Keywords

1.1 Introduction

The advancement in today’s technology has extended the boundaries of drone technologies. The major application of drones is in military, civil, and agriculture services. Due to its wide applications, drones are now used for delivery purposes to solve efficient and reduced delivery time problems [1]. The major advantage of drone is they can cut short 80% of delivery time compared to ground vehicles based on their flexible routes and parallelized operations [2]. Due to their cheap, flexible, and fast delivery drones can bring revolution to delivery department.

The shape and size of the cargo container in delivery drone play a vital role in overall efficiency of the operation as most of the cargo containers are rectangular in shape which occupies a huge air resistance at its surface making overall delivery drone design less efficient. Some studies did airflow analysis on different structures of freight vehicles and it has been observed that the streamline shape is most efficient as air flows smoothly over the surfaces at high wind speed operation [3]. The main demerit of an ideal rectangular shape cargo container is that at high-speed operations the container becomes heavily unstable and limits the operational speed [4]. Therefore, we redesign the structure of cargo container into an ellipse shape, changed the material of construction to make it durable- lightweight, and carried out CFD analysis to know the results with respect to efficiency, control, and dynamics. The new design is separated into three different storing sections to utilize space and maintain equal weight distribution during operation.

1.2 Literature Review

The advancement in today’s technology has pushed the boundaries of drone application; drones when attached to a cargo container can deliver various products in less time and more efficiently [5]. If we consider suburban areas and compare deliveries by a truck-only delivery and truck-drone delivery we see that the truck-only delivery is very advantageous economically [6]. Thus, it is important to study the drone characteristics and airflow analysis to be economical. Changing the design of light UAVS has resulted in more stability and performance [7]. These days drones can also perform their operations in automated modes with high velocity where their operation paths are predefined, Path generation is achieved by a unit quaternion curve and an associated parallel transport frame in the interactive process. [8]. But, it is important to select the specific type of drone for the delivery operations with respect to weight of cargo as more the number of motors and blades it has the more it consumes power, therefore, a study was conducted on octocopter drone and dodecacopter drone with, without periodic disturbance and it was observed that octocopter is more stable than dodecacopter without disturbance [9]. Hence, we can choose octocopter application for delivery drones.

The aerodynamic characteristic of the cargo container plays a major role in stability and performance parameters in delivery drones. A study on freight wagon was done where airflow analysis was done on the freight wagon the Reynolds number of the flow came out to be 105 [10]. Such shape containers with slung load are subject to massively separated unsteady flow and are limited by stability to operational airspeeds well below the power‐limited speed of the configuration [4]. Thus, we believe there needs to be change in design of cargo containers for high-speed delivery applications. The shape can withstand the high-speed drag, giving more stability and dynamic controls. Cargo can be highly unstable while in motions and needed to be tied up for so but, locking and unlocking cargo can consume more time hence, we can use baffle at different intersections of container to reduce the instability of cargo similar to baffle used in liquid containers which reduces the amplitude of fluid slosh in partly filled tanks [11].

1.2.1 Proposed Design

The design is developed on Autodesk software, the conventional design of cargo section is rectangular shaped so we modified it to give the cargo section a shape of an ellipse (Fig. 1.1). This design is aimed to minimize resistance and drag caused by air thus making cargo section more aerodynamic and will eventually enhance the productivity of the drone to carry out the delivery operation in a less time and power.

Fig. 1.1
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3D view of proposed cargo container

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The exterior of the design is developed like an ellipse shape as it has very less air resistance, the front and back edges have smooth (Fig. 1.2), which helps in creating aerodynamic path and increases controls due to less air resistance.

Fig. 1.2
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Top view of proposed cargo container for drone application

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The interior of the cargo section is divided into three parts namely cargo1, cargo2, cargo3 separated by baffle (Fig. 1.3). We have divided it into three parts because by separating each compartment the weight distribution will be balanced and there will be less chances of instability while in motion.

Fig. 1.3
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Interior of proposed cargo container for drone application

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The cargo areas 2 and 3 are built to store small or lightweight goods whereas cargo area 1 has large storage area for large heavy goods. They both have separate doors for loading unloading cargo situated at top. The interior of the new design consists of single door situated between the cargo area 1 and 3 and also performs as baffle between the surfaces (Fig. 1.3). The door lock mechanism and stopper will be situated at top and bottom of cargo area 1. Additionally, user can construct an area on top of cargo area 1 to mount the container and drone. The top view of the design is replica of bottom view shown in Fig. 1.4 and the back view of the design is replica of front view of design shown in Fig. 1.5.

