JP7475103B1 - Simulator development method, information processing system and program - Google Patents

Abstract

The present invention provides a simulator development method, an information processing system, and a program that contribute to reducing the amount of required calculations.
[Solution] A method of developing a simulator according to one embodiment of the present disclosure involves a computer executing the steps of discretizing the space around the fuselage of an aircraft using a computational grid, and applying a numerical computation method for aerodynamic calculations by solving the discretized fluid equations, applying an actuator line model to the blades of the aircraft, and simulating the navigation of the aircraft using the results of applying the numerical computation method and the results of applying the actuator line model to the blades.
[Selected figure] Figure 5

Description

The present invention relates to a simulator development method, an information processing system, and a program.

At the development stage, aircraft must be verified to determine whether they are capable of safe flight. In particular, new types of manned aircraft, such as flying cars, which have been coming into practical use in recent years, require more careful safety verification, because these aircraft involve new technology and the safety of the people on board must be ensured.

There are some navigation conditions that are very difficult to set up in experiments, and there are a huge number of navigation conditions that need to be verified, so there are limitations to conducting real-world verification experiments using actual aircraft or models. Also, because some things cannot be measured in experiments, verification is often carried out using numerical simulations on computers. For example, computational fluid dynamics techniques are used for the simulations.

In particular, flying cars require extremely high navigation safety compared to unmanned aircraft. For example, situations can be expected in which multiple multicopters approach each other (especially in the vertical direction), a multicopter approaches a building, one of the rotors rotates abnormally (e.g. stops), or an unexpected strong wind occurs. By running a simulation, it is possible to discover how the multicopter can regain its attitude and maintain safe navigation in such situations. In addition, by running a simulation, it is possible to verify the placement (or addition) of new rotors that improve safety, and to reflect the verification results in the design.

As a related technique, Non-Patent Document 1 discloses a technique for applying computational fluid dynamics simulation to quadrotor air taxis used in urban transportation systems.

Patricia Ventura Diaz and Seokkwan Yoon, “High-Fidelity Simulations of a Quadrotor Vehicle for Urban Air Mobility”, AIAA SciTech Forum 2022, January 3-7, 2022, San Diego, CA & Virtual

In flying vehicles such as multicopters, the thin and narrow rotor blades (rotating wings; hereafter simply referred to as blades) that make up the rotors rotate at high speeds during flight. In order to perform simulations on such flying vehicles, it is possible to apply a method of discretizing the space using a computational grid and directly calculating the fluid equations numerically. In this case, it is necessary to place very fine computational grids near the blade surfaces, so the total number of computational grid points used in the calculations becomes enormous. As a result, an enormous amount of calculation is required to determine the force acting on the blades (i.e. thrust) and the changes in the surrounding air flow at each time step of the calculation.

Furthermore, one time step in the calculation is an extremely short time interval. Therefore, it becomes extremely difficult for a computer to perform simulation calculations for a period of time (e.g., 1 to 2 minutes) that allows confirmation of the aircraft's navigation behavior, such as translation, rotation, and changes in attitude. For example, even when the above numerical simulation is performed using a supercomputer, there is an issue that the simulation time can only be advanced to the time it takes for the blade to rotate 30 times (e.g., 2 to 3 seconds). The computational fluid dynamics simulation described in Non-Patent Document 1 was performed with the aim of calculating the thrust obtained by the rotation of the blades, and was not intended to calculate the aircraft's navigation.

The present invention was made in consideration of these problems, and provides a simulator development method, information processing system, and program that contribute to reducing the amount of required calculations.

A method for developing a simulator according to one aspect of the present invention includes the steps of:
A step of discretizing a space around a fuselage of an aircraft using a computational grid, and applying a numerical computation method for aerodynamic calculation by solving the discretized fluid equations;
applying an actuator line model to a blade of the air vehicle;
simulating flight of the aircraft using a result of application of the numerical calculation method and a result of application of the actuator line model to the blades;
The above is executed by a computer.

An information processing system according to one aspect of the present invention includes:
a first application unit that discretizes a space around a fuselage of the aircraft using a computational grid and applies a numerical calculation method for aerodynamic calculation by solving the discretized fluid equations;
a second application unit that applies an actuator line model to a blade of the aircraft;
The aircraft is equipped with a simulator unit that simulates the flight of the aircraft by using a result of application of the numerical calculation method and a result of application of the actuator line model to the blades.

