Bao Nguyen Projects

• Aerial Ground Vehicle (December 2013)• Under-Expanded Flow Simulation (December 2013)• Structure Design with Finite Element Analysis (May 2013)• The Advection Diffusion of CO in San Bernardino Valley (May 2012)• Business Jet Design (May 2013)• Simulation of 2-D heat diffusion (August 2012)• Tennis Club Database Modeling(May 2011)

GAV Aerodynamic Analysis Stability & Control

Aerodynamics Characteristics Of Wing Sections

Requirements:•CL_max clean = 1.47•CL_max LandingFlaps = 2.42;

•In 118 airfoil sections, the selected: 0012_64a, 1412, 2410, 4412, 4418, 4421•Using a generic Matlab function to determine the airfoil with margin 0.3. (Codes at notes below) •Goal to get the highest lift coefficient among the selected: NACA 4412

General lift distribution of the telescoping wing with NACA 4412

• The monoplane equation:

• Lift coefficient:

• Induced drag coefficient:

• Numerical method:

• Parameters:

• Assumptions: thin airfoil theory, , Prandtl lifting line theory

• The lift curve for finite wing of general planform: • Assumptions: Figure 5.20: Induced drag factor δ as a function of taper ratio

C_t(m) b(m) t(m) n aoa_L0 (deg) aoa_Clmax (deg) theta_rad m pts

1.27 10.3 0.002 4 -4 14 π/2 30 30

C_t/C_r ~ 1.01Fig. 5.18: τ ~ 0.09Lift curve (/deg): a ~ 0.0865Numerical method C_L_α (/deg) 0.0859% error 0.74%

Errors from rounding errors and estimation from figure 5.20

Lift coefficient and Induced drag coefficient of the wing with NACA4412

Clmax (clean) C_Lmax (clean) C_Di_max 1.7 1.55 0.0936

(The airplane maximum lift coefficient) < (The airfoil maximum lift coefficients)

Flight Performance

•CruiseCL: 0.4 to 0.8L/D: 14.81 to 16.68•Takeoff: CL_to: 1.57L/D: 11.19•Landing: CL_ld: 1.5L/D: 10.63

Stability and Control

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C_m_ac -0.11 S 13.10 m2 Cl_α 0.1 /degα_0_L -4 deg b 10.30 m C_m_ac 0Cl_α 0.125 /deg c_bar 1.27 m i_t -1 degX_ac 0.25 c_bar l_f 4.20 mNo twist d_max 2.00 mi_w 1 deg S_H 2.15 m2

l_t 5.55 m

Tail airfoil sectionRef geometryWing airfoil characteristics

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Stability and Control ResultsCm_α Cm0

C_mcg_f = 0.013 α + -0.057C_mcg_w = 0.252 α + -0.092C_mcg_t = -2.351 α + 0.275C_mcg = -2.086 α + 0.125

A comparison with a general aircraft from Robert Nelson’s textbook

Payload range plot

FAR Required TOFL

FAR Climb Gradient Requirement

FAR Required LFL

References

• Anderson, John D. Fundamentals of Aerodynamics. New York: McGraw-Hill, 2011. Print.• Hale, Francis J. "Chapter 7." Introduction to Aircraft

Performance, Selection, and Design. New York: Wiley, 1984. N. Print.• Schaufele, The Elements of Aircraft Preliminary Design, Aries

Publications, 2000

Under-Expanded Flow Simulation

Bao Nguyen (Created program, process, and technical approach)

Teammates: Mike Krausert, Jesse Perez, Ronald Abrigo

Problem StatementAnalyze the diamond-shaped pattern seen in anUnder-expanded exhaust flow:

Conditions under which phenomena occursDefine pattern geometryDetermine local flow properties at selected points of interest

Swiss Propulsion Laboratorywww.spl.ch

PurposeAnalysis of Diamond-Shaped Pattern in Rocket Nozzle Exhaust FlowGeometry of characteristic mesh

Wall point location (jet boundary)Internal point locationSlopes of expansion / compression waves

Flow properties at grid pointsLocal mach number and flow directionLocal temperature and pressure

Swiss Propulsion Laboratorywww.spl.ch

Purpose (continued)

Analysis of Diamond-Shaped Pattern in Rocket Nozzle Exhaust FlowAssumptions:

Exit flow Me = Mach 3Underexpanded flow condition: PB < Pe,6Expansion wave consisting of 3 mach wavesIsentropic flow relations

Swiss Propulsion Laboratorywww.spl.ch

Approach

ResultsRocket Nozzle Design Input Parameters After the rocket nozzle design, we test it.

