Development method for simulator, information processing system and program

Abstract

To provide a development method for simulator, an information processing system and a program for contributing to reduction in necessary computational complexity.SOLUTION: A development method for simulator causes a computer to perform the steps of: discretizing a space in a circumference of the trunk of a flying body by the use of a calculation grid and solving a discretized fluid equation to apply a numeric calculation method for aerodynamic calculation; applying an actuator line model to the blades of the flying body; and using the application result of the numerical calculation method and the application result of the actuator line model to the blades to simulate a flight of the flying body.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a simulator development method, an information processing system, and a program. [Background technology]

[0002] During the development stage, aircraft must be verified to ensure safe flight. In particular, new types of manned aircraft, such as flying cars, which have recently begun to be put into practical use, require more careful safety verification, as these aircraft involve new technology and the safety of the people on board must be ensured.

[0003] There are limitations to conducting real-world verification experiments using actual aircraft or models, as some navigation conditions are extremely difficult to set up in experiments and the number of navigation conditions that need to be verified is enormous. Also, since there are some things that cannot be measured in experiments, verification is often carried out using numerical simulations on computers. Simulations use, for example, techniques from computational fluid dynamics.

[0004] Flying cars, in particular, require significantly higher flight safety than unmanned aircraft. For example, situations can be anticipated, such as when multiple multicopters approach each other (especially in the vertical direction), when a multicopter approaches a building, when one of the rotors rotates abnormally (e.g., stops), or when unexpected strong winds occur. Running simulations makes it possible to discover how a multicopter can regain its balance and maintain safe flight in such situations. Running simulations also makes it possible to verify new rotor arrangements (or additions) that improve safety, and to reflect the verification results in the design.

[0005] As a related technique, Non-Patent Document 1 discloses a technique for applying computational fluid dynamics simulation to a quadrotor air taxi used in an urban transportation system. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] 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 Summary of the Invention [Problem to be solved by the invention]

[0007] In aircraft such as multicopters, the thin, slender rotor blades (rotating wings; hereafter simply referred to as blades) that make up the rotors rotate at high speeds during flight. For simulations of such aircraft, it is conceivable to use computational grids to discretize the space and apply methods to directly calculate the fluid equations numerically. In this case, it is necessary to place extremely fine computational grids near the blade surfaces, resulting in a huge number of total computational grid points used in the calculations. Therefore, a huge amount of calculation is required to determine the force acting on the blades (i.e., thrust) and the changes in the surrounding airflow at each time step of the calculation.

[0008] Furthermore, one time step in the calculation is an extremely short time interval. Therefore, it is extremely difficult for a computer to perform simulation calculations for a period long enough to confirm the navigation behavior of the aircraft, such as changes in translation, rotation, and attitude (e.g., 1 to 2 minutes). For example, even when the above numerical simulation is performed using a supercomputer, there is a problem in that the simulation time can only be advanced to the time it takes for the blades 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 navigation of the aircraft.

[0009] The present invention has been made in view of the above problems, and provides a simulator development method, an information processing system, and a program that contribute to reducing the amount of calculation required. [Means for solving the problem]

[0010] 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 calculation 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 by using a result of applying the numerical calculation method and a result of applying the actuator line model to the blades; The above is executed by a computer.

[0011] 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 the blade of the aircraft; The aircraft includes a simulator unit that simulates the flight of the aircraft by using the result of application of the numerical calculation method and the result of application of the actuator line model to the blades.

[0012] 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 calculation 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 by using a result of applying the numerical calculation method and a result of applying the actuator line model to the blades; to be executed by the computer. [Effects of the Invention]

[0013] According to the present invention, it is possible to provide a simulator development method, an information processing system, and a program that contribute to reducing the amount of calculation required. [Brief explanation of the drawings]

[0014] [Figure 1] FIG. 1 is a block diagram illustrating an example of an information processing system. [Figure 2] Figure 2 shows an example of a multicopter. [Figure 3] FIG. 3 shows an example of a blade when the actuator line model is applied. [Figure 4] FIG. 4 shows an example of the forces that marker particles placed on a blade are subjected to from the surrounding air. [Figure 5] FIG. 5 is a flowchart showing an example of a typical process of the information processing system. [Figure 6] Figure 6 shows the data from the numerical calculations that show the magnitude of the flow velocity. [Figure 7] FIG. 7 is a graph comparing experimental results and calculation results for thrust. [Figure 8] Figure 8 shows the results of calculations using the actuator line model, showing how the reaction force of the blade thrust is applied to the surrounding air as downwash. [Figure 9] FIG. 9 is a block diagram illustrating an example of a hardware configuration of an information processing device according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0015] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the following description and drawings in the embodiments of the invention have been omitted or simplified as appropriate for clarity of explanation. Furthermore, in this embodiment, unless otherwise specified, when multiple items are defined as "at least one of multiple items," the definition may mean any one item, or any multiple items including all items.

