Development method of simulator, information processing system, and program

Abstract

The development method of the simulator of one embodiment of the present disclosure is performed by a computer to execute the following steps: a step of discretizing a space around a fuselage of a flight body using a computational grid and applying a numerical calculation method of aerodynamic calculation by solving a discretized fluid equation; a step of applying an actuation wire model to a blade of the flight body; and a step of simulating sailing of the flight body using a result of application of the numerical calculation method and a result of application of the actuation wire model to the blade.

Description

Technical Field

[0001] This invention relates to a method for developing simulators, an information processing system, and a program. Background Technology

[0002] During the development phase, aircraft need to be verified to ensure safe flight. In particular, for new types of manned aircraft such as flying cars that have become increasingly practical in recent years, more rigorous safety verification is required because these are new technologies and the safety of passengers must be ensured.

[0003] Because experiments often involve setting extremely difficult navigation conditions or requiring the verification of a large number of navigation conditions, there are limitations to using actual aircraft or models for real-world verification experiments. Furthermore, since there are aspects of the experiment that cannot be measured, numerical simulations on computers are frequently used for verification. In these simulations, methods such as numerical fluid dynamics are employed.

[0004] In particular, compared to drones, flying cars are required to have extremely high flight safety. For example, scenarios can be envisioned such as multiple multi-rotor aircraft approaching each other (especially vertically), multi-rotor aircraft approaching buildings, any rotor experiencing abnormal rotation (e.g., stopping), or unexpected strong winds. By conducting simulations, it can be determined how the multi-rotor aircraft recovers its attitude and maintains safe flight under these conditions. Furthermore, simulations can be used to verify the configuration (or addition) of new rotors to improve safety, and the verification results can be incorporated into the design.

[0005] As a related technology, Non-Patent Document 1 discloses a technique for applying numerical fluid dynamics simulation to quadcopter air taxis used in urban transportation systems.

[0006] Existing technical documents Non-patent literature Non-patent document 1: Patricia Ventura Diaz and Seokkwan Yoon, "High-FidelitySimulations of a Quadrotor Vehicle for Urban Air Mobility", AIAA SciTech Forum2022, January 3-7, 2022, San Diego, CA&Virtual. Summary of the Invention

[0007] The problem that the invention aims to solve In multi-rotor aircraft and other flying bodies, the thin and fine rotor blades (rotor blades; hereinafter referred to as blades) that constitute the rotor rotate at high speed during flight. For such flying bodies, a method is considered to discretize the space using a computational grid and directly calculate the fluid equations numerically for simulation. In this case, because a very fine computational grid needs to be configured near the blade surface, the total number of computational grid points used in the calculation becomes huge. Therefore, in order to determine the forces (i.e., thrust) acting on the blades and the changes in the surrounding airflow at each time step of the calculation, a huge amount of computation is required.

[0008] Furthermore, a single computation time step is a very short time interval. Therefore, it becomes extremely difficult for the computer to perform simulations until the extent of the aircraft's translational, rotational, and attitude changes (e.g., 1-2 minutes) can be confirmed. For example, even when using a supercomputer to perform the above numerical simulations, there is a problem that the simulation time can only be advanced up to the time it takes for the blades to rotate 30 times (e.g., 2-3 seconds). The numerical hydrodynamic simulation described in Non-Patent Document 1 is performed to calculate the thrust obtained from the blade rotation, not to calculate the aircraft's navigation.

[0009] This invention was made in view of this problem and provides a method for developing a simulator, an information processing system, and a program that helps reduce the necessary amount of computation.

[0010] Technical means for solving problems The present invention discloses a method for developing a simulator, executed by a computer, comprising the following steps: The steps involve discretizing the space surrounding the fuselage of an aircraft using a computational grid and applying aerodynamic numerical calculation methods by solving the discretized fluid equations. The step of applying the actuation line model to the blades of the flying body; The flight path of the aircraft is simulated by using the application results of the numerical calculation method and the application results of the actuation line model for the blade.

[0011] An information processing system according to one aspect of the present invention includes: The first application section uses a computational grid to discretize the space around the fuselage of the aircraft and applies numerical calculation methods for aerodynamics by solving the discretized fluid equations. The second application unit applies the actuation line model to the blades of the flying body; The simulation unit uses the application results of the numerical calculation method and the application results of the actuation line model for the blade to simulate the flight of the aircraft.

