Air oil filling and receiving simulation method

Abstract

The invention provides an air refueling and refueling simulation method, which comprises the following steps of: performing grid division under a refueling machine coordinate system, calculating refueling machine tail vortex field distribution in a grid division space range, and generating a refueling machine tail flow field grid data file; constructing a wake flow model according to the refueling machine wake flow field grid data file, and inputting two-machine interference pneumatic data into the wake flow model to obtain wake flow data; establishing a hose and taper sleeve assembly model according to the wake flow data, obtaining taper sleeve sinkage data, adjusting a taper sleeve pneumatic correction coefficient, and inputting the taper sleeve pneumatic correction coefficient into the hose and taper sleeve assembly model to generate a hose and taper sleeve assembly model taper sleeve pneumatic coefficient correction table data file. According to the air refueling and refueling simulation method, a wake flow calculation model is improved, two-machine interference data and a wake flow field grid file are fully utilized on the basis of a horseshoe vortex system theoretical method, the simulation precision of a refueling machine wake flow field is improved, and meanwhile the division number of wake flow field grids is greatly reduced.

Description

[0001] This application is based on Chinese patent application 202411365868.1 (filing date: September 27, 2024) and enjoys the priority of the Chinese patent application. This application includes all the contents of the Chinese patent application by reference. Technical Field

[0002] The invention belongs to the field of aviation technology, and in particular relates to an aerial refueling simulation method. Background Art

[0003] At present, aerial refueling technology is an important aviation technology that can significantly improve the endurance and combat capability of aircraft. The most commonly used system in the world is the hose-drogue refueling system. During simulation training, it is necessary to calculate the state of the hose-drogue and its wake at every moment in real time.

[0004] Due to the high difficulty and high risk of aerial refueling, pilots or operators are very likely to make mistakes during the docking and undocking process, resulting in refueling failure or even causing the refueling pipe to collide with the receiving aircraft, causing serious flight grade accidents and threatening flight safety. Therefore, aerial refueling simulation technology is very necessary.

[0005] However, the hose-drogue model based on finite element thinking and multi-rigid body dynamics has some assumptions and simplifications in creating and solving the HDA (Hose-Drogue Assembly) motion equations, which has led to a decrease in the simulation accuracy of the model and made the pilot experience unrealistic. In addition, the CFD (Computational Fluid Dynamics) calculation method also has the problem of excessive calculation volume due to too many grids when calculating the wake of the tanker.

[0006] The current simulation model makes simplified assumptions about the structure model and fluid of the aerial refueling hose-drogue refueling system. The main problems are:

[0007] 1) When calculating the wake field, the vortex method based on the horseshoe vortex system theory or the panel method is used to construct the wake flow field of the tanker. Compared with the computational fluid dynamics method of numerical calculation, this method does not take into account the real flow field effects caused by factors such as the tanker wing nacelle, engine jet, fuselage wake, and wake vortex diffusion and dissipation effects;

[0008] 2) The simulation method based on computational fluid dynamics (CFD) has high accuracy but large computational workload. It is difficult to meet the computational efficiency requirements of rapid design iteration and multi-parameter optimization under limited computing resources.

[0009] 3) In terms of structural dynamics modeling, the hose is discretized into a multi-rigid body structure consisting of multiple rigid small straight rods hinged together for simulation, without considering the material properties and stress distribution characteristics of the real hose;

[0010] 4) The cone sleeve is simplified as a mass point, which fails to describe its six-degree-of-freedom rigid body motion effect under the constraint of the hose;

[0011] 5) When calculating the dynamic aerodynamic force of the cone sleeve, the influence of the cone sleeve's own aerodynamic torque on its rotational motion is ignored, which reduces the simulation accuracy of the interference effect between the receiving aircraft and the cone sleeve head wave. Summary of the invention

[0012] The purpose of the present invention is to solve the problems in the prior art and propose an aerial refueling simulation method. The hose-drogue model and horseshoe vortex wake calculation model based on finite element thinking and multi-rigid body dynamics are improved, and the existing drogue sinking data and two-machine interference aerodynamic data are utilized. Not only the calculation amount of the wake field method is reduced, but also a higher simulation accuracy can be obtained, making the refueling simulation more realistic.

[0013] In order to achieve the above object, the present invention adopts the following technical scheme.