[0016] Not all of the features or steps shown in any one of the drawings are necessarily required to describe the exemplary embodiments, 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.

[0017] [Related Technology] First, we will explain the technology related to free-flight simulators for multicopters, such as flying cars, that are equipped with multiple rotors. Multicopters are able to navigate freely by obtaining thrust from the surrounding air as their blades rotate under gravity. A free-flight simulator is a program that uses information such as the shape and weight of the multicopters given in advance to simulate how the multicopters will navigate in the air, using only the time-varying blade rotation speed as a variable.

[0018] In a free flight simulator, the forces acting on the aircraft, including the blades, from the surrounding air and the effect of the object (i.e., the aircraft) on the surrounding air due to its movement are calculated. In calculating these forces, the forces acting on the blades due to their rotation are taken into account, while the forces acting on the entire aircraft due to its flight are taken into account.

[0019] In order for a computer to accurately calculate the forces acting on an aircraft from the surrounding air, it must solve the fluid equations (Navier-Stokes equations) with a viscous term. There are several methods for a computer to calculate the forces acting on a blade rotating at high speed, such as using a high-resolution computational grid that can resolve the boundary layer on the object surface, using a wall function model, or using DES (Detached Eddy Simulation) for calculations in the vicinity of the blade. However, all of these methods require a huge amount of calculations. Even in the wall function method, which is considered 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.

[0020] Another method that can be considered to reduce the amount of calculation required is to use the Euler equations, which are fluid equations without viscosity terms. In this case, since no boundary layer related to the airflow is generated, the only constraint on the resolution of the computational grid is the object shape. 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. Therefore, this method cannot be applied to free-floating simulators.

[0021] One example of the objective of this invention is to develop a simulator that can give the aircraft to be simulated only the blade rotation conditions as variables and allow the aircraft to freely navigate in a virtual computer space. The introduction (adoption) of an actuator line model for this purpose is a novel feature of this invention.

[0022] Note that the "aircraft" in this disclosure refers to any flying object having a blade portion and a fuselage portion, and includes, for example, a manned or unmanned drone, a flying car, an airplane, a spaceship, etc. In the following embodiments, a multicopter will be used as an example of the "aircraft," but the "aircraft" may also include rotorcraft other than a multicopters.

[0023] Embodiment 1 [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.

[0024] 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. The user can use the input unit 11 to input any input information 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 (e.g., rotation speed) of the multicopter's blades. 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, as well as parameters used in calculations, which will be described later. Peripheral objects include, for example, the ground and buildings.

[0025] The setting unit 12 sets a predetermined spatial range including the entire multicopter to be simulated as a calculation domain for the simulation. The spatial range is set based on, for example, the size and shape of the multicopter input by the input unit 11. The setting unit 12 also sets a time step interval that allows stable time integration.

[0026] Furthermore, if necessary in the simulation, the setting unit 12 places peripheral objects in the calculation domain (a predetermined range of space). The placement of the peripheral objects is set based on, for example, information about their relative positions, sizes, and shapes input by the input unit 11.

[0027] The setting unit 12 also sets boundary conditions (e.g., outflow boundary conditions) of the calculation domain. Furthermore, the setting unit 12 divides the multicopter into blades and a fuselage, which is the entire body of the multicopter excluding the blades. For example, the fuselage also includes a rotor support portion of the body. The setting unit 12 may perform the division based on information about the multicopter input from the input unit 11.

[0028] 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 other calculation domains. However, the setting unit 12 does not have to divide the calculation domain into region 1 and region 2.

[0029] 2 shows an example of a multicopter. The multicopter M1 includes rotors R1 to R4 and a fuselage D1. When dividing the calculation domain for the multicopter M1, the setting unit 12 may divide the calculation domain into region 1, which is a region around the rotors R1 to R4, and region 2, which is a region including the periphery of the fuselage D1.