A program according to one aspect of the present invention includes:
A step of discretizing a space around a fuselage of an aircraft using a computational grid, and applying a numerical computation method for aerodynamic calculation by solving the discretized fluid equations;
applying an actuator line model to a blade of the air vehicle;
simulating flight of the aircraft using a result of application of the numerical calculation method and a result of application of the actuator line model to the blades;
to be executed by the computer.

The present invention provides a simulator development method, information processing system, and program that contribute to reducing the amount of calculation required.

FIG. 1 is a block diagram illustrating an example of an information processing system. FIG. 2 shows an example of a multicopter. FIG. 3 shows an example of a blade when the actuator line model is applied. FIG. 4 shows an example of the forces that marker particles placed on a blade experience from the surrounding air. FIG. 5 is a flowchart showing an example of a typical process of the information processing system. FIG. 6 shows numerical calculation data indicating the magnitude of the flow velocity. FIG. 7 is a graph comparing experimental results and calculation results for thrust force. FIG. 8 shows the results of a calculation using an actuator line model, which shows the state in which the reaction force of the blade thrust is applied to the surrounding air as downwash. FIG. 9 is a block diagram illustrating an example of a hardware configuration of an information processing device according to an embodiment.

Below, an embodiment of the present invention will be described with reference to the drawings. Note that the following description and drawings in the embodiment of the invention have been omitted or simplified as appropriate for clarity of explanation. In addition, in this embodiment, unless otherwise specified, when "at least one of the multiple items" is defined for multiple items, the definition may mean any one item, or any multiple items including all items.

Not all of the features or steps shown in any one of the figures are necessarily required to describe an exemplary embodiment, and any part of the features or steps may be omitted. In addition, the order of steps described in the specification and drawings may be changed as appropriate.

[Related Technology]
First, we will explain the related technology of a free navigation simulator for a multicopter such as a flying car equipped with multiple rotors. A multicopter can navigate freely by obtaining thrust from the surrounding air as the blades rotate under gravity. A free navigation simulator is a program that predicts how a multicopter will navigate in the air by simulating the information such as the shape and weight of the multicopter that is given in advance, and giving only the time-varying blade rotation speed as a variable.

In a free flight simulator, calculations are made of the forces that the aircraft, including the blades, receives from the surrounding air, as well as the effect that the movement of the object (i.e. the aircraft) has on the surrounding air. In calculating these forces, the forces generated by the rotation of the blades are taken into account for the blades, and the forces that the entire aircraft receives as the aircraft flies are taken into account.

In order for a computer to accurately calculate the forces that an aircraft receives from the surrounding air, it needs to solve the fluid equations with viscous terms (Navier-Stokes equations). There are several methods for a computer to calculate the forces that a blade rotating at high speed receives, such as using a high-resolution computational grid that can resolve the boundary layer on the object's surface, using a wall function model, or using DES (Detached Eddy Simulation) for calculations in the vicinity including the blade. However, no matter which method is used, the amount of calculations that the computer must perform is enormous. Even in the method using wall functions, which is thought to have the lightest computational load among the above methods, the computer must always allocate a high-resolution computational grid to the vicinity of the blade during calculations. This results in a very large computational load.

In addition, to reduce the amount of calculation required, a method can be considered in which the computer performs calculations using the Euler equations, which are fluid equations without viscous terms. In this case, since no boundary layer is generated for the airflow, the only constraint on the resolution of the computational grid is the shape of the object. However, when using this method, the computer can only calculate the rotation of the blades and the vertical lift, and cannot calculate any airflow such as downwash generated by the blades. For this reason, this method cannot be applied to free navigation simulators.

One example of the objectives of the present invention is to develop a simulator that can give the aircraft to be simulated the only variable being the blade rotation conditions, and allow the aircraft to fly freely in the virtual space of a computer. The introduction (adoption) of an actuator line model for this purpose is a novel feature of the present invention.

In addition, the "aircraft" in this disclosure refers to any flying object having a blade portion and a fuselage portion, and includes, for example, manned or unmanned drones, flying cars, airplanes, spaceships, etc. In the following embodiments, the "aircraft" will be described using a multicopter as an example, but it may also include rotorcraft other than multicopters.

First embodiment
[Configuration Description]
1 is a block diagram showing an example of an information processing system 10. The information processing system 10 includes an input unit 11, a setting unit 12, a blade calculation unit 13, a time integral calculation unit 14, a change calculation unit 15, a display unit 16, and a storage unit 17. Each unit of the information processing system 10 will be described below.

