The detailed design phase encompassed all the final dimensions and derived airworthiness capabilities of the aircraft model to be flown. Following that of the preliminary stage through the structural analysis, CFD analysis, weight balance, etc.
The coefficient of drag and total drag were calculated to determine the amount of power consumed and thrust required throughout each phase of flight. To anticipate the stability and control of the UAV, longitudinal, lateral, and directional stability assessments were performed. The take-off study, structure analysis along the wing, CFD study of the wing, and weight-balance calculations were also performed.
4.1 Coefficient of drag calculation
The total drag was estimated by adding the wing, fuselage, empennage, and landing gear drags together. The overall drag was overestimated by 5% to account for interference drag along the wing and fuselage, as well as induced flow through the propeller.
Also, the drag polar can be obtained by taking the drag of the wing and tail as a function of coefficient of lift.
Where, = 0.021 and K = 0.0639
4.2 Structural Analysis
The design goal for the structure of the UAV was to ensure that all loads (Thrust Loads, Aerodynamic Loads, and Ground Loads) were accounted for and had an adequate load path to the major load-bearing components.
The aircraft structure also depends on the performance analysis of accelerated flight. First, constraints on load factor are analyzed concerning flight velocity and found that the maximum load factor value was 5. Also, from the analysis of constraints on load factor and the historical data for homebuilt aircraft, the structural capability of the final design illustrated inside a V-n diagram which is an effective way to determine and display the aircraft’s structural limitations and its flight envelope [16]. The V-n diagram shown in Fig. 4.
As weight is the most crucial parameter causing increased load and drag, the aircraft must be as light as possible. Thus, before finalizing a formal, detailed design, the aircraft loads along the wing were analyzed in both flight and landing scenarios. Figure 5 and Fig. 6 showed a 3D analysis of the shear force and bending moment on the wing, including the chord of the wing, respectively, using MATLAB.
4.3 Aircraft Performance Estimation
To begin, a take-off distance analysis was performed. This test was performed to ensure that the propulsion system could generate the requisite amount of power for the UAV to fly. During the analysis, the payload carrying capacity as well as the runway's functional co-efficient were taken into account. Figure 7 depicts the results. The take-off distance was under 30 feet for a coefficient of 0.02, and it could carry up to 10 pounds of payload.
The individual mission performance of the aircraft was estimated using data from weight, aerodynamic performance, and power sizing. Both missions necessitate the aircraft's maximum rate of climb, which is attained when the aircraft is moving at the speed that provides the greatest difference between power required (PR) and power available (PA) as shown in Fig. 8.
Using the result from Fig. 8 in the equations of motion, a maximum rate of climb of 7.22 ft/s is obtained. At that rate, it will take 2.5 seconds to climb to 5 meters (minimum height above the ground for each mission). To estimate how the aircraft will perform in mission 1, the airplane’s maximum speed or the static speed was found to be 84 ft/s (With the assumption that a 60-degree turn takes 1.63 seconds, the time for one lap is 6.53 seconds.) when the required power (PR) for the flight was equal to the power available (PA) in the aircraft propulsion system. Mission 2 is graded based on flight weight. Using the estimation of empty weight, added a payload of 1.76 lbs (4 payloads) .A low cruise speed of 48 ft/s will be used to ensure a high margin of safety and minimize battery use. The mission performance estimation is shown in Table 5.
Table 5: Mission Performance Estimation
Mission 1
|
Mission 2
|
Empty weight
|
3.09 lb
|
Empty weight
|
3.09 lb
|
Static velocity
|
84 ft/s
|
Cruise velocity
|
48 ft/s
|
Turn time
|
(4 x 1.63) sec
|
Turn time
|
(4 x 1.63) sec
|
Lap time
|
(3 x 6.53) sec
|
|
|
Max. Empty weight
|
3.09 lb
|
Rate of Climb
|
7.22 ft/s
|
Table 6: Control Surfaces, Propulsion System and Payload Bay Details
Name of Component
|
Parameters
|
Type/Dimension
|
Aileron
|
Span
|
38 in
|
Chord
|
1.5 in
|
Deflection
|
20°
|
Elevator
|
Span
|
18.7 in
|
Chord
|
1 in
|
Deflection
|
30°
|
Rudder
|
Span
|
12.38 in
|
Chord
|
1 in
|
Deflection
|
15°
|
Propulsion System
|
Power
|
1500 W
|
Motor
|
GT2820-07 Brushless Out-Runner Motor
|
Batteries
|
3S 11.1 V 2200mAh 30C LiPo Battery
|
Cells
|
3
|
Payload Bay
|
No. of Compartment
|
4
|
Compartment Length
|
1.98 in
|
Compartment Width
|
1.98 in
|
Table 7
System Description
System/Sub-system
|
Description
|
Fuselage
|
It is made of balsa wood where plywood has been used for strengthening the structure.