[0014] The aerial refueling simulation method comprises the following steps: performing grid division in a tanker coordinate system, calculating the distribution of the tanker wake vortex flow field within the grid division space, and generating a tanker wake flow field grid data file;

[0015] A wake model is constructed according to the wake field grid data file of the tanker, and the interference aerodynamic data of the two aircrafts are input into the wake model to obtain wake data;

[0016] A hose-drogue-sleeve combination model is established according to the wake data, the drogue-sleeve sinking amount data is obtained and the drogue-sleeve aerodynamic correction coefficient is adjusted, and the drogue-sleeve aerodynamic correction coefficient is input into the hose-drogue-sleeve combination model to generate a hose-drogue-sleeve combination model drogue-sleeve aerodynamic coefficient correction table data file.

[0017] Furthermore, the grid division is performed in the tanker coordinate system, the distribution of the tanker wake vortex flow field is calculated within the grid division space, and the grid data file of the tanker wake flow field is generated, including:

[0018] The wake calculation includes calculating the tail vortex flow field distribution of the tanker wing and saving the calculation results in the data file;

[0019] The data files include a wake field grid data file, a two-machine interference aerodynamic data file, and a cone sleeve aerodynamic coefficient correction table data file.

[0020] Further, the wake model is constructed according to the wake field grid data file of the tanker, and the aerodynamic data of the two aircraft interference is input into the wake model to obtain the wake data, which includes:

[0021] S301, calculating the relative positions of the two aircraft and the wake data of the horseshoe vortex model;

[0022] S302, searching the spatial grid where the receiving aircraft is currently located according to the relative positions of the two aircraft;

[0023] S303, judging whether the receiving aircraft is within the range of wind tunnel interference data, if so, converting the wind tunnel data into wake data and proceeding to step S305, if not, proceeding to step S304;

[0024] S304, determining whether the receiving aircraft is within the grid data range of the wake field, if it is within the grid data range, then calculating the grid data of this position and then proceeding to step S305, if it is not within the range, then outputting the horseshoe vortex model data and then proceeding to step S305;

[0025] S305: Perform data processing to generate final wake data.

[0026] Furthermore, the wake calculation includes using the Reynolds average solver to solve the wake of the tanker under different incoming flow conditions. The RANS control equation in three-dimensional integral form is:

[0027]

[0028] Where V is the volume of the control volume; S is the surface area of ​​the control volume; Q is the conserved quantity; f is a vector representing the sum of the inviscid flux and the viscous flux through the surface S; n is the external normal unit vector of the control volume surface S;

[0029] The wake model adopts an eddy viscosity model, and the eddy viscosity model adopts a two-equation Realizable k-ε model.

[0030] Furthermore, the calculation of the hose cone sleeve assembly model includes: setting the initial values ​​of the azimuth angle and the first-order differential of the segmented hose, calculating the position and velocity of the hose particle, calculating the resultant force other than the tension at the hose particle, calculating the tension matrix of the hose particle, calculating the acceleration of all the particles of the hose, calculating the second-order differential of the azimuth angle of the hose segment, integrating the first-order differential of the azimuth angle and the azimuth angle of the hose segment, judging whether the velocity and acceleration are zero, if so, terminating the model calculation, otherwise re-calculating the model.

[0031] Further, the hose-cone sleeve assembly model includes a hose reel model, a hose model and a cone sleeve model;

[0032] The hose reel model adopts a constant force spring control model, including:

[0033] T reel =T static [1-(L0-L) / L1]

[0034] Among them, T reel is the real-time tension of the hose reel, T static is the hose tension at the pod outlet position in the state of steady hose dragging before docking; L0, L and L1 are the initial length of the hose in the dragging state, the instantaneous length of the hose and the controllable length of the constant force spring respectively;

[0035] Under the control of the constant force spring, the retraction and extension acceleration of the hose is:

[0036]

[0037] Among them, T hose is the real-time tension of the hose at the pod outlet; M is the mass of the reel; Δm is the mass of the hose reeled back to the reel.