The input unit 11 is a component unit that accepts input information from a user. The input unit 11 may be configured with an input interface such as a touch panel, a keyboard, or a mouse. By using the input unit 11, a user can input input information of any content to the information processing system 10. For example, the user may use the input unit 11 to input information about the shape and mass of each part of the multicopter to be simulated, and the rotation conditions of the blades of the multicopter (for example, the rotation speed). The user may also use the input unit 11 to input information about the relative position, size, and shape of objects (hereinafter also referred to as peripheral objects) present around the multicopter, and parameters used in the calculation, which will be described later. Peripheral objects are, for example, the ground, buildings, etc.

The setting unit 12 sets a predetermined spatial range that includes the entire multicopter to be simulated as the calculation domain in the simulation. The spatial range is set, for example, based on the size and shape of the multicopter input by the input unit 11. The setting unit 12 also sets the interval of the time step that allows stable time integration.

If necessary in the simulation, the setting unit 12 also places peripheral objects in the calculation domain (a specified range of space). The placement of the peripheral objects is set based on, for example, information about the relative positions, sizes, and shapes input by the input unit 11.

The setting unit 12 also sets boundary conditions (e.g., outflow boundary conditions) for the calculation domain. Furthermore, the setting unit 12 divides the multicopter into the blades and the fuselage, which is all parts of the entire multicopter body except for the blades. For example, the rotor support parts of the body are also included in the fuselage. The setting unit 12 may perform the division based on the information about the multicopter input from the input unit 11.

Here, the setting unit 12 may divide the calculation domain into a region around the blade (hereinafter also referred to as region 1) and a calculation domain other than region 1 (hereinafter also referred to as region 2). Region 1 is, for example, a region that exists within a predetermined length from the surface of the blade of the multicopter. Region 2 may be divided into a region around the fuselage of the multicopter and the other calculation domain. However, the setting unit 12 does not have to divide the calculation domain into region 1 and region 2.

Figure 2 shows an example of a multicopter. Multicopter M1 has rotors R1 to R4 and a fuselage D1. When dividing the calculation domain for multicopter M1, setting unit 12 may divide the calculation domain into domain 1, which is the domain around rotors R1 to R4, and domain 2, which is the domain including the periphery of fuselage D1.

The setting unit 12 also sets the shape of the computational grid that divides the computational domain. The shape of the computational grid can be any shape, such as a hexahedron such as a rectangular parallelepiped, a rectangular prism, or a tetrahedron. The shape of the computational grid may be input by the user using the input unit 11, may be stored in the storage unit 17, or may be set by the setting unit 12 based on information related to the computation. The setting unit 12 sets a grid size that allows efficient computation with sufficient accuracy. The setting unit 12 may use a fine (i.e., small) grid in the vicinity of the fuselage (for example, within a predetermined distance from the fuselage) and a coarse (i.e., large) grid outside the vicinity of the fuselage. The setting unit 12 may also change the grid size depending on the strength of vortices in the generated flow.

Returning to FIG. 1, the blade calculation unit 13 will now be described. The blade calculation unit 13 executes the following processes to calculate the force the blade receives from the surrounding air as the blade rotates, and the momentum the blade imparts to the surrounding air, for the region around the blade. When the setting unit 12 divides the calculation region into region 1 and region 2, the blade calculation unit 13 executes the above calculations for the set region 1. Below, the process of applying the actuator line model executed by the blade calculation unit 13 will be described in detail.

(A) First, the blade calculation unit 13 removes the blades from the 3D (dimensions) shape model of the multicopter.

(B) Next, the blade calculation unit 13 applies blade element data that matches the shape of the blade to the deleted blade area. The blade element data is 2D data that shows the cross-sectional shape of the blade and data on its aerodynamic characteristics. The blade calculation unit 13 may use blade element data stored in the memory unit 17, for example, or may obtain the blade element data to be used from outside the information processing system 10 (for example, provided via the Internet).

(C) Then, the blade calculation unit 13 specifically sets the parameters of the actuator line model to be applied.