[0012] A program according to one aspect of the present invention is used to cause a computer to perform the following steps: The steps involve discretizing the space surrounding the fuselage of an aircraft using a computational grid and applying aerodynamic numerical calculation methods by solving the discretized fluid equations. The step of applying the actuation line model to the blades of the flying body; The flight path of the aircraft is simulated by using the application results of the numerical calculation method and the application results of the actuation line model for the blade.

[0013] The effects of the invention According to the present invention, a method for developing simulators, an information processing system, and a program can be provided that help reduce the amount of computation required. Attached Figure Description

[0014] [ Figure 1 ] Figure 1 This is a block diagram representing an example of an information processing system.

[0015] [ Figure 2 ] Figure 2 This represents an example of a multi-rotor aircraft.

[0016] [ Figure 3 ] Figure 3 This represents an example of a blade when the actuation line model is applied.

[0017] [ Figure 4 ] Figure 4 This represents an example of the force exerted on the surrounding air by a marker particle positioned on a blade.

[0018] [ Figure 5 ] Figure 5 This is a flowchart representing a typical processing step in an information processing system.

[0019] [ Figure 6 ] Figure 6 It is a numerical calculation data representing the magnitude of the flow velocity.

[0020] [ Figure 7 ] Figure 7 It is a chart showing the experimental and calculation results of thrust comparison.

[0021] [ Figure 8 ] Figure 8 It represents the calculated result of the reaction of the blade thrust calculated using the actuation line model as the state of the surrounding air given by the downwash.

[0022] [ Figure 9 ] Figure 9 This is a block diagram illustrating an example of the hardware configuration of an information processing apparatus according to an implementation method. Detailed Implementation

[0023] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that, for clarity of description, appropriate omissions and simplifications have been made to the following descriptions and drawings of the embodiments of the invention. Furthermore, in this embodiment, unless otherwise explicitly stated, when defining "at least one of a plurality of items," the definition may mean any single item or any plurality of items including all items.

[0024] For the purpose of illustrating exemplary embodiments, all features or steps shown in any of the drawings are not essential, and any part of a feature or step may be omitted. Furthermore, the order of steps described in the specification and drawings may be appropriately changed.

[0025] [Related Technologies] First, the technology related to free-flight simulators for multirotor aircraft, such as flying cars equipped with multiple rotors, will be explained. Multirotor aircraft obtain thrust from the surrounding air by rotating their blades under gravity, thus enabling free-flight. A free-flight simulator is a program that, given pre-provided information such as the shape and weight of the multirotor aircraft, uses only the time-varying blade rotation speed as a variable to simulate and predict how the multirotor aircraft will fly in the air.

[0026] In the free-flight simulator, the forces acting on the airborne part of the aircraft, including its blades, are calculated, as well as the effects of the aircraft's movement on the surrounding air. In this force calculation, for the blade section, the forces generated by blade rotation are considered; for the entire aircraft, the forces acting on it due to flight are considered.

[0027] To accurately calculate the forces acting on a body from the surrounding air, the computer needs to solve the fluid equations (Navier-Stokes equations) with viscous terms. Several methods exist for calculating the forces acting on rapidly rotating blades: for example, using a high-resolution computational mesh capable of solving the boundary layer of the object's surface, using a wall function model, or using DES (separated eddy simulation) in the near-field calculations involving the blades. However, regardless of the method, the computational load becomes enormous. Even in the wall function method, which is considered the least computationally demanding, the computer still needs to allocate a high-resolution computational mesh to the vicinity of the blades throughout the calculation. Therefore, the computational load becomes very high.

[0028] Alternatively, to reduce the computational load, the computer can use the Euler equations, a fluid equation without viscosity terms, for calculation. In this case, since no boundary layer is generated for the airflow, the limitation on the computational grid resolution depends only on the object shape. However, using this method, the computer can only calculate the lift in the vertical direction and the blade rotation, and cannot calculate the downwash or other airflow generated by the blades. Therefore, this method cannot be applied to free-flight simulators.

[0029] One example of the object of this invention is to develop a simulator that can provide only the rotational conditions of the blades as variables to the simulated aircraft, allowing the aircraft to navigate freely in a virtual space within a computer. To this end, the introduction (adoption) of an actuation line model is a novel feature of this invention.

[0030] It should be noted that the term "flying body" in this disclosure refers to any flying object having a blade portion and a fuselage portion, such as manned or unmanned drones, flying cars, airplanes, spacecraft, etc. In the following embodiments, the term "flying body" is described using a multi-rotor aircraft as an example, but it may also include gyroplanes and other types of aircraft besides multi-rotor aircraft.