Fig. 1.4
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Bottom view of proposed cargo container for drone application

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Fig. 1.5
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Front view of proposed cargo container for drone application

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1.2.2 CFD Analysis

We carried out computation fluid dynamics (CFD) analysis on ANSYS 2021 software. Table 1.1 shows the analysis parameters. The design was exported to ANSYS for simulation results. The airflow analysis was performed with Air as inlet material, we first exported the design and various geometry were set which provided the enclosure. Meshing was done and various input parameters were given mentioned below for simulation result.

Table 1.1 Analysis parameters
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In computational fluid dynamics, the k-omega (k–ω) turbulence model is a common two-equation turbulence model that is used as an approximation for the Reynolds-averaged Navier–Stokes equations (RANS equations). The model attempts to predict turbulence by two partial differential equations for two variables, k, and ω, with the first variable being the turbulence kinetic energy (k) while the second (ω) is the specific rate of dissipation (of the turbulence kinetic energy k into internal thermal energy). This design required SST k-omega turbulence model to calculate the value of lift force and drag force.

The two-equation model (written in conservation form) is given by the following:

$$\partial \left( {\frac{\rho k}{{\partial t}}} \right) + \frac{{\partial \left( {\rho ujk} \right)}}{\partial xj} = P - \beta^{*} \partial \omega k + \frac{\partial }{\partial xj}\left[ {\left( {\mu + \sigma_{k} \frac{\rho k}{\omega }} \right)\frac{\partial k}{{\rho xj}}} \right]$$

where,

$$Sij = \frac{1}{2}\left( {\frac{\partial uj}{{\partial xi}} + \frac{\partial uj}{{\partial xi}}} \right)$$

1.3 Result and Discussion

Figures 1.6, 1.7, 1.8, 1.9, 1.10, 1.11, and 1.12 are derived from airflow simulation and we can see that the graph stables up after peak of air which shows the lower air resistance on surfaces.

Fig. 1.6
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Pressure contour line with respect to Pascal

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Fig. 1.7
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Velocity contour lines with respect to kilohertz

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Fig. 1.8
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Velocity streamlines with respect to kilohertz

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Fig. 1.9
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Scaled residual plot, where x-axis is number of iterations and y-axis is equal to residuals

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Fig. 1.10
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Lift force plot, where x-axis is number of iteration and y-axis is equal to Coefficient of lift

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Fig. 1.11
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Drag coefficient plot, where x-axis is number of iteration and y-axis is equal to coefficient of drag

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Fig. 1.12
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Air inlet and outlet inside enclosure

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Figure 1.6: In CFD-POST, the figure shows the pressure magnitude by the means of contour lines dawn on a physical body. The pressure values have been maintained at constant atmospheric pressure. The difference in contour lines and its color clearly shows the pressure difference at inlet and outlet.

Figure 1.7: In CFD-POST, we can see the velocity difference of air at inlet and outlet. The inlet velocity has been set to be 30 m/s while at outlet the velocity is set to default. The velocity of air at inlet will be much more than the velocity at outlet. The difference has been demonstrated with the help of contour lines.

Figure 1.8 shows the flow of massless particles through the entire domain to show the velocity difference at different points on the domain.

Figure 1.9 directly quantifies the error in the solution of the system of equations, as it measures the local imbalance of conserved variables in each control volume. The graph represents the residual value of every cell solved equation.

Figure 1.10 is the lift force graph, as the graph stables up after some readings it specifies the lift performance of the new design.

Figure 1.11 is the drag coefficient plot which specifies the air resistance on the surface; the graph gets constant after the initial force, i.e., air gets diverged through first phase of air, increasing the aerodynamic of design. Figure 1.12 is the plot of fluid flow from inlet to outlet, in the figure the blue arrow shows the direction of fluid through inlet section under the enclosure section and red arrow specifies the outlet of fluid.

1.4 Conclusion

From the CFD results, we can say that the newly designed shape of cargo container for drone application is more practical to use as the new design results in less drag due to its curved shape from front and backside which helps in resisting air to a great extent, the new material of construction which is carbon fiber make design durable and helps in decreasing weight.

When the design comes in contact with high wind it becomes aerodynamic and its controls increase, the easier it is for a drone carrying cargo to move, the less energy the system needs making it a valuable part for delivery drones operating at high speed.