（１）において、ｄ_ｉは、ｉ番目のマーカー粒子と、（x,y,z）の位置にある計算格子点との距離である。εは、ガウス分布の標準偏差であり、マーカー粒子の影響半径のパラメータである。図３には、マーカー粒子を中心とする半径εの円が示されている。なお、図３は、簡単のためブレード及び計算格子を２Ｄで表現しているが、実際にはこれらは３Ｄで表される。 Fig. 3 shows an example of a blade when the actuator line model is applied. In Fig. 3, each blade B1 to B3 is represented by a plurality of particles (hereinafter, also referred to as marker particles) that make up the blade. The marker particles are shown as points in Fig. 3, and each blade is made up of an array of marker particles. Furthermore, each blade B1 to B3 exists within a computational grid. In this case, the Gaussian filter η that determines the range of influence that the marker particles have on the surrounding computational grids is expressed as follows:

In (1), d _i is the distance between the i-th marker particle and the computational grid point at the position (x, y, z). ε is the standard deviation of the Gaussian distribution and is a parameter of the radius of influence of the marker particle. In FIG. 3, a circle of radius ε is shown centered on the marker particle. Note that for simplicity, FIG. 3 shows the blade and computational grid in 2D, but in reality, they are expressed in 3D.

As described below, when the time integral calculation unit 14 performs calculations, the object boundary conditions of the multicopter are set. However, since the actuator line model is set for the area around the blades as described above, the blade calculation unit 13 does not need to set object boundary conditions.

ここで、ｕ_ｚは周囲の空気の流れのｚ軸成分であり、ｕ_θは周囲の空気の流れのθ軸成分である。また、ｒはマーカー粒子ｉのブレードの回転中心からの距離であり、Ωはブレードの角速度である。ｕ_ｒｅｌを用いると、マーカー粒子の位置でブレードが周囲の空気から受ける力Ｆ_２Ｄは、以下のように表される。

ここで、Ｃ_ａはブレードの翼弦長であり、ｅ_ｌ、ｅ_ｄはそれぞれ揚力、抗力が作用する方向の単位ベクトルである。Ｃ_ｌ、Ｃ_ｄはそれぞれ揚力係数、抗力係数であり、迎角αに対するデータセットとして事前に翼素データとして用意される。また、Δｒは、マーカー粒子同士の間隔を示すパラメータである。 Figure 4 shows an example of the forces that a marker particle arranged on a blade receives from the surrounding air based on the blade element momentum theory. The lift and drag forces acting on the marker particle i of the blade B2 are expressed as F _l and F _d , respectively. θ and z respectively indicate the coordinate axes of the rotation direction and the thrust direction. γ is the blade attachment angle (local pitch angle) with respect to the θ axis, which is the rotation direction of the blade, and α is the angle of attack. At this time, the relative speed u _rel of the blade is expressed as follows.

Here, u _z is the z-axis component of the surrounding air flow, and u _θ is the θ-axis component of the surrounding air flow. In addition, r is the distance of the marker particle i from the center of rotation of the blade, and Ω is the angular velocity of the blade. Using u _rel , the force F _2D that the blade receives from the surrounding air at the position of the marker particle is expressed as follows:

Here, C _a is the chord length of the blade, e _l and e _d are unit vectors in the directions in which lift and drag act, respectively. C _l and C _d are lift and drag coefficients, respectively, which are prepared in advance as blade element data as a data set for the angle of attack α. Also, Δr is a parameter indicating the distance between marker particles.

ここで、Ｆ_２Ｄ,ｉはＦ_２Ｄのマーカー粒子ｉの成分であり、Ｎ_ｐはマーカー粒子の総数である。 Furthermore, the force that the marker particle i exerts on the computational grid point at the position (x, y, z) (i.e., the momentum imparted to the surrounding air by the rotation of the blade) is calculated as follows:

where F _2D,i is the component of marker particle i in F _2D , and N _p is the total number of marker particles.

The blade calculation unit 13 sets the parameters ε and Δr to enable the above calculations (1) to (4). The parameters ε and Δr may be set by the user using the input unit 11, or the blade calculation unit 13 may use settings stored in the storage unit 17. The numerical values other than the parameters ε and Δr used in the calculations (1) to (4) are determined based on the multicopter information, etc., and data obtained by simulation.

(D) After that, the blade calculation unit 13 performs coordinate transformation for at least one of translation and rotation of the rotation axis together with the aircraft, depending on the attitude of the multicopter aircraft, for the actuator line model to be applied. For example, the blade calculation unit 13 may realize the coordinate transformation for rotation of the rotation axis by using a quaternion.

(E) Next, the blade calculation unit 13 determines the blades to which the actuator line model should be applied when the 3D model of the multicopter is placed in the calculation domain. The blade calculation unit 13 places a calculation grid in the domain around the blade, with a grid size that is approximately 1/100th the diameter of the blade. The grid size is arbitrary, but the size of the grid affects the calculation accuracy. The shape of the calculation grid is set by the setting unit 12.