[0031] Implementation Method 1 [Explanation of Composition] Figure 1 This is a block diagram illustrating an example of an information processing system. The information processing system 10 includes an input unit 11, a setting unit 12, a blade calculation unit 13, a time integration calculation unit 14, a change calculation unit 15, a display unit 16, and a storage unit 17. The following describes each part of the information processing system 10.

[0032] The input unit 11 is a component that accepts input information from the user. The input unit 11 may be composed of an input interface such as a touch panel, keyboard, or mouse. The user can input any content into the information processing system 10 using the input unit 11. For example, the user can use the input unit 11 to input information such as the shape and mass of various parts of the multirotor aircraft being simulated, as well as the rotation conditions (e.g., rotational speed) of the multirotor aircraft blades. Furthermore, the user can also use the input unit 11 to input information about the relative position, size, and shape of objects existing around the multirotor aircraft (hereinafter also referred to as surrounding objects) relative to the multirotor aircraft, as well as the parameters used in the calculations, described later. Surrounding objects include, for example, the ground, buildings, etc.

[0033] The setting unit 12 sets a predetermined spatial range, including the entire multirotor aircraft as the simulation object, as the calculation area in the simulation. The spatial range is set, for example, based on the size and shape of the multirotor aircraft input through the input unit 11. In addition, the setting unit 12 also sets the time step interval that enables stable time integration.

[0034] Furthermore, when required during simulation, the setting unit 12 arranges surrounding objects within the calculation area (a predetermined space). The arrangement of surrounding objects is set, for example, based on information about their relative position, size, and shape input through the input unit 11.

[0035] Furthermore, the setting unit 12 sets the boundary conditions of the calculation region (e.g., outflow boundary conditions). Further, the setting unit 12 divides the multirotor aircraft into blades and the fuselage, which consists of all parts removed from the overall multirotor aircraft body. For example, the rotor support section in the fuselage is also included. The setting unit 12 can perform this division based on the multirotor aircraft information input from the input unit 11.

[0036] Here, the setting unit 12 may also divide the calculation area into a region around the blade (hereinafter also referred to as region 1) and a region outside region 1 (hereinafter also referred to as region 2). Region 1 is, for example, a region existing within a predetermined length from the surface of the multirotor blade. Region 2 may be divided into a region around the multirotor fuselage and other calculation areas. However, the setting unit 12 does not necessarily divide the calculation area into region 1 and region 2.

[0037] Figure 2 This represents an example of a multi-rotor aircraft. The multi-rotor aircraft M1 includes rotors R1 to R4 and a fuselage D1. When the setting unit 12 divides the calculation area for the multi-rotor aircraft M1, the calculation area can be divided into the area around the rotors R1 to R4, i.e., area 1, and the area including the area around the fuselage D1, i.e., area 2.

[0038] Furthermore, the setting unit 12 sets the shape of the computational grid that divides the computational region. Any shape can be used as the computational grid shape, such as a rectangular prism, a tetrahedron, etc. The shape of the computational grid can be input by the user through the input unit 11, stored in the storage unit 17, or set by the setting unit 12 based on information about the computation. The setting unit 12 sets a grid size that enables efficient computation with sufficient accuracy. The setting unit 12 can use a finer (i.e., smaller) grid near the fuselage (e.g., within a predetermined distance from the fuselage) and a coarser (i.e., larger) grid outside the fuselage. Furthermore, the setting unit 12 can also change the grid size according to the intensity of the eddies in the generated flow.

[0039] return Figure 1The blade calculation unit 13 will now be described. The blade calculation unit 13 performs the following processing: for the region surrounding the blade, it calculates the force exerted on the blade by the blade from the surrounding air due to blade rotation, and it calculates the momentum exerted by the blade on the surrounding air. When the setting unit 12 divides the calculation area into region 1 and region 2, the blade calculation unit 13 performs the above calculations for the set region 1. Details of the actuation line model application processing performed by the blade calculation unit 13 will be described below.

[0040] (A) First, the blade calculation unit 13 removes the blade from the 3D (dimensional) shape model of the multi-rotor aircraft.

[0041] (B) Next, the blade calculation unit 13 applies airfoil data that conforms to the blade shape to the deleted blade region. Airfoil data is 2D data representing the blade profile shape and its aerodynamic characteristics. The blade calculation unit 13 may use airfoil data stored in the storage unit 17, or it may obtain the airfoil data to be used from outside the information processing system 10 (e.g., provided by the Internet).

