178
K. S. Vepa et al.
Table 3 Comparison of experimental and numerical drag force results
Speed (m/s)
Numerical
Experimental
4.788
1.5762 N
1.52873 N
tunnel tests and the simulations for a wind speed of 4.788 m/s which are equivalent
to 165 RPM in the wind tunnel. From the comparison, it is observed that there is
only a relative error of approximately 3% between the two.
5 Conclusions
In the present work, an unmanned aircraft system is considered for CFD simulation
to study its aerodynamic performance. The frame of the UAS is optimized for its
mass and structural strength. Due to its geometrical complexity, it is fabricated using
FDM technology. Flow field around the quadcopter and the drag forces generated
are analyzed. For validation, numerical simulations and wind tunnel experiments are
compared which shows they are in good agreement with each other. Simulations
are carried out during hovering and forward motion for various angles of attack.
Minimum drag is experienced between 4° and 8° during hovering and 8° and 12°
during forward motion (at a speed of 5 m/s). Based on the comparison of numerical
and experimental results, it is concluded that the drag is dependent on the AoA as
well as the wind velocity.
References
1. Hassanalian M, Abdelkefi A (2017) Classifications, applications, and design challenges of
drones: a review. Progr Aerosp Sci 91:99–131
2. Yan R-j et al (2010) Development and missions of unmanned surface vehicle. J Mar Sci Appl
9(4):451–457
3. Domenge PXC, Ilie M (2010) Numerical study of helicopter blade–vortex mechanism of
interaction using the potential flow theory. Appl Math Model 36(7):2841–2857
4. Dwivedi Y, Jagadish D, Sridhar V (2016) Aerodynamic analysis of corrugated winglet for
improved MAV performance
5. Sridhar V, Dwivedi Y (2017) Effect of peak shape in bio inspired corrugated wing. In:
International conference on advances in thermal systems, materials and design engineering
(ATSMDE2017)
6. Dwivedi Y et al (2017) Computational study of fluid flow behavior over bio-inspired corrugated
airfoil for micro aerial vehicles. In: International conference on advances in thermal systems,
materials and design engineering (ATSMDE2017)
7. Esakki B et al (2018) Design of amphibious vehicle for unmanned mission in water quality
monitoring using internet of things. Sensors 18(10):3318
8. Ganesan S, Esakki B (2019) Design and development of unmanned hovercraft
9. Filippone A, Michelsen J (2001) Aerodynamic drag prediction of helicopter fuselage. J Aircr
38(2):326–333
K. S. Vepa et al.
Table 3 Comparison of experimental and numerical drag force results
Speed (m/s)
Numerical
Experimental
4.788
1.5762 N
1.52873 N
tunnel tests and the simulations for a wind speed of 4.788 m/s which are equivalent
to 165 RPM in the wind tunnel. From the comparison, it is observed that there is
only a relative error of approximately 3% between the two.
5 Conclusions
In the present work, an unmanned aircraft system is considered for CFD simulation
to study its aerodynamic performance. The frame of the UAS is optimized for its
mass and structural strength. Due to its geometrical complexity, it is fabricated using
FDM technology. Flow field around the quadcopter and the drag forces generated
are analyzed. For validation, numerical simulations and wind tunnel experiments are
compared which shows they are in good agreement with each other. Simulations
are carried out during hovering and forward motion for various angles of attack.
Minimum drag is experienced between 4° and 8° during hovering and 8° and 12°
during forward motion (at a speed of 5 m/s). Based on the comparison of numerical
and experimental results, it is concluded that the drag is dependent on the AoA as
well as the wind velocity.
References
1. Hassanalian M, Abdelkefi A (2017) Classifications, applications, and design challenges of
drones: a review. Progr Aerosp Sci 91:99–131
2. Yan R-j et al (2010) Development and missions of unmanned surface vehicle. J Mar Sci Appl
9(4):451–457
3. Domenge PXC, Ilie M (2010) Numerical study of helicopter blade–vortex mechanism of
interaction using the potential flow theory. Appl Math Model 36(7):2841–2857
4. Dwivedi Y, Jagadish D, Sridhar V (2016) Aerodynamic analysis of corrugated winglet for
improved MAV performance
5. Sridhar V, Dwivedi Y (2017) Effect of peak shape in bio inspired corrugated wing. In:
International conference on advances in thermal systems, materials and design engineering
(ATSMDE2017)
6. Dwivedi Y et al (2017) Computational study of fluid flow behavior over bio-inspired corrugated
airfoil for micro aerial vehicles. In: International conference on advances in thermal systems,
materials and design engineering (ATSMDE2017)
7. Esakki B et al (2018) Design of amphibious vehicle for unmanned mission in water quality
monitoring using internet of things. Sensors 18(10):3318
8. Ganesan S, Esakki B (2019) Design and development of unmanned hovercraft
9. Filippone A, Michelsen J (2001) Aerodynamic drag prediction of helicopter fuselage. J Aircr
38(2):326–333