienced icing events during operation in a high altitude ice crystal environment has been tested in the Propulsion Systems Laboratory (PSL) altitude test facility at NASA Glenn Research Center. The PSL has the capability to produce a continuous ice cloud which is ingested by the engine during operation over a range of altitude conditions. The PSL test results confirmed that there was ice accretion in the engine due to ice crystal ingestion, at the same simulated altitude operating conditions as experienced previously in flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict ice accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. In a previous study, analysis of select PSL test data points helped to calibrate the engine icing computational tool to assess the risk of ice accretion. This current study is a continuation of that data analysis effort. The study focused on tracking the variations in wet bulb temperature and ice particle melt ratio through the engine core flow path. The results from this study have identified trends, while also identifying gaps in understanding as to how the local wet bulb temperature and melt ratio affects the risk of ice accretion and subsequent engine behavior.

Jorgenson, Philip C. E.↗