[0042] (C) Then, the blade calculation unit 13 specifically sets the parameters of the applied actuation line model.

[0043] Figure 3 This illustrates an example of a blade when the actuation line model is applied. Figure 3 In this model, each leaf, B1 to B3, is represented by multiple particles (hereinafter referred to as labeled particles) that make up the leaf. The labeled particles... Figure 3 The symbols are represented as points, and each blade is composed of an arrangement of labeled particles. Furthermore, each blade B1 to B3 exists within the computational grid. The Gaussian filter η, which determines the range of influence exerted by the labeled particles on the surrounding computational grid, is shown below.

[0044]

Mathematical Formula 1

[0045] In (1), d i ε is the distance between the i-th labeled particle and the computational grid point located at (x, y, z). ε is the standard deviation of the Gaussian distribution, and ε is a parameter representing the radius of influence of the labeled particle. Figure 3 A circle with radius ε centered on the marked particle is displayed. It should be noted that... Figure 3 To simplify, the blades and computational mesh are represented in 2D, but they are actually represented in 3D.

[0046] It should be noted that, as described later, the time integration calculation unit 14 sets the object boundary conditions of the multi-rotor aircraft when performing calculations. However, since the actuation line model is set for the area around the blades as described above, the blade calculation unit 13 does not need to set the object boundary conditions.

[0047] Figure 4 This represents an example of the forces exerted on a marked particle on a blade by the surrounding airflow, based on airfoil momentum theory. The lift and drag acting on the marked particle i on blade B2 are denoted as F. l and F d θ and z represent the coordinate axes for the direction of rotation and thrust, respectively. γ is the installation angle (local pitch angle) of the blade relative to the θ axis, which represents the direction of rotation, and α is the angle of attack. At this point, the relative velocity u of the blade... rel It is represented as follows.

[0048]

Mathematical Formula 2

[0049] Here, u z It is the z-axis component of the surrounding airflow, u θ This is the θ-axis component of the surrounding airflow. Furthermore, r is the distance of the marker particle i from the center of blade rotation, and Ω is the angular velocity of the blade. Using u... rel At that time, the force F exerted by the blade on the surrounding air at the location of the marked particle is... 2D It is represented as follows.

[0050]

Mathematical Expression 3

[0051] Here, Ca is the chord length of the blade, and e l e d These are the unit vectors representing the directions of lift and drag, respectively. C l C d These are the lift coefficient and drag coefficient, respectively, prepared in advance as airfoil data for an angle of attack α. Additionally, Δr is a parameter representing the distance between the labeled particles.

[0052] Furthermore, the force exerted by the labeled particle i on the computational grid point located at (x,y,z) (i.e., the momentum given to the surrounding air by the rotation of the blade) is calculated as follows.

[0053]

Mathematical Expression 4

[0054] Here, F 2D,i It is F 2D The component of the labeled particle i, N p It represents the total number of labeled particles.

[0055] The blade calculation unit 13 can perform the calculations described in (1) to (4) by setting parameters ε and Δr. The parameters ε and Δr can be set by the user using the input unit 11, or the blade calculation unit 13 can use the settings stored in the storage unit 17. The values ​​used in the calculations in (1) to (4), other than the parameters ε and Δr, are determined based on information about the multi-rotor aircraft and data obtained through simulation.

[0056] (D) After that, the blade calculation unit 13 performs a coordinate transformation for the applied actuation line model, based on the attitude of the multirotor aircraft body, with respect to at least one of translation along with the body or rotation along the rotation axis. For example, the blade calculation unit 13 can implement the coordinate transformation for rotation axis rotation using quaternions.

[0057] (E) Next, the blade calculation unit 13 determines the blades for which the actuation line model is applied when the 3D model of the multirotor aircraft is placed in the calculation area. The blade calculation unit 13 configures a calculation grid with a grid size of approximately 1 / 100 of the blade diameter in the area surrounding the blade. The grid size is arbitrary, but the size of the grid size will affect the calculation accuracy. The shape of the calculation grid is set by the setting unit 12.

[0058] (F) Then, the blade calculation unit 13 calculates the force (thrust and torque) on the blade calculated by mathematical formula (3) by applying the actuation line model, and applies the calculated force to the part supporting the rotor blade. On the other hand, the blade calculation unit 13 applies the reaction momentum of this force to the air around the blade as shown in mathematical formula (4).

