A simulation method and system for airflow and droplet deposition within the canopy.

Abstract

This invention discloses a simulation method and system for airflow and droplet deposition within a canopy, relating to the field of canopy interior simulation technology. The method includes: determining a rotation domain, a canopy domain, a computational domain, a fluid mesh model, and a solid mesh model; setting requirements for the fluid mesh model using Fluent software; converting the solid mesh model into a particle model using LS-DYNA software and setting requirements thereafter; setting the number of simulation steps, the time represented by each step, and the simulation termination conditions; repeating the simulation process until the simulation termination conditions are met, and outputting the simulation results for airflow and droplet deposition within the canopy. This invention achieves the simulation of airflow and droplet deposition within the canopy.

Description

Technical Field

[0001] This invention relates to the field of canopy interior simulation technology, and in particular to a method and system for simulating airflow and droplet deposition within the canopy. Background Technology

[0002] In the process of sustainable agricultural development, pest and disease control has always been a focus of attention. Agricultural drones, as an important tool for pest and disease control, have gained widespread attention due to their flexibility and convenience, and have made new progress in pest and disease control. However, during drone application, the impact of the crop canopy on the downwash airflow of the rotor cannot be ignored. The downwash airflow carries droplets, affecting their spatial movement and adhesion and penetration within the canopy. Therefore, clarifying the airflow and its patterns during agricultural drone application of pesticides to fruit trees is crucial for assessing the deposition effect of droplets within the canopy, thereby enabling targeted improvements in the efficiency of drone application.

[0003] Currently, there are two main methods for simulating airflow patterns within the canopy using computational fluid dynamics (CFD): (1) Porous media – constructing virtual crops. Since the resistance of the crop canopy causes a loss of downwash flow, this method constructs a virtual crop model through geometric modeling. The entire computational domain is divided into structural meshes, and a virtual crop canopy is established in the structural mesh based on the actual measured relative position of the UAV and the crop. Then, the resistance of the flow field on the canopy is set in the porous media region through Fluent simulation. The main parameters are the inertial drag coefficient and the viscous drag coefficient. (2) Porous media – static porosity similarity method. This method is based on the inherent hierarchy and order formed by the fractal characteristics of crop morphology and structure. The crop population is abstracted into layers of porous media planes with different porosities. By combining enough planes with different optical porosities according to their height, the crop population under this porosity can be approximately described. Different static porosities are set to represent different crops or different growth forms of crops. By establishing and performing simulation calculations of UAV spray under different static porosities in CFD, the spatial distribution of droplets under different porosities can be obtained.

[0004] Because porous media only add an additional momentum loss to the momentum equation, their effect on turbulence is only approximate, leading to some distortion of the flow field. The airflow velocity and droplet deposition within the constructed virtual crop cannot be accurately measured, meaning they cannot reflect the turbulent distribution inside the crop after airflow passes through it in actual operations. Furthermore, the static porosity similarity method produces simulations that differ from actual operations, failing to accurately simulate the real situation. Therefore, existing technologies have low accuracy in simulating airflow and droplet deposition within the canopy, resulting in poor performance in targeted improvements to the efficiency of drone-based pesticide application. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for simulating airflow and droplet deposition within the canopy, thereby simulating airflow and droplet deposition within the canopy.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for simulating airflow and droplet deposition within a canopy, the method comprising:

[0008] Construct a drone rotor source model and a fruit tree canopy model;

[0009] The rotation domain of the UAV rotor is determined based on the aforementioned UAV rotor source model;

[0010] The canopy domain of the fruit tree is determined based on the aforementioned fruit tree canopy model;

[0011] The computational domain is determined based on the rotation domain and the canopy domain;

[0012] Based on the rotation domain, the canopy domain, and the computational domain, a fluid geometry model is constructed;

[0013] The fluid geometry model is meshed to obtain a fluid mesh model;