T (N) 1.20E+07 Pa (Pa) 2.65E+04 Pb ≡ P2 (psi) 5Altitude (km) 10 Pa ≡ Pe 2.65E+04 Pe,6 ≡ P1 (psi) 10Po (Pa) 3.45E+06 Me 3.89 Underexpanded flow

To (K) 2800 Te (K) 696.62 Me,6 ≡ M1 2.5γ 1.4 Ue (m/s) 2055.83 Po/P1 17.09R (J/kg.K) 287.05 m_dot (kg/s) 5837.06 Po/P2 34.17

A* ≡ At (m2) 0.57 M2 2.95Ae (m2) 5.54 ν(M2) (deg) 48.82

ν(M1) (deg) 39.12θ (deg) 9.70

Results (continued)

References

• Anderson, John D. Fundamentals of Aerodynamics. New York: McGraw-Hill, 2011. Print.• Zikanov, Oleg. Essential Computational Fluid Dynamics.

Hoboken, NJ: Wiley, 2010. Print.

Structural Design With Finite Element Analysis

The Process

Step1

•Set up the model: 4 groups of stringers & stiffeners, and 5 groups of panels•The thicknesses of all the panels: 0.002 ≤ t ≤ 0.15 in•The cross sectional area of the stiffeners and stringers: 0.01 ≤ A ≤ 2 sq.in

Step2

•Activate FEADLAB•Feed the program the random numbers for area and thickness within the specific

ranges•Store the data in a matrix

Step3

•Filter the data by using the criteria required for this project: margin of safety (MS) ≥ 0.5, the maximum displacement allowable δall ≤ 1.2 in

•Guarantee: Max (MS) ≤ k*Min (MS). Constant k is empirically picked from the observation of the margin of safety data, i.e.200.

Step4

•The data retrieved will be used to select the lightest weight, which we manually adjust to meet the requirements.

Results

A1 A2 A3 A4 t1 t2 t3 t4 t50.05

0.017

0.034

0.04

0.018

0.017

0.08

0.026

0.0087

• The data retrieved will be used to select the lightest weight, which we manually adjust to meet the requirements.• Results:

• With the maximum deflection of 0.95038 in, the angle of twist:

where 10 inches is the length of the stiffener 16. The twist angle comes out to be:

There are 8 longitudinal stringers, 8 transverse stiffeners, 4 upper and lower panels, 4 side walls or panels, and 2 transverse panels.Forces (lbf) applied at nodes:Node 3 (-z): 2000Node 5 (+z): 500Node 5 (+y): 1000Node 6 (-z): 1000Node 6 (+y): 2000Node 8 (-z): 1500Node 9 (-y): 750Node 11 (-z): 1000

References

• Kim, Nam H., and Bhavani V. Sankar. Introduction to Finite Element Analysis and Design. New York: John Wiley & Sons, 2009. Print.

The Advection Diffusion of CO in San

Bernardino Valley

Objectives• Investigate the concentration of carbon monoxide diffused in San Bernardino valley• Learn how to program a simplified form of the equation

After simplifying the above equation:

A is the advection coefficient and K is the diffusivity coefficient

The process• Collect data of wind speed and CO concentration on 04/07/2012 f rom 3 AM to 10 PM• Calculate the standard

deviation of CO concentration, and estimate the diffusivity K(t):• Optimize the calculation

with the initial condition f(x) = sin(pi*x).