[0059] (G) The blade calculation unit 13 performs the calculations (1) to (4) above for a blade within region 1 defined in (E) using the processing results performed in (F). The calculation grid used in the calculation is set as described in (E). As a result, the blade calculation unit 13 can calculate the force exerted on the blade by the surrounding air due to the blade rotation and the momentum given to the surrounding air under the influence of the movement or rotation of the aircraft.

[0060] (H) The blade calculation unit 13 performs (G) calculations for each blade in region 1, thereby calculating the forces exerted on all blades by the surrounding air and the momentum given to the surrounding air.

[0061] return Figure 1The time integration calculation unit 14 will now be described. The time integration calculation unit 14 configures a calculation grid with a grid size approximately 1 / 300th of the total fuselage length (i.e., the total length of the fuselage) very close to the surface of the aircraft. When the setting unit 12 divides the calculation area into region 1 and region 2, the time integration calculation unit 14 can configure a calculation grid with a different grid size than region 1 in the set region 2 (i.e., the area surrounding the fuselage). The grid size is arbitrary, but to ensure a certain level of calculation accuracy, a fine grid smaller than a predetermined size is required. However, a larger grid size can also be used as the distance from the aircraft. The shape of the calculation grid is set by the setting unit 12. Then, the time integration calculation unit 14 sets the object boundary conditions of the moving object (i.e., the multi-rotor aircraft) in the area where the calculation grid is configured.

[0062] The time integration calculation unit 14 performs aerodynamic calculations by applying numerical calculation methods to and solving the fluid equations discretized using a computational grid, while considering the established boundary conditions of the object. Thus, the time integration calculation unit 14 calculates the forces exerted on the fuselage by the surrounding air due to the movement of all parts of the aircraft (i.e., the fuselage) excluding the blades. Furthermore, it also calculates the influence of the boundary conditions of the moving object on the air side. The "numerical calculation method for aerodynamic calculations" refers to well-known calculation methods other than the actuation line model, such as the finite volume method, finite element method, lattice Boltzmann method, and particle method. Since the details of this calculation method are well known, a description is omitted.

[0063] In addition, when necessary, the time integration calculation unit 14 can also use moving computational grid methods such as sliding grid or overlapping grid to reduce the amount of computation.

[0064] During this process, the blade calculation unit 13 and the time integration calculation unit 14 can calculate the forces exerted on the blades and fuselage (i.e., the entire aircraft) by the surrounding air at a given moment. By repeatedly performing this calculation within a certain time interval of blade rotation, the blade calculation unit 13 and the time integration calculation unit 14 can calculate the airflow corresponding to the blade rotation and the surrounding airflow generated by the fuselage movement. This allows the flight behavior of the multirotor aircraft to be confirmed. It should be noted that when calculating the airflow corresponding to the blade rotation, the blade calculation unit 13 can also use the time-varying rotation speed condition input from the input unit 11.

[0065] The variation calculation unit 15 simulates the flight of a multirotor aircraft 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 integration calculation unit 14. Specifically, the variation calculation unit 15 meticulously divides the fuselage surface and calculates the translational force and rotational torque acting on the entire aircraft by integrating the forces acting on the fuselage surface obtained by the time integration calculation unit 14. The variation calculation unit 15 calculates the temporal changes in the translation, rotation, and attitude of the multirotor aircraft by integrating the equations of motion using information such as the size, shape, and mass of each part of the multirotor aircraft and the moment of inertia about the center of gravity. In other words, the variation calculation unit 15 simulates the flight of the multirotor aircraft by applying the results of numerical calculations of aerodynamics for the fuselage and the results of actuation line models for the blades.

[0066] Display unit 16 displays the simulation results of change calculation unit 15. If necessary, display unit 16 may further display at least one of the calculation results of blade calculation unit 13 or time integration calculation unit 14. These calculation results include airflow around the blade periphery or near the fuselage surface, air pressure at various points on the fuselage surface, etc. Display unit 16 may be, for example, a monitor or a touch panel. By visually checking display unit 16, the user can understand the results of the multirotor free-flight simulation after a certain period of time.

[0067] The storage unit 17 stores the time variations of all airflow within the calculation area obtained from the calculations performed by the time integration calculation unit 14, the time variations of the pressure distribution on the fuselage surface, and the time variations of the forces (thrust and torque) acting on the blades obtained from the calculations performed by the blade calculation unit 13. The storage frequency is specified by the setting unit 12. In addition, the storage unit 17 also stores the information required for processing, such as the program for the setting unit 12 to the display unit 16 to perform processing, the shape of the calculation grid, airfoil data, and the settings of parameters ε and Δr.

