emilio borges - nasa 2016 summer internship final report

Effect of Water Droplets crossing the Boundary Layer in a

Stagnation Point Configuration

Emilio Borges

NASA Glenn Research Center

Major: Computer Science and Engineering

2016 Summer Session

Date: 11 August 2016

This final report has been reviewed and approved by Mario Vargas to ensure

information is accurate and does not contain sensitive data.

Signature LTI0/11 Aug. 2016

Mentor Name & Org Code/Date

NASA – Internship Final Report

NASA Glenn Research Center 1 11 August 2016

Effect of Water Droplets crossing the Boundary Layer in a

Stagnation Point Configuration

Emilio Borges1 University of Toledo

Dr. Mario Vargas2 NASA Glenn Research Center

Cleveland, OH 44135

Dr. Andy Broeren 3 NASA Glenn Research Center

Cleveland, OH 44135

Dr. Stephen McClain4 Baylor University

Waco, TX 76798

NASA Glenn Research Center Summer Internship 2016 Funded by the Ohio Space Grant Consortium through the Ohio Aerospace Institute

Aircraft icing is a dangerous phenomenon that is studied in-depth by

NASA’s Icing Branch in order to improve safety for passengers and crew of

aircraft operating in icing conditions. One of NASA’s most widely used tools

is icing prediction codes, such as LEWICE. Within LEWICE, the modeling

of ice roughness and its effects on convective heat transfer can be improved,

furthering LEWICE’s attractiveness to potential customers. Building on

several previous studies, this study examines the effect different sized water

droplets have on airflow within the boundary layer in stagnation region

flows. Using the Vertical Icing Studies Tunnel (VIST) at NASA Glenn

Research Center, a test plate representing the leading 2% chord of a NACA

0012 was subject to various flow conditions. A hot-wire anemometer is used

to measure the VIST’s boundary layer flow characteristics at varying flow

speeds to build a control group of data before proceeding with modifying the

tunnel to install a spray water nozzle. To select the best nozzle for the

experiment, special software was designed to model the flow pattern of the

nozzle within the varying flow conditions of the VIST. Once the nozzle is

installed, another set of hot-wire anemometer data is to be collected to study

the effect the nozzle had on the VIST’s boundary layer. The data gathered

during this study will ultimately be used to improve ice accretion codes, such

as LEWICE, in an effort to improve their ability to match real icing events

and allow more accurate prediction of ice accretions on aircraft surfaces

without the need for full-scale testing.

1 Bachelor’s of Computer Science and Engineering at The University of Toledo, Toledo, OH 43606 2 Aerospace Engineer, Icing Branch, 21000 Brookpark Rd., AIAA Associate Fellow. 3 Aerospace Engineer, Icing Branch, 21000 Brookpark Rd., AIAA Associate Fellow. 4 Associate Professor, Department of Mechanical Engineering, One Bear Place #97356, AIAA Senior Member.



Nomenclature

𝐴𝑜 = Nozzle orifice area

𝑄 = Volumetric flow rate capacity

𝑉𝑜 = Orifice flow velocity

𝜃𝑠 = Nozzle spray angle

𝜌𝐴 = Air density

𝜌𝑊 = Water density

𝜇 = Dry air dynamic viscosity

𝐴𝑑 = Droplet cross sectional area

𝑉𝑜𝑙𝑑 = Droplet volume

𝑀 = Droplet mass

𝐺 = Gravity

𝑉𝑉𝐼𝑆𝑇 = VIST flow velocity

𝑉𝑠𝑙𝑖𝑝 = Droplet slip velocity

𝑅𝑒 = Reynolds number

𝐶𝑑 = Drag coefficient

I. Introduction

he effects of in-flight ice accretions on aircraft surfaces have been studied by NACA and

NASA since the mid 1940’s [1]. Following the high loss rate of cargo aircraft flying supply

missions over the Himalayas during the Second World War, the United States government began

construction of the Icing Research Tunnel in 1944. Since then, the Icing Branch at NASA Glenn

Research Center has utilized a wide variety of tools to study the effects of icing and the methods

of its formation in order to improve aircraft safety. As demonstrated in Figure 1, as ice forms on

the leading edge of an airfoil, the lift and stall margin decrease while the skin friction drag and

weight increase. As a result of such serious reduction in performance of an aircraft in icing

conditions, the Federal Aviation Administration has published a set of certification requirements

for flying in such icing conditions known as Appendix C. All aircraft must undergo certification

to fly in Appendix C icing conditions. As a result, commercial and military aircraft alike utilize

extensive testing to ensure their aircraft’s ability to operate in such conditions. In addition to pure

research, the Icing Research Tunnel at NASA Glenn Research Center, in-flight testing, and

computational ice prediction codes are all utilized by customers in order to certify their aircraft.