[0030] 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 enables efficient computation with sufficient accuracy. The setting unit 12 may use a fine (i.e., small) grid near 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.

[0031] Returning to FIG. 1, the blade calculation unit 13 will now be described. The blade calculation unit 13 executes the following processing to calculate the force that the blade receives from the surrounding air as the blade rotates, and the momentum that 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 calculation for the set region 1. Below, the details of the process of applying the actuator line model executed by the blade calculation unit 13 will be described.

[0032] (A) First, the blade calculation unit 13 deletes the blades from the 3D (dimensions) shape model of the multicopter.

[0033] (B) Next, the blade calculation unit 13 applies blade element data that matches the blade shape to the deleted blade region. The blade element data is 2D data that indicates 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 storage unit 17, for example, or may obtain the blade element data to be used from outside the information processing system 10 (for example, from sources provided via the Internet).

[0034] (C) Then, the blade calculation unit 13 specifically sets the parameters of the actuator line model to be applied.

[0035] FIG. 3 shows an example of blades when an 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 particle has on the surrounding computational grid is expressed as follows:

number

[0036] As will be described later, the object boundary conditions of the multicopter are set when the time integral calculation unit 14 executes calculations. However, since the actuator line model is set for the region around the blades as described above, the blade calculation unit 13 does not need to set the object boundary conditions.

[0037] Figure 4 shows an example of the forces that a marker particle placed on a blade receives from the surrounding air based on the blade element momentum theory. The lift and drag forces acting on a marker particle i on blade B2 are respectively F l and F d θ and z indicate the coordinate axes of the direction of rotation and the direction of thrust, respectively. γ is the blade installation angle (local pitch angle) with respect to the θ axis, which is the direction of rotation of the blade, and α is the angle of attack. At this time, the relative velocity of the blade u relis expressed as follows:

number

number

[0038] Furthermore, the force that 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:

number

[0039] The blade calculation unit 13 is able to perform the calculations (1) to (4) above by setting the parameters ε and Δr. The parameters ε and Δr may be set by a user using the input unit 11, or may be set by the blade calculation unit 13 using settings stored in the storage unit 17. Numerical values ​​other than the parameters ε and Δr used in the calculations (1) to (4) are determined based on information about the multicopter and data obtained by simulation.

[0040] (D) Then, the blade calculation unit 13 performs coordinate transformation for at least one of translation and rotation of the rotation axis together with the airframe, depending on the attitude of the multicopter airframe, for the applied actuator line model. For example, the blade calculation unit 13 may realize coordinate transformation for rotation of the rotation axis by using a quaternion.

[0041] (E) Next, the blade calculation unit 13 determines the blades to which the actuator line model is 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 region around the blade, with a grid size of approximately 1 / 100 of the blade diameter. 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.

[0042] (F) Then, the blade calculation unit 13 calculates the forces (thrust and torque) acting on the blades calculated by equation (3) by applying the actuator line model, and imparts the calculated forces to the parts of the aircraft that support the rotor blades. Meanwhile, the blade calculation unit 13 imparts the momentum of the reaction of these forces to the air around the blades as shown in equation (4).

[0043] (G) The blade calculation unit 13 performs the calculations (1) to (4) above 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 performed 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 the blade imparts to the surrounding air as the blade rotates under the influence of the aircraft's movement and rotation.

[0044] (H) The blade calculation unit 13 executes the calculation (G) for each blade in the 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.

[0045] Returning to FIG. 1 , the time integral calculation unit 14 will be described. The time integral calculation unit 14 arranges a computational grid with a grid size of approximately 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 arrange a computational grid with a grid size different from that of domain 1 in the set domain 2 (i.e., the domain around the fuselage). The grid size is arbitrary, but to ensure a certain degree of calculation accuracy, it is necessary to arrange a finer 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 where the computational grid is arranged.

[0046] The time integral calculation unit 14 performs aerodynamic calculations by applying a numerical calculation method to solve the fluid equations 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. The time integral calculation unit 14 also calculates the effect on the air of boundary conditions that reflect the moving objects. 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, and the particle method. The details of this calculation method are well known, so a detailed explanation will be omitted.

[0047] Furthermore, the time integral calculation unit 14 may use a moving calculation grid method such as a sliding grid or an overset grid, if necessary, in order to reduce the amount of calculation.