(F) Then, the blade calculation unit 13 calculates the forces (thrust and torque) acting on the blade calculated by equation (3) by applying the actuator line model, and imparts the calculated forces to the part of the aircraft that supports the rotor blade. Meanwhile, the blade calculation unit 13 imparts the momentum of the reaction of the forces to the air around the blade as shown in equation (4).

(G) The blade calculation unit 13 performs the above calculations (1) to (4) for one blade in the region 1 determined in (E) using the results of the processing performed in (F). The computational grid used in the calculations is set as in (E). As a result, the blade calculation unit 13 can calculate the force that the blade receives from the surrounding air and the momentum that it imparts to the surrounding air as the blade rotates under the influence of the aircraft moving and rotating.

(H) The blade calculation unit 13 performs the calculation (G) for each blade in region 1 to calculate the force that the blade receives from the surrounding air and the momentum that the blade imparts to the surrounding air for all blades.

Returning to FIG. 1, the time integral calculation unit 14 will be described. The time integral calculation unit 14 places a computational grid with a grid size of about 1/300 of the total length of the fuselage (i.e., the total length of the aircraft) in the immediate vicinity of the aircraft surface. When the setting unit 12 divides the computational domain into domain 1 and domain 2, the time integral calculation unit 14 may place a computational grid with a different grid size from domain 1 in the set domain 2 (i.e., the domain around the fuselage). The grid size is arbitrary, but in order to ensure a certain degree of computational accuracy, it is necessary to place a fine grid of a predetermined size or less. However, as the grid size, a larger grid may be used as the distance from the aircraft increases. The shape of the computational grid is set by the setting unit 12. Then, the time integral calculation unit 14 sets the object boundary conditions of the moving object (i.e., the multicopter) in the domain in which the computational grid is placed.

The time integral calculation unit 14 performs aerodynamic calculations by applying a numerical calculation method to solve the fluid equations that have been discretized using a computational grid while taking into account the set object boundary conditions. In this way, the time integral calculation unit 14 calculates the force that the fuselage receives from the surrounding air when all parts of the entire aircraft except for the blades (i.e. the fuselage) move. In addition, the effect of the boundary conditions that reflect the moving objects on the air side is also calculated. The "numerical calculation method for aerodynamic calculations" is a known calculation method other than the actuator line model, and includes, for example, the finite volume method, the finite element method, the lattice Boltzmann method, the particle method, and the like. The details of this calculation method are well known, so a description will be omitted.

If necessary, the time integral calculation unit 14 may use a moving computational grid method such as a sliding grid or an overlap grid to reduce the amount of calculation.

Through this process, the blade calculation unit 13 and the time integral calculation unit 14 can calculate the force that the blades and the fuselage (i.e. the entire aircraft) receive from the surrounding air at a certain time. The blade calculation unit 13 and the time integral calculation unit 14 repeatedly perform this calculation for a certain period of time while the blades rotate, thereby calculating the airflow corresponding to the rotation of the blades and the surrounding airflow generated by the movement of the fuselage. This makes it possible to confirm the navigation behavior of the multicopter. Note that when calculating the airflow corresponding to the rotation of the blades, the blade calculation unit 13 may use a condition in which the rotation speed input from the input unit 11 changes over time.

The change calculation unit 15 simulates how the multicopter navigates in the air based on the force that the blades receive from the surrounding air, calculated by the blade calculation unit 13, and the force that the fuselage receives from the surrounding air, calculated by the time integration calculation unit 14. In detail, the change calculation unit 15 finely divides the surface of the fuselage and integrates the forces acting on the fuselage surface calculated by the time integration calculation unit 14 to obtain the translation force and rotation torque that the entire aircraft receives. The change calculation unit 15 calculates the time changes in the translation, rotation, and attitude of the aircraft by integrating the equation of motion using information such as the size, shape, and mass of each part of the multicopter and information on the moment of inertia around the center of gravity. In other words, the change calculation unit 15 simulates the navigation of the multicopter by using the results of applying a numerical calculation method for aerodynamic calculation to the fuselage and the results of applying an actuator line model to the blades.

The display unit 16 displays the simulation results of the change calculation unit 15. If necessary, the display unit 16 may further display at least one of the calculation results of the blade calculation unit 13 or the calculation results of the time integral calculation unit 14. These calculation results include the air flow around the blades and near the surface of the aircraft, and the pressure that various points on the surface of the aircraft receive from the air. The display unit 16 is, for example, a display or a touch panel. By visually checking the display unit 16, the user can grasp the results of the free navigation simulation of the multicopter over a certain period of time.