[0014] Using Fluent software, the surfaces in the computational domain other than the bottom surface are set as pressure outlets, and the bottom surface is set as a wall. The rotational speed of the UAV rotor is set according to the payload of the UAV where the UAV rotor source model is located. The center and direction of the rotation domain are set. A discrete phase model of droplet motion is established. The nozzle position is determined to be 0.1m to 0.5m directly below the UAV rotor, the injection half angle is 10° to 90°, the injection flow rate is 0.005kg / s to 0.02kg / s, the release time is 0 to 10s, and the orifice width is 0.0005 to 0.001. The turbulence model is determined to be SSTk-ω, the solution method is set to double precision, and the iteration method is set to coupled iteration.

[0015] The canopy domain is meshed to obtain a solid mesh model;

[0016] Using LS-DYNA software, the region containing the solid mesh model is transformed into a particle model. Particle parameters are set, including density, type, and size. The contact surface between the particles in the solid domain and the mesh in the fluid domain is set. The total number of particles and the generation rate are set. The particle generation method is set to dynamic particle generation. During the simulation, the number of particles generated is specified to be the same as the number of meshes in the canopy domain. The coupling interface between the outer wall and the fluid mesh model is set to fully analytical.

[0017] Set the number of simulation steps, the time represented by each step, and the simulation termination conditions;

[0018] The simulation process is repeated until the simulation termination condition is met, and the simulation results of airflow and droplet deposition inside the canopy are output. The simulation process is as follows: the fluid mesh model results for one simulation step are solved in the Fluent environment, and the particle model results for one simulation step are solved in the LS-DYNA environment; the data exchange between the fluid mesh model results and the solid mesh model results is performed through the coupling interface.

[0019] Optionally, the process of establishing the UAV rotor source model specifically includes:

[0020] Obtain the structural parameters of the UAV rotor, including: outer diameter, pitch, thickness, and tilt angle;

[0021] The UAV rotor source model is established based on the structural parameters.

[0022] Optionally, the process of establishing the fruit tree canopy model specifically includes:

[0023] Obtain fruit tree parameters; the fruit tree parameters include the lowest point of the canopy, the highest point of the canopy, the outer diameter of the canopy, and the canopy density;

[0024] The fruit tree canopy model is established based on the fruit tree parameters.

[0025] A simulation system for airflow and droplet deposition within a canopy, the system comprising:

[0026] The model building module is used to construct drone rotor source models and fruit tree canopy models;

[0027] The rotation domain determination module is used to determine the rotation domain of the UAV rotor based on the UAV rotor source model.

[0028] The canopy domain determination module is used to determine the canopy domain of the fruit tree based on the fruit tree canopy model.

[0029] A computational domain determination module is used to determine the computational domain based on the rotational domain and the canopy domain;

[0030] A fluid geometry model determination module is used to construct a fluid geometry model based on the rotation domain, the canopy domain, and the computational domain;

[0031] The fluid mesh model determination module is used to perform mesh generation on the fluid geometry model to obtain the fluid mesh model;

[0032] The first setting module is used to use Fluent software to set the surfaces in the computational domain other than the bottom surface as pressure outlets, set the bottom surface as a wall, set the rotational speed of the UAV rotor according to the payload of the UAV where the UAV rotor source model is located, set the center and direction of the rotation domain, establish a discrete phase model of droplet motion, determine that the nozzle position is 0.1m to 0.5m directly below the UAV rotor, the injection half angle is 10° to 90°, the injection flow rate is 0.005kg / s to 0.02kg / s, the release time is 0 to 10s, the orifice width is 0.0005 to 0.001, determine the turbulence model as SSTk-ω, set the solution method as double precision, and determine the iteration method as coupled iteration.

[0033] A solid mesh model determination module is used to perform mesh generation on the canopy domain to obtain a solid mesh model;

[0034] The second setting module is used to transform the region where the solid mesh model is located into a particle model using LS-DYNA software, set particle parameters including density, type and size, set the contact surface between the particles in the solid domain and the mesh in the fluid domain, set the total number of particles and the generation rate, set the particle generation method to the particle dynamic generation method, specify that the amount of particles generated is the same as the number of meshes in the canopy domain during simulation, and set the coupling interface between the outer wall and the fluid mesh model to fully analytical.