LEWICE, developed by researchers at NASA Glenn, is one of the leading software

applications in industry and provides valuable data to customers without the need for full-scale

testing. LEWICE couples computational fluid dynamics with heat transfer to predict the

formation of ice accretions on airfoils [2]. It is widely used throughout the aeronautics industry

and is currently the best predictor of ice accretions on aircraft surfaces. However, this does not

mean LEWICE is perfect. There are still many areas within the LEWICE source code that need

improvement. In order to validate such improvements, experimental tests need to be conducted

to verify LEWICE’s results match with experimental results. The objective of the author’s ten-

week summer internship at NASA Glenn Research Center is to determine the validity of the

following hypothesis in a stagnation point configuration: water droplets crossing a boundary

layer will create turbulent spots that will accelerate the transition from laminar to turbulent. The

T



experimental results from this hypothesis will then go on to improve LEWICE’s ice accretion

predictions on aircraft surfaces. However, due to the short duration of the ten-week summer

internship, the author was not able to obtain experimental data for this hypothesis. Instead, all the

necessary requirements to get the experiment set up and ready to gather data were completed.

Figure 1 - Negative effects on aircraft performance due to ice accretion.

II. Experiment

All testing in this study was performed at NASA Glenn Research Center in Building 5,

Room CW-5 utilizing the Vertical Icing Studies Tunnel. The following sections will outline the

testing apparatus, testing equipment used, spray nozzle selection, spray nozzle bread table

experiment, designing the spray nozzle installation, and how data was gathered.

A. Testing Apparatus

The Vertical Icing Studies Tunnel is a closed loop, atmospheric tunnel with a 7.2:1

contraction ratio, a 4 in. wide throat, and a 3 HP DC motor with a max speed of 1750 rpm. The

VIST’s fan enables throat velocities ranging from 2 m/s (6.5 ft/s) to 25 m/s (82 ft/s). The VIST

was designed in 2005 by Dr. Ed White and first presented as a viable test apparatus shortly

thereafter in a publication by White and Oliver [3]. It was originally design to study water

droplet impingement on a 737 midspan at the stagnation region. The VIST’s design to study the

stagnation region of airfoils made it an ideal testing apparatus for this study. Unlike conventional

wind tunnels, the VIST utilizes an instrumented flat plate to model the airfoil desired. In order to

model the desired airfoil, the side walls of the VIST were contoured and instrumented with

pressure taps to ensure the test plate was subjected to the same accelerating flows experienced by

the airfoil in question. The original test plate installed in the VIST was a 30 in. by 60 in. flat,

aluminum plate instrumented with pressure taps along its surface. The stagnation point on the

test plate was directly in the center, with the flow impinging downward on the test plate at the

center and accelerating as the flow continued outward as shown in Figure 2.



Figure 2 - VIST schematic showing side wall and test plate

position.

Figure 3 - Vertical Icing Studies Tunnel

B. Testing Equipment

To get an accurate measurement of the boundary layer flow, a TSI 1218-10 standard

boundary layer hot-wire anemometer, shown in Figures 4 and 5, was positioned inside the VIST

at varying distances from the stagnation point. A hot-wire anemometer measures air flow

velocity by electrically heating an extremely thin tungsten wire above ambient temperature. As

air flows past the wire, the temperature of the tungsten changes, which changes the resistance of

the wire. This resistance is then measured and compared against a relationship between

resistance and flow velocity [4]. With a sensitive hot-wire anemometer, such as the TSI 1218-10,

it is possible to measure turbulence within the boundary layer flow.