The memory unit 17 stores the time changes in all air flows within the calculation domain obtained by the calculations performed by the time integral calculation unit 14, the time changes in pressure distribution on the aircraft surface, and the time changes in forces (thrust and torque) acting on the blades obtained by the calculations performed by the blade calculation unit 13. The frequency of storage is specified by the setting unit 12. The memory unit 17 also stores information necessary for processing, such as programs for causing the setting unit 12 to the display unit 16 to execute processing, the geometry of the calculation grid, blade element data, and settings for the parameters ε and Δr.

[Flow description]
Fig. 5 is a flowchart showing an example of a representative process of the information processing system 10. The process of the information processing system 10 is explained using the flowchart of Fig. 5. Note that the details of each process are as described above, and therefore will not be explained again.

The input unit 11 inputs information required for calculation, such as information on the multicopter to be simulated, blade rotation conditions, and information on surrounding objects, based on user operations (step S11). The setting unit 12 sets calculation conditions, such as the calculation domain, the arrangement of surrounding objects, boundary conditions, and the shape of the calculation grid (step S12). The setting unit 12 may further set domains 1 and 2.

Then, the blade calculation unit 13 applies an actuator line model to calculate the force that the blade receives from the surrounding air (step S13). Details of this are as shown in (A) to (H). Furthermore, the time integral calculation unit 14 applies a numerical calculation method for aerodynamic calculation to calculate the force that the aircraft receives from the surrounding air and the effect on the surrounding air (step S14). Details of this are also as described above. The blade calculation unit 13 and the time integral calculation unit 14 repeatedly execute the calculations of steps S13 and S14 in a loop for a certain period of time that the blade rotates. Here, either step S13 or step S14 may be executed first, or both may be executed in parallel.

The change calculation unit 15 simulates the navigation of the multicopter based on the calculation results of the blade calculation unit 13 and the calculation results of the time integral calculation unit 14 (step S15). The display unit 16 displays the calculation results of the change calculation unit 15 (step S16).

[Effects]
As described above, the information processing system 10 applies an actuator line model to the calculation of the blades of the aircraft, while applying a numerical calculation method for aerodynamic calculation to the calculation of other parts of the aircraft. This makes it possible to dramatically reduce the amount of calculation required for the free flight simulator.

In the related art so far, a numerical calculation method for aerodynamic calculations, which discretizes and solves the Navier-Stokes equations having a viscosity term, has been applied to the calculation of the blade. At this time, in order to obtain a calculation result with sufficient accuracy, a calculation grid having a grid size of 1/1000 of the diameter of the blade or less is placed near the blade. Here, when the calculation grid placed near the blade has a size of 1/1000 of the diameter of the blade (situation A), the number of calculation grids to be considered as calculation targets is 10 ³ (1000) times larger than when the calculation grid placed near the blade has a size of 1/100 of the diameter of the blade (situation B). Furthermore, in situation A, the interval of the calculation time step must also be 1/10 compared to situation B. Therefore, for example, the amount of calculation for region 1 is 10 ⁴ (10,000) times larger in situation A than in situation B. In addition, the faster the rotation speed of the blade, the smaller the calculation grid must be in order to ensure the accuracy of the calculation. Therefore, the amount of calculation for the blade has become enormous.

On the other hand, in the present invention, the blade calculation unit 13 applies an actuator line model, so that the computational grid placed near the blade can be made larger than 1/1000 of the blade diameter. Therefore, the computational load per step of the blade can be reduced compared to the related art. For example, situation A in the related art can be changed to situation B in the present invention. As a result, the amount of calculation for region 1 can be reduced to 1/10,000 or less, and it is also possible to reduce the amount of calculation for region 1 to, for example, 1/10 or less of the amount of calculation for the entire free navigation simulator.

The information processing system 10 according to the present invention can therefore adequately calculate the time it takes for the blades to rotate 1,000 times, making it possible to simulate the free flight of the entire aircraft. For example, the information processing system 10 can also perform a free flight simulation for the takeoff and landing process of an aircraft.

Furthermore, the method of the information processing system 10 described above can also ensure the accuracy of the calculations. Below, the accuracy of the calculations of the information processing system 10 will be explained with reference to the data of the actual simulator results.