[0035] The third settings module is used to set the number of simulation steps, the time represented by each step, and the simulation termination conditions.

[0036] The simulation module is used to repeatedly execute the simulation process until the simulation termination condition is met, and output the simulation results of airflow and droplet deposition inside the canopy. The simulation process is as follows: solve the fluid mesh model results for one simulation step in the Fluent environment, and solve the particle model results for one simulation step in the LS-DYNA environment; and exchange data between the fluid mesh model results and the solid mesh model results through the coupling interface.

[0037] Optionally, the model building module includes a UAV rotor source model building submodule, which specifically includes:

[0038] A structural parameter acquisition unit is used to acquire the structural parameters of the UAV rotor, including: outer diameter, pitch, thickness, and tilt angle;

[0039] The UAV rotor source model building unit is used to build the UAV rotor source model based on the structural parameters.

[0040] Optionally, the model building module includes a fruit tree canopy model building sub-module, which specifically includes:

[0041] The fruit tree parameter acquisition unit is used to acquire fruit tree parameters, including the lowest point of the canopy, the highest point of the canopy, the outer diameter of the canopy, and the canopy density.

[0042] The fruit tree canopy model establishment unit is used to establish the fruit tree canopy model based on the fruit tree parameters.

[0043] This invention discloses a method and system for simulating airflow and droplet deposition within a canopy. The method includes: constructing a UAV rotor source model and a fruit tree canopy model; determining the rotation domain of the UAV rotor based on the UAV rotor source model; determining the canopy domain of the fruit tree based on the fruit tree canopy model; determining the computational domain based on the rotation domain and the canopy domain; constructing a fluid geometry model based on the rotation domain, the canopy domain, and the computational domain; meshing the fluid geometry model to obtain a fluid mesh model; and using Fluent software, setting the surfaces in the computational domain except for the bottom surface as... As a pressure outlet, the bottom surface is set as a wall. The rotational speed of the UAV rotor is set according to the payload of the UAV containing the UAV rotor source model. The center and direction of the rotation domain are set. A discrete phase model of droplet motion is established. The nozzle position is determined to be 0.1m–0.5m directly below the UAV rotor, the injection half-angle is 10°–90°, the injection flow rate is 0.005kg / s–0.02kg / s, the release time is 0–10s, and the orifice width is 0.0005–0.001. The turbulence model is determined to be SST. The simulation process involves setting the solution method to double precision (k-ω) and the iteration mode to coupled iteration. The canopy domain is meshed to obtain a solid mesh model. Using LS-DYNA software, the solid mesh model is transformed into a particle model. Particle parameters, including density, type, and size, are set. The contact surface between the particles in the solid domain and the mesh in the fluid domain is defined. The total number of particles and their generation rate are set, and the particle generation method is set to dynamic particle generation. During simulation, the number of particles generated is specified to be the same as the number of meshes in the canopy domain. The coupling interface between the outer wall and the fluid mesh model is set to fully analytical. The simulation step size, the time represented by each step, and the simulation termination condition are set. The simulation process is repeated until the simulation termination condition is met, and the simulation results of airflow and droplet deposition within the canopy are output. The simulation process involves solving the fluid mesh model for one simulation step in the Fluent environment and solving the particle model for one simulation step in the LS-DYNA environment. Data exchange between the fluid mesh model results and the solid mesh model results is performed through the coupling interface. This invention achieves the simulation of airflow and droplet deposition within the canopy. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A schematic diagram of the simulation method for airflow and droplet deposition inside the canopy provided in an embodiment of the present invention;

[0046] Figure 2 Schematic diagram of the computational domain, canopy domain, and rotation domain;

[0047] Figure 3 This is a schematic diagram of a particle model;

[0048] Figure 4 This is a schematic diagram of a simulation system for airflow and droplet deposition inside the canopy, provided as an embodiment of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] The purpose of this invention is to provide a method and system for simulating airflow and droplet deposition within the canopy, aiming to simulate airflow and droplet deposition within the canopy.