[0068] [Process Description] Figure 5 This is a flowchart illustrating an example of representative processing by the information processing system 10. Figure 5 The flowchart illustrates the processing of information processing system 10. It should be noted that details regarding each process are as described above, and therefore are omitted.

[0069] Based on the user's operation, the input unit 11 inputs information required for calculation, such as information about the multi-rotor aircraft being simulated, the rotation conditions of the blades, and information about surrounding objects (step S11). The setting unit 12 sets calculation conditions such as the calculation area, the configuration of surrounding objects, boundary conditions, and the shape of the calculation mesh (step S12). It should be noted that the setting unit 12 can also make further settings for regions 1 and 2.

[0070] Then, the blade calculation unit 13 calculates the force exerted on the blade by the surrounding air by applying the actuation line model (step S13). Details are shown in (A) to (H). Furthermore, the time integration calculation unit 14 calculates the force exerted on the blade by the surrounding air and its influence on the surrounding air by applying aerodynamic numerical calculation methods (step S14). Details are also as described above. The blade calculation unit 13 and the time integration calculation unit 14 repeatedly perform the calculations of steps S13 and S14 over a certain period of time as the blade rotates. Here, steps S13 and S14 can be performed either first or in parallel.

[0071] The variation calculation unit 15 simulates the flight of the multi-rotor aircraft based on the calculation results of the blade calculation unit 13 and the time integration calculation unit 14 (step S15). The display unit 16 displays the calculation results of the variation calculation unit 15 (step S16).

[0072] [Explanation of Effects] As described above, the information processing system 10 applies an actuator line model for calculations on the blades of the aircraft, while applying aerodynamic numerical calculation methods for calculations on other parts of the aircraft. Therefore, the computational load required for a free-flight simulator can be significantly reduced.

[0073] In existing related technologies, the calculation of blades has also applied numerical calculation methods for aerodynamic calculations by solving discretized Navier-Stokes equations with viscous terms. In this case, to obtain sufficiently accurate calculation results, a computational grid with a mesh size less than 1 / 1000 of the blade diameter is configured near the blade. Here, compared to the case where the computational grid near the blade is one-thousandth the size of the blade diameter (Case A), the number of computational grids considered as the object of calculation becomes 10. 3 (1000) times. Furthermore, compared to case B, the time step interval for case A also needs to be reduced to 1 / 10. Therefore, for example, the computational cost for region 1 becomes 10 times that of case B in case A. 4 (10000) times. Furthermore, the faster the blade rotation speed, the smaller the computational grid needs to be to ensure calculation accuracy. Therefore, the computational workload related to the blades becomes enormous.

[0074] On the other hand, in this invention, the blade calculation unit 13, by applying an actuation line model, can set the calculation grid arranged near the blade to be larger than 1 / 1000 of the blade diameter. Therefore, compared with related technologies, the computational load of each step of the blade can be reduced. For example, case A in the related technology can be changed to case B in this invention. As a result, the computational load for region 1 can be reduced to less than 1 / 10000, for example, the computational load for region 1 can be set to less than 1 / 10 of the overall computational load of the free navigation simulator.

[0075] Therefore, the information processing system 10 of the present invention can fully calculate the time until the blades rotate approximately 1000 times, thereby enabling the simulation of free-flight of the entire aircraft. For example, the information processing system 10 can also perform free-flight simulations regarding the takeoff and landing processes of the aircraft.

[0076] Furthermore, the method of the information processing system 10 described above can also ensure the accuracy of the calculation. The following explanation, referring to actual simulator results, illustrates the calculation accuracy of the information processing system 10.

[0077] Figure 6 This represents numerically calculated data showing the velocity at a given moment, influenced by the surrounding airflow, when using blades of the same shape and rotational speed as those used in the reference (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 calculations include four results for blade rotational speeds of 1600 rpm, 1900 rpm, 2200 rpm, and 2500 rpm. For example... Figure 6 As shown, the method of the present invention, which uses the actuation line model, can obtain aerodynamic calculation results comparable to those obtained by discretizing the Navier-Stokes equations using an extremely fine mesh. Figure 6 The calculation results in the previous paragraph are very consistent. Figure 6 next paragraph).