Figure 6 shows numerical calculation data showing the magnitude of the flow velocity at a certain time caused by the influence of the surrounding air when using a blade with the same shape and rotation speed as the blade used in the reference paper (Knut Erik Teigen Giljarhus, Alessandro Porcarelli and Jorgen Apeland, “Investigation of Rotor Efficiency with Varying Rotor Pitch Angle for a Coaxial Drone”, Drones 2022, April 4, 2022, MDPI). The numerical calculation data includes four types of calculation results for blade rotation speeds of 1600 rpm, 1900 rpm, 2200 rpm, and 2500 rpm. As can be seen from Figure 6, the method of the present invention using the actuator line model can obtain calculation results (lower part of Figure 6) that are very consistent with the results of aerodynamic calculations that discretize and solve the Navier-Stokes equations using a very fine grid (upper part of Figure 6).

Figure 7 is a graph showing the results of calculations performed by the information processing system 10 using the same blade shape and rotation speed as in the reference paper (i.e., the calculation results using the actuator line model according to the present invention). Figure 7 shows five types of calculation results with blade rotation speeds of 1600 rpm, 1900 rpm, 2200 rpm, 2500 rpm, and 2600 rpm. As shown in Figure 7, it is possible to obtain calculation results in which the experimental data in the reference paper and the results of aerodynamic calculations that discretize and solve the Navier-Stokes equations using a very fine grid match very well in terms of thrust.

Figure 8 shows the results of a calculation that shows how, when a flying car takes off, the reaction force of the blades, calculated using an actuator line model, acts on the surrounding air as downwash, which then hits the ground and spreads out sideways. Figure 8 shows the state of the vortexes that are generated, and as shown by the isosurface of the second invariant of the velocity gradient tensor of the airflow, the information processing system 10 is able to calculate that very fine vortices are released from the blades.

The user may input at least one of the following information when applying the actuator line model to the blade: the spacing of the marker particles, or the parameters of the radius of influence of the Gaussian filter. The blade calculation unit 13 can use the input information when applying the actuator line model. Therefore, the user can freely adjust the degree of reduction in the amount of calculation and the accuracy of the actuator line model by changing the input parameters.

The blade calculation unit 13 may also set the size of the computational grid applied to the area around the blade to 1/1000 of the blade diameter or more. For example, the blade calculation unit 13 may set the size of the computational grid to 1/100 of the blade diameter. By setting this value, the blade calculation unit 13 can achieve the effect of reducing the amount of calculation while maintaining the accuracy of the calculation using the actuator line model. However, the blade calculation unit 13 may set the length of the computational grid to a different size as necessary. For example, the blade calculation unit 13 may set the size of the computational grid to any size, such as 1/50 or 1/200 of the blade diameter.

The information processing system 10 of the present invention may be configured as a single computer device, or may be configured as a distributed system having multiple computer devices. In a distributed system, the processing executed by the information processing system 10 can be shared and executed by multiple computer devices. In other words, the components from the input unit 11 to the storage unit 17 may be distributed and installed on two or more computer devices.

In the above embodiment, the information processing system according to the present invention has been described as being configured as hardware, but the information processing system according to the present invention is not limited to this. The present invention can also be realized by having a processor in a computer execute a computer program to process each device that configures the information processing system 10 described in the above embodiment.

FIG. 9 is a block diagram showing an example of the hardware configuration of an information processing system (in other words, a computer) according to an embodiment. Referring to FIG. 9, an information processing system 90 includes a signal processing circuit 91, a processor 92, a memory 93, a storage 94, and an interface 95.

The signal processing circuit 91 is a variety of circuits for processing signals according to the control of the processor 92.

The processor 92 is connected to the memory 93, and performs the processing of the system described in the above embodiment by reading a computer program from the memory 93 and executing it while communicating with the memory 93. As an example of the processor 92, one of a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), an FPGA (Field-Programmable Gate Array), a DSP (Demand-Side Platform), and an ASIC (Application Specific Integrated Circuit) may be used, or multiple of them may be used in parallel.

The memory 93 is a main storage device that is composed of, for example, a volatile memory. The number of memories 93 is not limited to one, and multiple memories may be provided. The volatile memory may be, for example, a RAM (Random Access Memory) such as a DRAM (Dynamic Random Access Memory).

The memory 93 is used to store one or more instructions and data. Here, the one or more instructions are stored in the memory 93 as a program. The processor 92 can perform the processing described in the above embodiment by reading and executing these programs and data from the memory 93.

Note that the memory 93 may include memory built into the processor 92 in addition to memory provided outside the processor 92. The memory 93 may also include storage located away from the processors constituting the processor 92. In this case, the processor 92 can access the memory 93 via an I/O (Input/Output) interface.