[0051] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0052] Figure 1 This is a schematic diagram of a simulation method for airflow and droplet deposition within the canopy, provided in an embodiment of the present invention. Figure 1 As shown, this embodiment illustrates a method for simulating airflow and droplet deposition within a canopy. The method includes:

[0053] Step 101: Construct the UAV rotor source model and the fruit tree canopy model.

[0054] Step 102: Determine the rotation domain of the UAV rotor based on the UAV rotor source model.

[0055] Step 103: Determine the canopy domain of the fruit tree based on the fruit tree canopy model.

[0056] Step 104: Determine the computational domain based on the rotation domain and the canopy domain.

[0057] Specifically, such as Figure 2As shown, the computational domain encompasses both the rotational domain and the canopy domain. The projected area of ​​the computational domain is 3 to 5 times the size of the projected area of ​​the canopy domain, completely enclosing the rotational domain and placing the canopy domain at the center of the computational domain. The computational domain is typically set as a cuboid or cylinder, and its size needs to allow sufficient space for airflow development. Airflow flows within the defined computational domain, and theoretically, the larger the better. However, a larger computational domain requires more computational resources, so the waste of computational resources must also be considered.

[0058] Step 105: Construct a fluid geometry model based on the rotation domain, canopy domain, and computational domain.

[0059] Step 106: Mesh the fluid geometry model to obtain the fluid mesh model.

[0060] Step 107: Use Fluent software to set requirements for the fluid mesh model.

[0061] Step 107 specifically involves: using Fluent software, setting all surfaces in the computational domain except the bottom surface as pressure outlets, setting the bottom surface as a wall, setting the rotor speed of the UAV (1500rpm~3000rpm) according to the payload (5kg~15kg) of the UAV rotor source model, setting the center and direction of the rotation domain, establishing a discrete phase model of droplet motion, determining the nozzle position to be 0.1m~0.5m directly below the UAV rotor, the injection half-angle to be 10°~90°, the injection flow rate to be 0.005kg / s~0.02kg / s, the release time to be 0~10s, and the orifice width to be 0.0005~0.001, determining the turbulence model to be SSTk-ω, setting the solution method to double precision, and determining the iteration method to be coupled iteration.

[0062] For example, using Fluent software, the surfaces in the computational domain other than the bottom surface are set as pressure outlets, the bottom surface is set as a wall, the UAV rotor speed is set to 1500rpm~2500rpm, the center and direction of the rotation domain are set, a discrete phase model of droplet motion is established, the nozzle position is determined to be 0.25m directly below the UAV rotor, the spray half-angle is 55°, the spray flow rate is 0.00833kg / s, the release time is 0~10s, the orifice width is 0.0007, the turbulence model is determined to be SSTk-ω, the solution method is set to double precision, and the iteration mode is determined to be coupled iteration. The nozzle position can be adjusted according to the actual situation, within 0.1m~0.5m; the spray half-angle can be adjusted according to the actual situation, within 10°~90°; the spray flow rate can be adjusted according to the actual situation of the nozzle's water pump, within 0.005kg / s~0.02kg / s; and the orifice width can be adjusted according to the actual situation of the nozzle.

[0063] Specifically, the surfaces of the computational domain other than the bottom surface are set as pressure outlets (pressureoutlet in Fluent software), with an initial value of 0; the bottom surface is set as a wall (wall in Fluent software); the direction of the rotation domain is clockwise or counterclockwise, which can be set according to the actual situation of the rotor distribution.

[0064] Step 108: Mesh the canopy domain to obtain a solid mesh model.

[0065] Step 109: Using LS-DYNA software, convert the solid mesh model into a particle model and set the requirements.

