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At least 19 records
All sourcesNASA NTRSDOE OSTI
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 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

Introduction to the Glenn Icing Computational Environment (GlennICE)

The NASA John H. Glenn Research Center at Lewis Field is developing the Glenn Icing Computational Environment (GlennICE) tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This short course will walk through some of the underlying physics involved with GlennICE and how we achieve efficient 3D ice accretion predictions. After an introduction of GlennICE, an analysis of the Common Research Model High-Lift will be demonstrated to showcase the typical workflow for an aircraft icing analysis. Within this walkthrough, capabilities will be highlighted with future planned capabilities being discussed. Finally, we will showcase the impact GlennICE is having on NASA’s icing portfolio and how it is advancing aircraft icing research and safety.

Icing↗
NASA NTRSDate not supplied

Demonstration of Initial GlennICE Relative Frame Capability: Axial-Flow Propeller

Modifications have been implemented in the GlennICE software to accommodate a non-inertial reference frame. GlennICE accepts a flow solution from an external flow solver. It then introduces particles and tracks them through the flow field in a Lagrangian manner. Centrifugal and Coriolis terms were added to the GlennICE software to account for relative frame simulations. The objective of the present paper is twofold. First, to check that the new terms are implemented correctly and that the code still behaves as expected with respect to convergence. And second, to provide some initial insight into an upcoming propeller experiment in the NASA Icing Research Tunnel. The paper presents a description of the code modifications. In addition, results are presented for two operating conditions, and three particle sizes. Each case was simulated with four different grid densities to assess grid dependence.

Aircraft Icing↗
NASA NTRSDate not supplied

Demonstration of Initial GlennICE Relative Frame Capability: Axial-Flow Propeller

Modifications have been implemented in the GlennICE software to accommodate a non-inertial reference frame. GlennICE accepts a flow solution from an external flow solver. It then introduces particles and tracks them through the flow field in a Lagrangian manner. Centrifugal and Coriolis terms were added to the GlennICE software to account for relative frame simulations. The objective of the present paper is twofold. First, to check that the new terms are implemented correctly and that the code still behaves as expected with respect to convergence. And second, to provide some initial insight into an upcoming propeller experiment in the NASA Icing Research Tunnel. The paper presents a description of the code modifications. In addition, results are presented for two operating conditions, and three particle sizes. Each case was simulated with four different grid densities to assess grid dependence.

Aircraft 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

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 Comparison of Trajectory Refinement Schemes for GlennICE

A requirement of computational ice accretion solvers is the ability to predict the water impingement on a geometry of interest. This portion of the tool is typically implemented in an Eulerian or Lagrangian methodology with both approaches having various pros and cons. GlennICE utilizes a Lagrangian framework. For this approach to be tractable in an engineering sense, the trajectories simulated must be chosen in a more intelligent fashion than naïve uniform refinement. This paper investigates a new refinement methodology implemented in GlennICE and compares it to the previous implementation.

Computational↗
NASA NTRS2008

Comparison of LEWICE and GlennICE in the SLD Regime

A research project is underway at the NASA Glenn Research Center (GRC) to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from two different computer programs. The first program, LEWICE version 3.2.2, has been reported on previously. The second program is GlennICE version 0.1. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the GRC Icing Research Tunnel (IRT) has also been performed, including additional data taken to extend the database in the Super-cooled Large Drop (SLD) regime. This paper will show the differences in ice shape between LEWICE 3.2.2, GlennICE, and experimental data. This report will also provide a description of both programs. Comparisons are then made to recent additions to the SLD database and selected previous cases. 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 programs are within the accuracy limits of the experimental data for the majority of cases.

Wright, William B.↗
NASA NTRSDate not supplied

Simulation of Fluid Flow and Collection Efficiency for a SEA Inc. Multi-Element Probe and Ice Crystal Detector Using GlennICE

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.

aircraft, icing, Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Simulation of Fluid Flow and Collection Efficiency for a SEA Inc. Multi-Element Probe and Ice Crystal Detector Using GlennICE

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.

aircraft, icing, Computational Fluid Dynamics↗
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 NTRS2024

GlennICE Manual 4.2.0

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↗
NASA NTRS2011

Mixed Phase Modeling in GlennICE with Application to Engine Icing

A capability for modeling ice crystals and mixed phase icing has been added to GlennICE. Modifications have been made to the particle trajectory algorithm and energy balance to model this behavior. This capability has been added as part of a larger effort to model ice crystal ingestion in aircraft engines. Comparisons have been made to four mixed phase ice accretions performed in the Cox icing tunnel in order to calibrate an ice erosion model. A sample ice ingestion case was performed using the Energy Efficient Engine (E3) model in order to illustrate current capabilities. Engine performance characteristics were supplied using the Numerical Propulsion System Simulation (NPSS) model for this test case.

Wright, William B.↗
NASA NTRSDate not supplied

LEWICE2D and GlennICE Results for Ice Prediction Workshop

This presentation documents results from the LEWICE2D and GlennICE computer codes for the 1st AIAA Ice Prediction Workshop. The results include ice shape comparisons between the code predictions with experimental ice shapes for a limited number of configurations and conditions. The intent of this workshop is to establish a sound baseline of the current capabilities and use this baseline to target the best topics for follow-on workshops.

William Wright↗
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

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↗