The storage 94 is an auxiliary storage device composed of, for example, a non-volatile memory. The number of storages 94 is not limited to one, and multiple storages 94 may be provided. The non-volatile memory may be, for example, a hard disk drive (HDD), a programmable random only memory (PROM), a read only memory (ROM) such as an erasable programmable read only memory (EPROM), a flash memory, or a solid state drive (SSD). The storage 94 stores a program to be supplied to the memory 93. The storage 94 may also function as the memory unit 17 in the first embodiment, and may store the calculation results of the time integral calculation unit 14 and the change calculation unit 15 shown above, and information required for processing.

The interface 95 includes a communication circuit for transmitting and receiving signals or data via a network. The interface 95 may be, for example, a network interface card (NIC). The processor 92 may transmit data stored in the memory 93 and storage 94 to another information processing system via the interface 95, or may store data transmitted from another information processing system in the memory 93 and storage 94 via the interface 95.

As described above, one or more processors in each system in the above-described embodiments execute one or more programs including a set of instructions for causing a computer to execute the algorithm described in the drawings. By executing the programs, the information processing described in each embodiment can be realized.

The program includes instructions or software code that, when loaded into a computer, causes the computer to perform one or more functions described in the embodiments. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or tangible storage medium may include random-access memory (RAM), read-only memory (ROM), hard disk drive (HDD), flash memory, solid-state drive (SSD) or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disk (DVD), Blu-ray (registered trademark) disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a temporary computer-readable medium or communication medium. By way of example and not limitation, the temporary computer-readable medium or communication medium may include electrical, optical, acoustic, or other forms of propagating signals. The temporary computer-readable medium or communication medium may provide the program to the computer via a wired communication path, such as electric wire and optical fiber, or a wireless communication path.

Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-mentioned embodiments. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

REFERENCE SIGNS LIST 10 Information processing system 11 Input unit 12 Setting unit 13 Blade calculation unit 14 Time integral calculation unit 15 Change calculation unit 16 Display unit 17 Storage unit 90 Information processing system 91 Signal processing circuit 92 Processor 93 Memory 94 Storage 95 Interface

Claims (9)

A step of discretizing a space around a fuselage of an aircraft using a computational grid, and applying a numerical computation method for aerodynamic calculation by solving the discretized fluid equations;
applying an actuator line model to a blade of the air vehicle;
simulating flight of the aircraft using a result of application of the numerical calculation method and a result of application of the actuator line model to the blades;
A method for developing a simulator that runs on a computer. The computer receives input of at least one of information on the interval between marker particles constituting the blade or a parameter of the influence radius of a Gaussian filter, and uses the received information in applying the actuator line model.
A method for developing a simulator according to claim 1. The computer uses a computational grid having a size equal to or greater than 1/1000 of the diameter of the blade in a computational domain around the blade to apply the actuator line model.
A method for developing a simulator according to claim 1 or 2. a first application unit that discretizes a space around a fuselage of the aircraft using a computational grid and applies a numerical calculation method for aerodynamic calculation by solving the discretized fluid equations;
a second application unit that applies an actuator line model to a blade of the aircraft;
a simulator unit that simulates the flight of the aircraft by using a result of application of the numerical calculation method and a result of application of the actuator line model to the blades. an input unit that receives input of at least one of information on an interval between marker particles constituting the blade or a parameter of an influence radius of a Gaussian filter;
The simulator unit uses the received information in applying the actuator line model.
5. The information processing system according to claim 4. the simulator unit uses a computational grid having a size equal to or greater than 1/1000 of the diameter of the blade in a computational domain around the blade to apply the actuator line model;
6. The information processing system according to claim 4 or 5. A step of discretizing a space around a fuselage of an aircraft using a computational grid, and applying a numerical computation method for aerodynamic calculation by solving the discretized fluid equations;
applying an actuator line model to a blade of the air vehicle;
simulating flight of the aircraft using a result of application of the numerical calculation method and a result of application of the actuator line model to the blades;
A program that causes a computer to execute the following. receiving, into the computer, at least any one of information regarding the interval between marker particles constituting the blade or a parameter of the radius of influence of a Gaussian filter, and causing the computer to use the received information in applying the actuator line model;
The program according to claim 7. causing the computer to use a computational grid having a size equal to or greater than 1/1000th of the diameter of the blade in a computational domain around the blade for applying the actuator line model;
The program according to claim 7 or 8.

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