[0078] Figure 7 This is a graph of the results of calculations performed by the information processing system 10 using the same blade shape and rotational speed as in the reference (i.e., calculation results using the actuation line model of the present invention). As a result of the calculations, Figure 7The calculation results are displayed for five blade rotation speeds of 1600 rpm, 1900 rpm, 2200 rpm, 2500 rpm, and 2600 rpm. For example... Figure 7 As shown, thrust calculations are obtained that are in very good agreement with experimental data from the references and aerodynamic calculations using extremely fine mesh discretization to solve the Navier-Stokes equations.

[0079] Figure 8 This represents the calculated result of the reaction of the blade thrust calculated using the actuation line model when the flying car takes off, which is given to the surrounding air as a downwash and diffuses laterally after it hits the ground. Figure 8 The generated vortex state is shown as an isosurface of the second invariant of the air velocity gradient tensor, and the information processing system 10 is able to calculate very fine vortices emitted from the blades.

[0080] It should be noted that users can also input at least one of the parameters, such as the marker particle spacing or the Gaussian filter influence radius, when applying the actuation line model to the blade. The blade calculation unit 13 can use the input information when applying the actuation line model. Therefore, users can freely adjust the degree of computational reduction and accuracy of the actuation line model by changing the input parameters.

[0081] Furthermore, the blade calculation unit 13 can also set the size of the computational grid applied to the blade's peripheral region to 1 / 1000 or more of the blade diameter. For example, the blade calculation unit 13 can also set the size of the computational grid to 1 / 100 of the blade diameter. By setting this value, the blade calculation unit 13 can reduce the computational load while maintaining the computational accuracy of the applied actuation line model. However, the blade calculation unit 13 can also set the computational grid length to other sizes when needed. For example, the blade calculation unit 13 can also set the size of the computational grid to any size such as 1 / 50 or 1 / 200 of the blade diameter.

[0082] The information processing system 10 of the present invention can be configured as a single computer device or as a distributed system having multiple computer devices. In a distributed system, the processing performed by the information processing system 10 can be shared by multiple computer devices. That is, the components from the input unit 11 to the storage unit 17 can also be distributed across two or more computer devices.

[0083] In the above embodiments, although the information processing system of the present invention has been described as a hardware configuration, the information processing system of the present invention is not limited thereto. The present invention can also achieve the processing of each device constituting the information processing system 10 described in the above embodiments by having a processor in a computer execute a computer program.

[0084] Figure 9 This is a block diagram illustrating an example of the hardware configuration of an information processing system (in other words, a computer) implemented in accordance with the method described. (See reference...) Figure 9 The information processing system 90 includes a signal processing circuit 91, a processor 92, a memory 93, a storage device 94, and an interface 95.

[0085] The signal processing circuit 91 is a series of circuits used to process signals under the control of the processor 92.

[0086] The processor 92 is connected to the memory 93 and performs the system processing described in the above embodiments by reading computer programs from the memory 93 and executing them while communicating with the memory 93. As an example of the processor 92, one of the following can be used: CPU (Central Processing Unit), MPU (Micro Processing Unit), GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), DSP (Demand-Side Platform), and ASIC (Application Specific Integrated Circuit), or multiple of them can be used in parallel.

[0087] Memory 93 is, for example, main memory composed of volatile memory. Memory 93 is not limited to one unit; multiple units may be provided. Volatile memory may be, for example, RAM (Random Access Memory) such as DRAM (Dynamic Random Access Memory).

[0088] The memory 93 is used to store one or more instructions and data. Here, one or more instructions are stored in the memory 93 as a program. The processor 92 is able to perform the processing described in the above embodiment by reading from the memory 93 and executing these programs and data.

[0089] It should be noted that the memory 93 may be located outside the processor 92, or it may be built into the processor 92. Furthermore, the memory 93 may also include a storage device configured remotely from the processor constituting the processor 92. In this case, the processor 92 can access the memory 93 through an I / O (Input / Output) interface.

[0090] Storage device 94 is, for example, an auxiliary storage device composed of non-volatile memory. Storage device 94 is not limited to one; multiple devices may be provided. Non-volatile memory may be, for example, ROM (Read Only Memory) such as HDD (Hard Disk Drive), PROM (Programmable Random Only Memory), EPROM (Erasable Programmable Read Only Memory), flash memory, or SSD (Solid State Drive). Storage device 94 stores the program supplied to memory 93. Furthermore, storage device 94 functions as storage unit 17 in Embodiment 1, storing the calculation results of the time integration calculation unit 14 and the change calculation unit 15, as well as information required for processing.