[0066] Step 109 specifically involves: using LS-DYNA software to transform the region containing the solid mesh model into a particle model; setting particle parameters, including density, type, and size; setting the contact surface between the particles in the solid domain and the mesh in the fluid domain; setting the total number of particles and their generation rate; setting the particle generation method to dynamic particle generation; specifying that the amount of particles generated during simulation is the same as the number of meshes in the canopy domain; and setting the coupling interface between the outer wall and the fluid mesh model to fully analytical. For example... Figure 3 As shown, the particle model is Smoothed Particle Hydrodynamics, also known as the SPH model.

[0067] Specifically, according to the SPH particle parameter reference table, the density can be approximately obtained from the actual density of the canopy, and the type and size can be set according to the actual upper, middle and lower layers, and can be approximately obtained from the maturity and softness of the canopy leaves.

[0068] Step 110: Set the number of simulation steps, the time represented by each step, and the simulation termination conditions.

[0069] Specifically, settings can be configured according to the actual situation, such as setting a sufficiently long number of simulation steps to allow the simulation results to converge, for example, 4000 to 10000 steps, setting the time represented by each simulation step (for example, 0.001 seconds), and setting the simulation termination condition (i.e., the simulation residual convergence condition), which ends when the simulation residual is less than 0.00001.

[0070] Step 111: Repeat the simulation process until the simulation termination conditions are met, and output the simulation results of airflow and droplet deposition inside the canopy. The simulation process is as follows: solve the fluid mesh model results for one simulation step in the Fluent environment, and solve the particle model results for one simulation step in the LS-DYNA environment; exchange data between the fluid mesh model results and the solid mesh model results through the coupling interface.

[0071] As an optional implementation method, the process of establishing the UAV rotor source model specifically includes:

[0072] Obtain the structural parameters of the UAV rotor, including: outer diameter, pitch, thickness, and tilt angle.

[0073] A model of the UAV rotor source was established based on the structural parameters.

[0074] As an optional implementation method, the process of establishing a fruit tree canopy model specifically includes:

[0075] Obtain fruit tree parameters; fruit tree parameters include the lowest point of the canopy, the highest point of the canopy, the outer diameter of the canopy, and the canopy density.

[0076] Establish a fruit tree canopy model based on fruit tree parameters.

[0077] Figure 4 This is a schematic diagram of a simulation system for airflow and droplet deposition within the canopy, provided as an embodiment of the present invention. Figure 4 As shown, the simulation system for airflow and droplet deposition within the canopy in this embodiment includes:

[0078] Model building module 201 is used to build a UAV rotor source model and a fruit tree canopy model.

[0079] Rotation domain determination module 202 is used to determine the rotation domain of the UAV rotor based on the UAV rotor source model.

[0080] The canopy domain determination module 203 is used to determine the canopy domain of the fruit tree based on the fruit tree canopy model.

[0081] The computational domain determination module 204 is used to determine the computational domain based on the rotation domain and the canopy domain.

[0082] The fluid geometry model determination module 205 is used to construct a fluid geometry model based on the rotation domain, the canopy domain, and the computational domain.

[0083] The fluid mesh model determination module 206 is used to mesh the fluid geometry model to obtain the fluid mesh model.

[0084] The first setting module 207 is used to use Fluent software to set the surfaces in the computational domain other than the bottom surface as pressure outlets, set the bottom surface as a wall, set the rotational speed of the UAV rotor according to the payload of the UAV where the UAV rotor source model is located, set the center and direction of the rotation domain, establish a discrete phase model of droplet motion, determine that the nozzle position is 0.1m to 0.5m directly below the UAV rotor, the injection half angle is 10° to 90°, the injection flow rate is 0.005kg / s to 0.02kg / s, the release time is 0 to 10s, the orifice width is 0.0005 to 0.001, determine the turbulence model as SSTk-ω, set the solution method as double precision, and determine the iteration method as coupled iteration.