[0048] Through this process, the blade calculation unit 13 and the time integral calculation unit 14 can calculate the forces 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.

[0049] The change calculation unit 15 simulates how the multicopter navigates in the air based on the forces acting on the blades from the surrounding air calculated by the blade calculation unit 13 and the forces acting on the fuselage from the surrounding air calculated by the time integral calculation unit 14. In particular, 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 integral calculation unit 14 to calculate the translational force and rotational torque acting on the entire aircraft. The change calculation unit 15 calculates the time changes in the translation, rotation, and attitude of the aircraft by integrating the equations 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 calculations to the fuselage and the results of applying an actuator line model to the blades.

[0050] The display unit 16 displays the simulation results of the change calculation unit 15. If necessary, the display unit 16 may also display at least one of the calculation results of the blade calculation unit 13 and 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 exerted by the air on various points on the surface of the aircraft. 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.

[0051] The storage unit 17 stores the time changes of all air flows within the calculation domain obtained by the calculations performed by the time integral calculation unit 14, the time changes of pressure distribution on the airframe surface, and the time changes of 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 storage 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 shape of the calculation grid, blade element data, and settings of the parameters ε and Δr.

[0052] [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 will be 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.

[0053] The input unit 11 inputs information necessary for calculation, such as information on the multicopter to be simulated, blade rotation conditions, and information on surrounding objects, based on user operation (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 the domains 1 and 2.

[0054] Then, the blade calculation unit 13 applies an actuator line model to calculate the force acting on the blade 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 acting on the aircraft 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 over a fixed time period as the blades rotate. Here, either step S13 or step S14 may be executed first, or both may be executed in parallel.

[0055] The change calculation unit 15 simulates the flight 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).

[0056] [Effect description] 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 aerodynamic calculation method to the calculation of other parts of the aircraft, which makes it possible to dramatically reduce the amount of calculation required for the free flight simulator.

[0057] Previous related technologies applied a numerical calculation method for aerodynamic calculations that discretized and solved the Navier-Stokes equations, which also have viscosity terms, for blade calculations. In this case, in order to obtain calculation results with sufficient accuracy, computational grids with a grid size of 1 / 1000 or less of the blade diameter are placed near the blade. Here, when the computational grid placed near the blade is 1 / 1000 the size of the blade diameter (Situation A), the number of computational grids that should be considered for calculation purposes is 10 times smaller than when the computational grid placed near the blade is 1 / 1000 the size of the blade diameter (Situation B). 3 (1000) times. Furthermore, in Situation A, the calculation time step interval must be 1 / 10 of that in Situation B. Therefore, for example, the amount of calculation for area 1 in Situation A is 10 times that in Situation B. 4 (10,000) times faster. In addition, the faster the blade rotation speed, the smaller the computational grid must be to ensure accuracy of the calculations. This resulted in a huge amount of calculations for the blades.

[0058] On the other hand, in the present invention, the blade calculation unit 13 applies an actuator line model, allowing the computational grid located near the blade to be larger than 1 / 1000 of the blade diameter. This reduces the computational load per blade step 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 computation for Region 1 can be reduced to 1 / 10,000 or less, and it is even possible to reduce the amount of computation for Region 1 to, for example, 1 / 10 or less of the amount of computation for the entire free navigation simulator.

[0059] Therefore, the information processing system 10 according to the present invention can sufficiently calculate the time required for the blades to rotate approximately 1,000 times, and therefore can simulate the free flight of the entire aircraft. For example, the information processing system 10 can also perform free flight simulations of the takeoff and landing processes of an aircraft.

[0060] Furthermore, the above-described method of the information processing system 10 can also ensure the accuracy of calculations. The accuracy of calculations by the information processing system 10 will be described below with reference to data of actual simulator results.

[0061] Figure 6 shows numerical calculation data showing the magnitude of the flow velocity at a given time caused by the influence of the surrounding air when using blades with the same shape and rotational speed as those 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 calculation results for four blade rotational 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 (bottom of Figure 6) that closely match the results of aerodynamic calculations that discretize and solve the Navier-Stokes equations using a very fine grid (top of Figure 6).

[0062] Fig. 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 those in the reference paper (i.e., the calculation results using the actuator line model according to the present invention). Fig. 7 shows five calculation results for blade rotation speeds of 1600 rpm, 1900 rpm, 2200 rpm, 2500 rpm, and 2600 rpm. As shown in Fig. 7, the calculation results obtained show a very good agreement in terms of thrust between 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.

