Oswald efficiency estimation function
This function lets you use different methods to estimate Oswald efficiency factor, e, for purposes of approximating a simple parabolic drag polar:
C_D = C_D0 + C_L^2/(pi*e*AR), where C_L is lift coefficient.
Based on some or all of the following:
- Wing aspect ratio
- Wing sweep
- Parasite drag coefficient (drag independent of lift)
- Ratio of fuselage diameter (or width) to wing span
- Planform efficiency - usually .98 < u < 1
You can also choose between two common methods as proposed by Raymer ("Aicraft Design: A Conceptual Approach") or Shevell ("Fundamentals of Flight"). OSWALDFACTOR can also calculate using both methods and return the most pessimistic or optimistic result or a weighted average of the two results.
Example: Replicate Shevell's Figure 11.8.
u = .99; df_b = 0.114;
ARx = linspace(0,12,25);
[CD0,AR] = meshgrid([.01 .015 .02 .025],ARx);
e = oswaldfactor(AR,0,'shevell',CD0,df_b,u);
plot(ARx,e); axis([0 12 .6 1]); grid on
xlabel('Aspect Ratio'); ylabel('Efficiency factor, e')
legend('C_{D,0} = 0.01','0.015','0.02','0.025')
text(8.5,.63,'u = 0.99 s = 0.975')
sweepx = linspace(0,40,41);
[AR,sweep] = meshgrid([4;8;12],sweepx*pi/180);
e = oswaldfactor(AR,sweep,'shevell',0,df_b,u)./...
oswaldfactor(AR, 0 ,'shevell',0,df_b,u);
axes('pos',[0.25 0.25 0.3 0.25]);
plot(sweepx,e); axis([0 40 .9 1.02]); grid on
xlabel('Sweep, \Lambda (deg)'); ylabel('e_\Lambda/e_{\Lambda=0}')
legend('AR = 4','8','12','Location','SouthWest')
引用格式
Sky Sartorius (2024). Oswald efficiency estimation function (https://www.mathworks.com/matlabcentral/fileexchange/38800-oswald-efficiency-estimation-function), MATLAB Central File Exchange. 检索来源 .
MATLAB 版本兼容性
平台兼容性
Windows macOS Linux类别
标签
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!版本 | 已发布 | 发行说明 | |
---|---|---|---|
1.5.0.0 | minor: documentation and input handling |
||
1.4.0.0 | name change to help differentiate from lifting line e |
||
1.3.0.0 | improved n-dim input handling |
||
1.2.0.0 | added weighted average method; changed exponent from 2.3 to 2.2 so as not to be too optimistic; better input handling |
||
1.1.0.0 | improved math and curve fit coefficients; added example |
||
1.0.0.0 |