Figure 4 - TSI 1218-10 Standard Boundary Layer Hot-Wire

Anemometer Probe

Figure 5 - TSI 1218-10 probe hundredth of an inch above the VIST test plate

In order to measure minute changes in resistance, the TSI 1218-10 probe is paired up

with the TSI IFA-300 Constant Temperature Anemometer anemometry system. The IFA-300

provides the necessary hardware to configure the probe, collect precise measurements, and

remove any unwanted signal noise. The output from the IFA-300 then feeds into a National

Instruments Data Acquisition system, which allows LabView software to monitor and collect

data from the probe.

Lastly, to control the position of the probe, a Velmex VXM Stepping Motor Controller

was utilized. Through a LabView program, the probe position can be finely controlled to

thousandth of an inch. This level of control was especially helpful when lowering the probe to

hover just above the plate.



C. Spray Nozzle Selection

Generating water droplets inside the VIST of the right size and flow pattern requires a

specialized water nozzle with a well-understood and predictable operation while in varying wind

velocities. It was known that a flat spray nozzle was needed, but specifically which flat spray

nozzle would work best with the VIST was to be determined. Because the test plate inside the

VIST represents the leading 2% chord of a NACA 0012, the nozzle needed to produce water

droplets between 200 and 5000 micrometers in diameter. The biggest factor, however, when

searching for a nozzle was making sure the inner walls of the VIST would not get wet while

running the experiment. To get a better idea of which nozzles worked best, specialized software

was written to calculate the nozzle’s outer flow trajectory given the nozzle’s flow rate, spray

angle, and orifice diameter parameters, constant VIST wind velocity, and water pressure into the

nozzle.

From the given information, the software then calculates the following:

𝐴𝑜 = 𝜋 (𝑑

2)

2

where d is the orifice diameter

𝑄 = a power curve fit of a linear-to-power transformation of a linear regression on a linear

fit of a power-to-linear transformation of the given nozzle flow rate capacity values

𝑦 = 𝑎𝑥𝑏 → ln(𝑦) = 𝑏 ln(𝑥) + ln(𝑎) → 𝑦 = 𝑒ln(𝑎)𝑥𝑏

where y = nozzle flow rate, x = given water pressure, ln(𝑎) = linear y-intercept, a =

power y-intercept, b = slope

𝑉𝑜 = 𝑄/𝐴𝑜

𝜃𝑠 = logarithmic least squares fitting of the given nozzle spray angle at varying water

pressures [5]

𝑦 = 𝑎 + 𝑏 ln 𝑥

𝑏 =𝑛 ∑ (𝑦𝑖 ln 𝑥𝑖) − ∑ 𝑦𝑖

𝑛𝑖=1 ∑ ln 𝑥𝑖

𝑛𝑖=1

𝑛𝑖=1

𝑛 ∑ (ln 𝑥𝑖) − (∑ ln 𝑥𝑖𝑛𝑖=𝑖 )2𝑛

𝑖=1

𝑎 =∑ 𝑦𝑖

𝑛𝑖=𝑖 − 𝑏 ∑ (ln 𝑥𝑖)

𝑛𝑖=𝑖

𝑛

where y = 𝜃𝑠, x = water pressure

𝜌𝐴 = 1.200227 kg/m3 at 70ºF [6]

𝜌𝑊 = 998.02 kg/m3 at 70ºF [7]

𝜇 = 1.77E-5 at 70ºF [8]

𝐴𝑑 = 𝜋 (𝑑

2)

2

where d is the droplet diameter

𝑉𝑜𝑙𝑑 = 4

3𝜋 (

𝑑

2)

3

where d is the droplet diameter

𝑀 = 𝑉𝑜𝑙𝑑 ∗ 𝜌𝑊

𝐺 = 9.80665 m/s2

𝑉𝑠𝑙𝑖𝑝 = 𝑉𝑜 − 𝑉𝑉𝐼𝑆𝑇

𝑅𝑒 = 𝑉𝑠𝑙𝑖𝑝 𝑑

𝜇/𝜌𝐴 where d is the droplet diameter



𝐶𝑑 = 24

𝑅𝑒+

2.6(𝑅𝑒

5)

1+(𝑅𝑒

5)

1.52 +0.411(

𝑅𝑒

263,000)

7.94

1+(𝑅𝑒

263,000)

−8 +𝑅𝑒0.8

461,000 [9]

After calculating the above values, the software then uses the Runge-Kutta numerical

method for first order differential equations [10] to solve for the outer droplet’s X and Y

velocities from the following acceleration equations:

𝑥′ = −𝐶 √𝑥2 + 𝑦2 𝑥

𝑦′ = 𝑔 − 𝐶√𝑥2 + 𝑦2 𝑦

where 𝐶 =𝜌𝐶𝑑𝐴𝑑

2𝑀 is the constants value extracted and reworked from the drag force equation

𝐹𝑑 = 𝑀 𝐴𝑐𝑐𝑑 =1

2𝜌𝐴𝑉𝑠𝑙𝑖𝑝

2 𝐶𝑑𝐴𝑑 where 𝐴𝑐𝑐𝑑 is the droplet acceleration. Using the droplet X and

Y velocities over time, the X and Y displacements are calculated and used to plot the graph

shown in Figure 6.

Figure 6 - VIST Nozzle Spray Area Software Interface; Control Panel (top), VIST Water Nozzle Predicted Spray Area (left), Droplet Velocity vs. Time (right)

Once completed, the above software was then ran with various nozzle parameters in

various VIST conditions to see which nozzle worked best for the experiment. In the left graph of

the figure above, the orange vertical lines represent the side walls of the VIST, the blue lines

represent the nozzle spray area, the zero-x axis represents the VIST test plate, and the y axis is

the height of the nozzle from the test plate. The goal of this software was to determine which

nozzles gave us the maximum spray area without getting the side walls wet. With the results

from the software, two nozzles from Spray Systems Co. were selected; an air atomizing 16860-

1/8JJAU-SS spray nozzle [11] and a hydraulic 1/8TT-SS spray nozzle [12] both equipped with a

UniJet 800050 TPU spray tip.



D. Spray Nozzle Bread Table Experiment

Before installing the spray nozzle into the VIST, a bread table experiment was designed to test and operate the nozzle in order to work out any issues and write the operating procedure. As shown in Figure 7, the nozzle control interface is fed pressurized shop air at 120 psi, which is redirected into an EMERSON Tescom pressure regulator system. The Tescom system is what controls the water pressure feeding into the nozzle through a computer interface (not shown). Once the water tank reaches the desired pressure, the water valve is opened and pressurized water flows through the flow meter and into the nozzle. This experiment allowed for the understanding of operating the water nozzle and paved way for designing how the nozzle should be installed inside the VIST.

Figure 7 - 1/8TT-SS spray nozzle bread table experiment; nozzle control interface (left), nozzle and flow meter (right)

E. Designing Spray Nozzle Installation

With a nozzle selected, the next challenge is designing a frame to hold the nozzle inside

the center of the VIST above the contraction phase. The decision was made to use the acrylic

glass window, shown in Figure 8 near the top, as the location to hold and interface with the

nozzle.

Figure 8 – VIST front; acrylic glass window (top)



The design for the frame was constrained to minimal machinign and easy assembly. The final design, shown in Figure 9, includes pre-made parts ordered from McMaster-Carr and acrylic sheets machined to shape.

Figure 9 – Nozzle Frame CAD Assembly; (left) nozzle frame without nozzle, (middle) nozzle frame with nozzle, (right) complete nozzle frame assembly with acrylic glass window

F. Gathering Data

Given the short duration of the ten-week internship, the set of boundary layer airflow data

collected is from the unmodified VIST without the nozzle installed. These measurements act as a

control to compare against future measurements when the nozzle is installed. The measurements

were made at varying heights above the VIST test plate near the stagnation point at varying flow

velocities. Six different velocities were measured: 15 ft/s, 25 ft/s, 35 ft/s, 40 ft/s, 45 ft/s, 55 ft/s.

For each velocity, the TSI 1218-10 hot-wire anemometer probe collected 50,000 measurements

per second for 2.5 seconds at eighty-one different heights above the VIST test plate totaling to

10,125,000 measurements per velocity. Before collecting data, the hot-wire anemometer was

carefully lowered to be as close as possible to the test plate. As the test ran, the Velmex system

would raise the probe slightly until eighty-one different heights were measured in the two inch

height boundary the probe was set to measure. Through the IFA-300 and NI DAQ, the

measurements were recorded on a computer in a standard .txt file. The values recorded were

voltages representing the boundary layer flow at different times.