[0063] Figure 8 shows the calculation results of when a flying car takes off, calculated using the actuator line model, in which the reaction force of the blade thrust acts on the surrounding air as downwash, which then hits the ground and spreads sideways. Figure 8 shows the state of the vortices 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.

[0064] The user may input at least one of information about the spacing between marker particles or the parameters of the influence radius of the Gaussian filter when applying the actuator line model to the blade. 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 calculation amount and accuracy of the actuator line model by changing the input parameters.

[0065] Furthermore, the blade calculation unit 13 may set the size of the computational grid applied to the region around the blade to 1 / 1000 or more of the blade diameter. 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.

[0066] 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.

[0067] In the above embodiment, the information processing system according to the present invention has been described as a hardware configuration, 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 perform the processing of each device that constitutes the information processing system 10 described in the above embodiment.

[0068] 9 is a block diagram showing an example of the hardware configuration of an information processing system (i.e., 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.

[0069] The signal processing circuit 91 is a variety of circuits for processing signals under the control of the processor 92 .

[0070] 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 a plurality of these may be used in parallel.

[0071] The memory 93 is a main storage device configured of, for example, a volatile memory. The memory 93 is not limited to one, and a plurality of memories may be provided. The volatile memory may be, for example, a RAM (Random Access Memory) such as a DRAM (Dynamic Random Access Memory).

[0072] The memory 93 is used to store one or more instructions and data. Here, the one or more instructions are stored as a program in the memory 93. The processor 92 can perform the processing described in the above embodiment by reading and executing the program and data from the memory 93.

[0073] 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.

[0074] The storage 94 is an auxiliary storage device configured, for example, by a nonvolatile memory. The storage 94 is not limited to one, and multiple storages may be provided. The nonvolatile memory may be, for example, a hard disk drive (HDD), a read-only memory (ROM) such as a programmable random-only memory (PROM) or 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 described above, and information required for processing.

[0075] 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 the 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 the storage 94 via the interface 95.

[0076] As described above, one or more processors included in each system in the above-described embodiments execute one or more programs including instructions for causing a computer to execute the algorithms described using the drawings. Execution of the programs enables the information processing described in each embodiment to be realized.

[0077] 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, computer-readable media or tangible storage media include random-access memory (RAM), read-only memory (ROM), hard disk drives (HDDs), flash memory, solid-state drives (SSDs) or other memory technologies, compact disc read-only memory (CD-ROMs), digital versatile disks (DVDs), Blu-ray discs or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage, or other magnetic storage devices. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals. The transitory computer-readable medium or communication medium may provide the program to the computer via a wired communication path, such as an electric wire or optical fiber, or via a wireless communication path.

[0078] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those 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. [Explanation of symbols]

[0079] 10 Information Processing Systems 11 Input section 12 Setting section 13 Blade calculation section 14 Time integral calculation section 15 Change calculation section 16 Display section 17 Memory section 90 Information Processing Systems 91 Signal processing circuit 92 Processor 93 Memory 94 Storage 95 Interface

Claims

1. A step of discretizing a space around a fuselage of an aircraft using a computational grid and applying a numerical calculation 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 by using a result of applying the numerical calculation method and a result of applying the actuator line model to the blades; A method for developing a simulator that runs on a computer.

2. the computer receives input of at least one of information about the spacing 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.

3. 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.

4. 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 the blade of the aircraft; a simulator unit that simulates the flight of the aircraft by using the application result of the numerical calculation method and the application result of the actuator line model to the blades. Information processing system.

5. an input unit that receives input of at least one of information about the interval between marker particles that constitute the blade or a parameter of the influence radius of a Gaussian filter; the simulator unit uses the received information in applying the actuator line model. The information processing system according to claim 4 .

6. 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.

7. A step of discretizing a space around a fuselage of an aircraft using a computational grid and applying a numerical calculation 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 by using a result of applying the numerical calculation method and a result of applying the actuator line model to the blades; A program that causes a computer to execute the following.

8. receiving input of at least one of information about the spacing between marker particles constituting the blade or a parameter of the radius of influence of a Gaussian filter into the computer, and causing the computer to use the received information in applying the actuator line model; The program according to claim 7.

9. causing the computer to use 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 for applying the actuator line model; The program according to claim 7 or 8.

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