[0085] The solid mesh model determination module 208 is used to mesh the canopy domain to obtain a solid mesh model.

[0086] The second setting module 209 is used to transform the region where the solid mesh model is located into a particle model using LS-DYNA software, set particle parameters, including density, type and size, set the contact surface between the particles in the solid domain and the mesh in the fluid domain, set the total number of particles and the generation rate, set the particle generation method to the particle dynamic generation method, specify that the amount of particles generated is the same as the number of meshes in the canopy domain during simulation, and set the coupling interface between the outer wall and the fluid mesh model to fully analytical.

[0087] The third setting module 210 is used to set the number of simulation steps, the time represented by each step, and the simulation termination conditions.

[0088] Simulation module 211 is used to repeatedly execute the simulation process until the simulation termination condition is met, and output the simulation results of airflow and droplet deposition inside the canopy. The simulation process is as follows: solve the fluid mesh model results for one simulation step in the Fluent environment, and solve the particle model results for one simulation step in the LS-DYNA environment; exchange data between the fluid mesh model results and the solid mesh model results through the coupling interface.

[0089] As an optional implementation, the model building module 201 includes a UAV rotor source model building submodule, which specifically includes:

[0090] The structural parameter acquisition unit is used to acquire the structural parameters of the UAV rotor, including: outer diameter, pitch, thickness, and tilt angle.

[0091] The UAV rotor source model building unit is used to build a UAV rotor source model based on structural parameters.

[0092] As an optional implementation, the model building module 201 includes a fruit tree canopy model building submodule, which specifically includes:

[0093] The fruit tree parameter acquisition unit is used to acquire fruit tree parameters, including the lowest point of the canopy, the highest point of the canopy, the outer diameter of the canopy, and the canopy density.

[0094] The fruit tree canopy model building unit is used to build a fruit tree canopy model based on fruit tree parameters.

[0095] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0096] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for simulating airflow and droplet deposition within a canopy, characterized in that, The method includes: Construct a drone rotor source model and a fruit tree canopy model; The rotation domain of the UAV rotor is determined based on the aforementioned UAV rotor source model; The canopy domain of the fruit tree is determined based on the aforementioned fruit tree canopy model; The computational domain is determined based on the rotation domain and the canopy domain; Based on the rotation domain, the canopy domain, and the computational domain, a fluid geometry model is constructed; The fluid geometry model is meshed to obtain a fluid mesh model; Using Fluent software, the surfaces in the computational domain other than the bottom surface are set as pressure outlets, and the bottom surface is set as a wall. The rotational speed of the UAV rotor is set according to the payload of the UAV where the UAV rotor source model is located. The center and direction of the rotation domain are set. A discrete phase model of droplet motion is established. The nozzle position is determined to be 0.1m~0.5m directly below the UAV rotor, the injection half angle is 10°~90°, the injection flow rate is 0.005kg / s~0.02kg / s, the release time is 0~10s, and the orifice width is 0.0005~0.

001. The turbulence model is determined to be SST k-ω, the solution method is set to double precision, and the iteration method is determined to be coupled iteration. The canopy domain is meshed to obtain a solid mesh model; Using LS-DYNA software, the region containing the solid mesh model is transformed into an SPH particle model. Particle parameters are set, including density, type, and size. The contact surface between the particles in the solid domain and the mesh in the fluid domain is set. The total number of particles and the generation rate are set. The particle generation method is set to dynamic particle generation. During the simulation, the number of particles generated is specified to be the same as the number of meshes in the canopy domain. The coupling interface between the outer wall and the fluid mesh model is set to fully analytical. Set the number of simulation steps, the time represented by each step, and the simulation termination conditions; The simulation process is repeated until the simulation termination condition is met, and the simulation results of airflow and droplet deposition inside the canopy are output. The simulation process is as follows: the fluid mesh model results for one simulation step are solved in the Fluent environment, and the SPH particle model results for one simulation step are solved in the LS-DYNA environment; the data exchange between the fluid mesh model results and the solid mesh model results is performed through the coupling interface.