III. Results and Discussion

Following the collection of data, the measurements were run through a MATLAB script,

developed by Dr. Stephen McClain, to interpret the voltage measurements as meaningful data.

For each velocity measured, the script produced two graphs; boundary layer flow velocity vs.

height, as shown in Figure 10, and turbulence intensity vs. height, as shown in Figure 11.



Figure 10 – Boundary layer flow velocity (m/s) vs. height (in.)

at 15 ft/s

Figure 11 – Boundary layer turbulence intensity (%) vs.

height (in.) at 15 ft/s


at 35 ft/s




at 55 ft/s



From the graphs, it is clear the VIST’s boundary layer flow contains too much turbulence

for droplet measurements to be useful. From the turbulence intensity graphs above, the average



turbulence intensity is around 2%. The acceptable turbulence should be between 0.5% and 1%

intensity.

IV. Conclusion

Due to the high level of turbulence inherent in the VIST, experimental measurements

cannot continue until the turbulence is lowered below 1%. It is thought that the centrifugal fan

used in the VIST is the cause for such high turbulence, but this suspicion has not been verified.

The VIST already includes honeycomb and mesh to improve the flow field, but it is not enough

to lower the turbulence. A study needs to be conducted on what specifically is causing the high

turbulence and develop a plan of action to correct the issue(s).

Acknowledgements

The study outlined in this paper was performed under the NASA Space Grant Internship

funded by the Ohio Space Grant Consortium through the Ohio Aerospace Institute at NASA

Glenn Research Center. The assistance of Mr. Robert Clark, Mr. Kurt Rusmisel, Mrs. Katelyn

McCormick, and Mrs. Marivell Baez at NASA GRC is greatly appreciated. Finally, the

assistance of fellow interns Joaquin Martinez and Aaron Tallman in work on the VIST and

development of spray trajectory software, respectively, is also greatly appreciated. Any opinions

presented in this paper are those of the authors and do not reflect the views of NASA or the

United States government.

References 1Leary, W. M. (2002). We Freeze to Please: A History of NASA's Icing Research Tunnel and the

Quest for Flight Safety (No. NAS 1.21: 4226,). 2Wright, W.B., “User Manual for the NASA Glenn Ice Accretion Code LEWICE,” NASA/CR-

2002-211793, 2002. 3White, E. B. and Oliver, M. J., (2005), “Experiments on Surface Roughness Effects in Ice

Accretion,” Presented at the AIAA 4th Theoretical Fluids Meeting, June 22-25, 2005,

Toronto, ON, AIAA-2005-5190. 4"Hot-wire Anemometer explanation". eFunda. Archived from the original on 10 October 2006.

Retrieved 18 September 2006. 5WolframMathWorld, “Least Squares Fitting--Logarithmic," Retrieved June 27, 2016, from

mathworld.wolfram.com/LeastSquaresFittingLogarithmic.html 6The Engineering ToolBox, “Air Density and Specific Weight,” Retrieved June 28, 2016, from

www.engineeringtoolbox.com/air-density-specific-weight-d_600.html 7The Engineering ToolBox, “Water Density and Specific Weight,” Retrieved June 29, 2016,

from www.engineeringtoolbox.com/water-density-specific-weight-d_595.html 8The Engineering ToolBox, “Dry Air Properties,” Retrieved June 28, 2016, from

www.engineeringtoolbox.com/dry-air-properties-d_973.html 9Faith A. Morrison, “Data Correlation for Drag Coefficient for Sphere,” Department of Chemical

Engineering, Michigan Technological University, Houghton, MI,

www.chem.mtu.edu/~fmorriso/DataCorrelationForSphereDrag2013.pdf 10Bahr. “Solving Ordinal Differential Equation Using Ms. Excel.” Web log post. Bahrfly’s Blog.

N.p., 16 Feb. 2010. Web. 5 July 2016. 11Spray Systems Co. “Automatic & Air Atomizing Spray Nozzles.” Catalog. pp. A4, A6, B16,

C8. http://www.spray.com/cat76/automatic/



12Spray Systems Co. “Industrial Hydraulic Spray Products.” Catalog. pp. A6, A8, C24-C31.

http://www.spray.com/cat75/hydraulic/ 13White, Edward B. "Design and Construction of an Icing Physics Flow Laboratory." Proposal.

Case Western Reserve University, 2004. Print.

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