Christopher E Porter | Search NASA

NASA NTRS2025

Details of Adhering and Testing Artificial Ice Shapes to the High Lift Common Research Model in the National Transonic Facility

There is currently interest in conducting flight Reynolds number aerodynamic performance testing for iced airplane configurations. There has only been limited testing in the past, none of which has resulted in publicly available data. Consequently, there is virtually no documented knowledge for conducting icing related testing at flight Reynolds number where testing in cryogenic conditions is required. The National Transonic Facility (NTF) is a cryogenic wind tunnel at NASA Langley Research Center that is capable of achieving flight Reynolds numbers on subscale models. A large number of aerodynamic tests have been performed in this facility for uniced subscale model configurations. Through the collaborations associated with the High Lift Common Research Model, a test campaign was conducted to fill the existing research gaps with publicly available data. This resulted in a requirement that NASA develop a suitable level of competency for performing icing related tests in cryogenic environments. This document provides information about the challenges faced during the test campaign, how the issues were mitigated, and preserves the institutional knowledge gained by providing recommendations that will be used to reduce risk for future testing.

Iced Aerodynamics↗

NASA NTRSDate not supplied

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↗

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

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 NTRSDate not supplied

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