|
Payload Bay
|
It consists of four compartments, each having separate locking mechanism using a servo for operation. There are thin walls separating all four payload unit.
|
Wing
|
It has two divided parts each of starboard and port side. Each half-wing has 25.83 in of span where 10 ribs were provided for structural integrity and strength. Also, four spars were constructed. The whole skeleton-structure was enveloped by finely cut balsa wood of 1 mm of thickness.
|
Empennage
|
The horizontal and vertical tail has 6 mm thickness of balsa wood structure.
|
Tail Boom
|
It is a carbon fiber pipe providing for both high-load bearing capability and less weight.
|
Payload Drop Mechanism
|
It is a simple sliding door lock mechanism.
|
Battery
|
It is a Turnigy 2200mAh 3S 30C LiPo battery pack.
|
Motor
|
It is EMAX GT2820-07 Brushless Out-Runner Motor.
|
Propeller
|
It is as supported by the motor and its material is Carbon Finer. It is of the APC origin designed for electrical motor mount
|
Speed Controller
|
TURNIGY Plush 30A speed controller w/BEC.
|
Servo Mechanism
|
There are total 8 servos to provide for the required maneuvering.
|
Landing Gear
|
The undercarriage is a simple Aluminum-made rod bent for convenient use. The wheels are added from conventional shops.
|
|
4.4 Longitudinal stability analysis
Longitudinal static stability guarantees balance in all conditions, even if the aircraft moves away from the trim position due to a disturbance. Based on the longitudinal stability analysis, the horizontal stabilizer parameters were derived.
4.5 Lateral stability analysis
To restore the moment and yaw generated by side force, lateral stability is required. A negative rolling moment from the aileron is necessary to restore those rolling tendencies. Table 6 summarizes the obtained parameters for aileron surface and maximum deflection angle based on these conditions.
4.6 Directional stability analysis
The vertical stabilizer and rudder are critical for canceling aileron drag (adverse yaw), which occurs when the airplane is banked. Another important factor is the destabilizing moment caused by the propeller's induced flow, which is difficult to control. The final parameters of the vertical stabilizer and rudder are presented in Table 4 and Table 6 respectively based on these constraints.
4.7 Aerodynamic Capabilities of Wing
Before the UAV was built, a 3D computational fluid dynamics (CFD) analysis of the wing was undertaken. For addressing the 3D analysis, the general steps for numerical solution, such as the computational domain, meshing topology, and density, turbulence model, and numerical scheme, were specified. The computational domain (as illustrated in Fig. 9) was formed to apply the requisite boundary conditions. The velocity inlet boundary condition was applied at a distance of 5C from the wing leading edge. At a distance of 8C, a pressure outlet boundary condition was applied. The wing surface and wing tips' boundary conditions were modeled as non-slip walls.
After that, the domain was divided into different dimensions elements. This approach used an unstructured mesh to construct nearly 776,481 tetrahedron elements and 245,617 nodes over the domain. Because of the improved numerical solution, a significantly denser and more refined mesh was generated in the region of the wing surface. The mesh around the wing surface is shown in Fig. 10. A value of y + less than 2 was chosen to solve the partial differential equations near the viscous sub-layer. The normal distance between the nearest wall and the nodal point of the first layer was 1.554 x 10− 3 in.
One of the most important aspects of CFD analysis is choosing a turbulence model. Flow separation over the wing occurs at a stall angle of attack. The two-equation shear stress transport (SST) k-ω model provides the biggest advantages over separating flows and in adverse pressure gradients, according to the literature review. As a result, the SST k-w model was chosen to better anticipate fluctuating flow rates.
The validation study with a coefficient of lift for varied AOA from − 4º to 14º is shown in Fig. 11 for both computational and experimental results. For all AOA, the computational analysis were slightly higher than those of the experimental analysis. The causes behind this were manufacturing difficulties with the E423 airfoil's curvature, as well as the roughness of the wing surface, both of which are negligible in numerical analysis.
The static pressure distribution over the wing is depicted in Fig. 12. The maximum pressure was measured at the leading edge of the upper surface of the wing, then gradually decreased along the chord length.