David L. Rigby | Search NASA

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Simulation of Fluid Flow and Collection Efficiency at Low Stokes Number

Numerical simulations of fluid flow and collection efficiency for a Science Engineering Associates (SEA) Robust probe are presented. The cases cover a range of freestream velocity from 10-135 m/s, and particle sizes from 1-200 µm. This combination produces results for Stokes numbers in the range of 0.07-1092. A blended modified Stokes (defined in the paper) is introduced which covers a range of 0.07-146. Of particular interest is the collection efficiency of the sensing element (a forward-facing half-pipe), Etot, in the low Stokes number regime. It was observed that the collection efficiency of the sensing area approached one for large Stokes numbers (>100) as expected. As blended modified Stokes number approached one, the Etot dropped to approximately 0.5. By blended modified Stokes numbers of 0.3, the Etot has dropped to essentially zero. Plotting collection versus blended modified Stokes number, the different freestream velocities collapsed quite well on to a single curve. The paper presents a discussion on the flowfield and local collection efficiency, beta, in an effort to explain the predictions. Of particular interest is what is essentially a shadow zone in plain sight. As the Stokes number is reduced, the local beta along the centerline of the half-pipe goes to zero. This occurs at Stokes numbers where the overall collection, Etot, is still appreciable. An empirical relation was developed to allow for corrected collection values at low Stokes numbers. The correlation remains within 2% for blended modified Stokes numbers above 1, and within 6% for all cases.

Instrumentation↗

NASA NTRSDate not supplied

Simulation of Fluid Flow and Collection Efficiency at Low Stokes Number

Numerical simulations of fluid flow and collection efficiency for a Science Engineering Associates (SEA) Robust probe are presented. The cases cover a range of freestream velocity from 10-135 m/s, and particle sizes from 1-200 µm. This combination produces results for Stokes numbers in the range of 0.07-1092. A blended modified Stokes (defined in the paper) is introduced which covers a range of 0.07-146. Of particular interest is the collection efficiency of the sensing element (a forward-facing half-pipe), Etot, in the low Stokes number regime. It was observed that the collection efficiency of the sensing area approached one for large Stokes numbers (>100) as expected. As blended modified Stokes number approached one, the Etot dropped to approximately 0.5. By blended modified Stokes numbers of 0.3, the Etot has dropped to essentially zero. Plotting collection versus blended modified Stokes number, the different freestream velocities collapsed quite well on to a single curve. The paper presents a discussion on the flowfield and local collection efficiency, beta, in an effort to explain the predictions. Of particular interest is what is essentially a shadow zone in plain sight. As the Stokes number is reduced, the local beta along the centerline of the half-pipe goes to zero. This occurs at Stokes numbers where the overall collection, Etot, is still appreciable. An empirical relation was developed to allow for corrected collection values at low Stokes numbers. The correlation remains within 2% for blended modified Stokes numbers above 1, and within 6% for all cases.

Instrumentation↗

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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↗

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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↗

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Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗

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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↗

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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↗