2. The method for simulating airflow and droplet deposition within the canopy according to claim 1, characterized in that, The process of establishing the UAV rotor source model specifically includes: Obtain the structural parameters of the UAV rotor, including: outer diameter, pitch, thickness, and tilt angle; The UAV rotor source model is established based on the structural parameters.

3. The method for simulating airflow and droplet deposition within the canopy according to claim 1, characterized in that, The process of establishing the fruit tree canopy model specifically includes: Obtain fruit tree parameters; the fruit tree parameters include the lowest point of the canopy, the highest point of the canopy, the outer diameter of the canopy, and the canopy density; The fruit tree canopy model is established based on the fruit tree parameters.

4. A simulation system for airflow and droplet deposition within a canopy, characterized in that, The system includes: The model building module is used to construct drone rotor source models and fruit tree canopy models; The rotation domain determination module is used to determine the rotation domain of the UAV rotor based on the UAV rotor source model. The canopy domain determination module is used to determine the canopy domain of the fruit tree based on the fruit tree canopy model. A computational domain determination module is used to determine the computational domain based on the rotational domain and the canopy domain; A fluid geometry model determination module is used to construct a fluid geometry model based on the rotation domain, the canopy domain, and the computational domain; The fluid mesh model determination module is used to perform mesh generation on the fluid geometry model to obtain the fluid mesh model; The first setting module is used to use Fluent software to set the surfaces in the computational domain other than the bottom surface as pressure outlets, set the bottom surface as a wall, set the rotational speed of the UAV rotor according to the payload of the UAV where the UAV rotor source model is located, set the center and direction of the rotation domain, establish a discrete phase model of droplet motion, determine that the nozzle position is 0.1m~0.5m directly below the UAV rotor, the injection half angle is 10°~90°, the injection flow rate is 0.005kg / s~0.02kg / s, the release time is 0~10s, the orifice width is 0.0005~0.001, determine the turbulence model as SST k-ω, set the solution method as double precision, and determine the iteration method as coupled iteration. A solid mesh model determination module is used to perform mesh generation on the canopy domain to obtain a solid mesh model; The second setting module is used to transform the region where the solid mesh model is located into an SPH particle model using LS-DYNA software, set particle parameters including density, type and size, set the contact surface between the particles in the solid domain and the mesh in the fluid domain, set the total number of particles and the generation rate, set the particle generation method to the particle dynamic generation method, specify that the amount of particles generated is the same as the number of meshes in the canopy domain during simulation, and set the coupling interface between the outer wall and the fluid mesh model to fully analytical. The third settings module is used to set the number of simulation steps, the time represented by each step, and the simulation termination conditions. The simulation module is used to repeatedly execute the simulation process until the simulation termination condition is met, and output the simulation results of airflow and droplet deposition inside the canopy. The simulation process is as follows: solve the fluid mesh model results for one simulation step in the Fluent environment, and solve the SPH particle model results for one simulation step in the LS-DYNA environment; and exchange data between the fluid mesh model results and the solid mesh model results through the coupling interface.

5. The simulation system for airflow and droplet deposition within the canopy according to claim 4, characterized in that, The model building module includes a UAV rotor source model building submodule, which specifically includes: A structural parameter acquisition unit is used to acquire the structural parameters of the UAV rotor, including: outer diameter, pitch, thickness, and tilt angle; The UAV rotor source model building unit is used to build the UAV rotor source model based on the structural parameters.

6. The simulation system for airflow and droplet deposition within the canopy according to claim 4, characterized in that, The model building module includes a fruit tree canopy model building sub-module, which specifically includes: The fruit tree parameter acquisition unit is used to acquire fruit tree parameters, including the lowest point of the canopy, the highest point of the canopy, the outer diameter of the canopy, and the canopy density. The fruit tree canopy model establishment unit is used to establish the fruit tree canopy model based on the fruit tree parameters.

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