The process (continued)

• function CN = CN_Mat(maxN,c1,c2,c3): Calculate the matrix with coefficients c1, c2, c3 with parameters k(subinterval of time), h(subinterval of space) and K(diffusivity constant) by using Crank-Nicolson method

• function AInvB = Crank_Nicolson_Const(k, h, D, maxN): Feed the function above c1, c2, c3, and calculate A*inv(B) from the returned matrixes A, B

• function InitCondArr = InitCond(maxN,h): Calculate the initial condition data.• function W = LW_Mat(k, h, A, maxN): Calculate the matrix with parameters k(subinterval of

time), h(subinterval of space), A(windspeed), and maxN(the number of space subintervals) by using Lax-Wendroff method.

• function v = MatMulti(mat1, mat2, maxN): Process vector multiplication and return a vector.• function TimeDependent1(mat, k, h, maxN, maxM): Calculate the concentration of CO with

the assumption the wind speed and the diffusivity constant are unchanged during each subinterval of time.

• function MainProj(): Control the program.

Results

References

• Hanna, Steven R., Gary A. Briggs, and Rayford P. Hosker. Handbook on Atmospheric Diffusion: Prepared for the Office of Health and Environmental Research, Office of Energy Research, U.S. Department of Energy. [Oak Ridge, TN]: Technical Information Center, U.S. Dept. of Energy, 1982. Print.

• Cengel, Yunus A., and Michael A. Boles. "1." Thermodynamics: An Engineering Approach. Singapore: McGraw-Hill, 2011. Print.

• Fox, Robert W. "4." Introduction to Fluid Mechanics, by R.w. Fox. Print.• Web. 10 May. 2012. <http://weathercurrents.com/sanbernardino/ArchiveDay.do?

day=07Apr2012>.• Web. 10 May 2012. http://www3.aqmd.gov/webappl/aqdetail/AirQualityParameterData.aspx?

Stationid=36197&AreaNumber=34&res=1680>.

Business Jet Design

C_L vs α plot for clean, takeoff and landing flap settings

C_Lα = 0.09CL_max clean = 1.45; CL_max flapup = 1.95; CL_max TOFlaps = 2.33; CL_max LandingFlaps = 2.75;

Component zero lift drag buildup

C_Dp = Σ(D/q)_i/S_ref = 0.0238Cf = 0.55/(log10RN)^2.58Cf is a function of surface finish, and this expression is only valid for a typical metal aircraft skin condition, as stated in the figure.

Takeoff and landing flap setting

ΔCD flaps 15 0.007ΔCD flaps 25 0.017ΔCD flaps 50 0.081ΔC_Dslat 0.006

Clean configuration drag polar : e_lowspeed = e_cruise(0.90) = 0.68

Takeoff configuration:*Leading edge devices extended:*Trailing edge flaps set for takeoff*Gear retracted*Speed = 1.2 VstallThe total drag coefficient for this condition may be written:

C_D vs. Mach for increasing C_L

*Our plane cruises at Mach 0.8. The airplane will be best performed at CL = 0.2*It has been found that for the lift coefficients of interest for cruise, the shape of the compressibility drag rise curve vs Mach number may be generalized for all lift coefficients as a function of Mdiv as shown in fig. 12-10.

L/D vs. CL at cruise condition for different Mach values

From the data generating cruise drag map, by interpolation at each Mach number, C_D is derived.

Maneuvering & Gust Envelope

Choice of materialsn = 3.46

Graphite-epoxy

ρ = 0.056 lb/in^3 σ_ult = 110 ksi to 180 ksi

References

• Schaufele, The Elements of Aircraft Preliminary Design, Aries Publications, 2000

Simulation of 2-D Heat Diffusion

The Process • Simulate the transient heat transfer:• Time step must satisfy a stability criterion:• Use spmd to run two functions in two labs separately.• Results: (starting from first row to second row and from left to

right)

References

• Incropera, Frank P. Fundamentals of Heat and Mass Transfer / Frank P. Incropera ... Hoboken, NJ: John Wiley, 2007. Print.

Tennis Club Database Modeling

The Process• Use Oracle SQL to transform the logical entity relationship diagram (ERD) into a physical data model.• Connect the database to ASP. Net

References

• Oracle Database 11g: SQL Fundamentals I, Volume I, II (Student Guide)