[0091] Interface 95 includes communication circuitry for sending / receiving signals or data over a network. Interface 95 may be, for example, a NIC (Network Interface Card). Processor 92 can send data stored in memory 93 and storage device 94 to other information processing systems via interface 95, and can also store data sent from other information processing systems via interface 95 into memory 93 and storage device 94.

[0092] As described above, each system in the above embodiments has one or more processors executing one or more programs, which contain a group of instructions that cause the computer to execute the algorithms described in the accompanying drawings. By executing the program, the information processing described in each embodiment can be realized.

[0093] A program contains a set of instructions or software code that, when read by a computer, causes the computer to perform one or more functions described in the implementation. The program may be stored on 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 drive (HDD), flash memory, solid-state drive (SSD) or other memory technologies, read-only optical disc (CD-ROM), digital versatile optical disc (DVD), Blu-ray disc (registered trademark) or other optical disc storage devices, magnetic tape cassettes, magnetic tape, disk storage devices, or other magnetic storage devices. The program may also be transmitted on a transient computer-readable medium or a communication medium. By way of example, and not limitation, a transient computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagation signals. A transient computer-readable medium or communication medium may supply the program to a computer via a wired communication path such as a power line and optical fiber, or a wireless communication path.

[0094] While this disclosure has been described above with reference to embodiments, it is not limited to the embodiments described above. Within the scope of this disclosure, various modifications to the structure and details of this disclosure that are understandable to those skilled in the art can be made. Furthermore, each embodiment can be appropriately combined with other embodiments.

[0095] This application claims priority based on Japanese Patent Application No. 2024-018919, filed on February 9, 2024, the entire contents of which are incorporated herein by reference.

[0096] [Explanation of Labels in the Attached Images] 10. Information Processing System 11. Input Section 12. Setting Department 13. Blade Calculation Section 14. Time Integration Calculation Department 15. Change Calculation Department 16. Display Section 17. Storage Department 90. Information Processing System 91. Signal processing circuit 92. Processor 93. Memory 94. Storage device 95. Interface

Claims

1. A method for developing a simulator, executed by a computer, comprising the following steps: The steps involve discretizing the space surrounding the fuselage of an aircraft using a computational grid and applying aerodynamic numerical calculation methods by solving the discretized fluid equations. The step of applying the actuation line model to the blades of the flying body; The flight path of the aircraft is simulated by using the application results of the numerical calculation method and the application results of the actuation line model for the blade.

2. The simulator development method according to claim 1, wherein, The computer accepts input of at least one of the parameters constituting the blade's marker particle spacing or the Gaussian filter's influence radius, and uses the accepted information when applying the actuation line model.

3. The method for developing a simulator according to claim 1 or 2, wherein, The computer uses a computational grid of at least 1 / 1000th of the blade diameter in the computational region surrounding the blade for the application of the actuation line model.

4. An information processing system, comprising: The first application section uses a computational grid to discretize the space around the fuselage of the aircraft and applies numerical calculation methods for aerodynamics by solving the discretized fluid equations. The second application unit applies the actuation line model to the blades of the flying body; The simulation unit uses the application results of the numerical calculation method and the application results of the actuation line model for the blade to simulate the flight of the aircraft.

5. The information processing system according to claim 4, further comprising: The input unit accepts input of at least one of the parameters constituting the blade, namely the spacing between the marked particles or the radius of influence of the Gaussian filter. The second application unit uses the received information when applying the actuation line model.

6. The information processing system according to claim 4 or 5, wherein, The second application unit uses a computational grid of a size greater than 1 / 1000 of the blade diameter in the computational region surrounding the blade for the application of the actuation line model.

7. A program for causing a computer to perform the following steps: The steps involve discretizing the space surrounding the fuselage of an aircraft using a computational grid and applying aerodynamic numerical calculation methods by solving the discretized fluid equations. The step of applying the actuation line model to the blades of the flying body; The flight path of the aircraft is simulated by using the application results of the numerical calculation method and the application results of the actuation line model for the blade.

8. The procedure according to claim 7, wherein, The computer accepts input of at least one of the parameters constituting the blade's marker particle spacing or the Gaussian filter's influence radius, and uses the accepted information when applying the actuation line model.

9. The procedure according to claim 7 or 8, wherein, The computer uses a computational grid of at least 1 / 1000th of the blade diameter in the computational region surrounding the blade for the application of the actuation line model.

Images