[0038] Furthermore, the hose model includes treating the hose as a number of rigid links with variable lengths connected in series, adjacent links are connected by frictionless spherical hinges, the mass and force of each link are concentrated on the hinge, and the motion law of all links under the influence of the attitude change of the tanker is obtained according to the number of links, the length of the kth link, the deflection angle of the link relative to the towing coordinate system OXY and OXZ planes, the retraction and extension speed and acceleration of the hose, and the motion equation of the hose;

[0039] According to the external forces on the hinge, including the aerodynamic resistance formed by the steady flow, the wake of the tanker and the atmospheric disturbance, as well as the bending restoring force of the hose and gravity; the internal tension of the connecting rod, the mass of the connecting rod, the mass per unit length of the connecting rod, the acceleration of the hinge and the acceleration of the adjacent hinge, and the algebraic linear equation group of the tension of the two adjacent rods are used to calculate the resultant external force of the hinge k;

[0040] The bending restoring force is calculated based on the elastic modulus of the hose material, the area moment of inertia of the hose cross section, the angle between adjacent connecting rods, the outer diameter of the hose, and the resultant external force of the hose;

[0041] The aerodynamic drag is calculated based on air density, surface friction coefficient and pressure differential drag coefficient, and the difference between the inertial velocity of the hinge node and the wake, wherein the aerodynamic drag includes surface friction and pressure differential drag.

[0042] Furthermore, the cone sleeve model includes simplifying the cone sleeve into a mass point, and the resultant external force Q acting on the cone sleeve N It is expressed as:

[0043]

[0044] Among them, m drogue is the mass of the cone sleeve; Ddrogue is the aerodynamic resistance of the drogue;

[0045] The binding force of the plug is added during the docking process:

[0046]

[0047] Where κ is the constraint coefficient; x drogue 、x drogue and z drogue is the spatial position coordinate of the cone sleeve; x probe 、x probe and z probe is the spatial position coordinate of the plug;

[0048] The aerodynamic resistance of the drogue is expressed as

[0049]

[0050] Where ρ is the air density; C drogue is the aerodynamic drag coefficient of the drogue, V N It is the difference between the inertial velocity of the drogue and the wake.

[0051] In order to achieve the above-mentioned object, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a program running on the processor, and when the processor runs the program, the steps of the aerial refueling simulation method as described above are executed.

[0052] In order to achieve the above object, the present invention also provides a computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed, the steps of the aerial refueling simulation method as described above are executed.

[0053] The present invention proposes an aerial refueling simulation method, which has the following beneficial effects:

[0054] The present invention improves the hose-cone sleeve model and the horseshoe vortex wake calculation model based on the finite element concept and multi-rigid body dynamics, adds a correction coefficient to the aerodynamic model of the cone sleeve, improves the wake calculation model, and fully utilizes the interference data of the two machines and the CFD grid file on the basis of the horseshoe vortex system theory method. By using the CFD grid data file and the wind tunnel test data file, the simulation accuracy of the refueling simulation method is improved, and the calculation amount of the CFD grid data file generation process is greatly reduced.

[0055] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0057] Figure 1 A flowchart of an aerial refueling simulation method of the present invention;

[0058] Figure 2 A schematic diagram of an aerial refueling simulation process of the present invention;

[0059] Figure 3 This is a schematic diagram of the common fuel dispenser grid division;

[0060] Figure 4 A flowchart for implementing an aerial refueling simulation solution of the present invention;

[0061] Figure 5 is a flow chart of the hose reel calculation model of the present invention;

[0062] Figure 6 It is a schematic diagram of the hose dynamics modeling of the present invention;

[0063] Figure 7 It is an approximate abstract schematic diagram of the bending of the hose of the present invention;

[0064] Figure 8 The calculation flow chart of the hose cone sleeve assembly model of the present invention;

[0065] Fig. 9 The present invention is a flowchart of the correction of the aerodynamic damping coefficient of the cone sleeve;

[0066] Fig.10 It is a schematic diagram of wake model calculation of the present invention;

[0067] Fig.11 It is a schematic diagram of the wake field calculation process of the present invention. DETAILED DESCRIPTION

[0068] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0069] Example 1

[0070] Figure 1 The following is a flow chart of the aerial refueling simulation method according to the present invention. Figure 1 , the aerial refueling simulation method of the present invention is described in detail.

[0071] In step 101, grid division is performed in the tanker coordinate system, and the distribution of the tanker wake vortex flow field is calculated within the grid division space to generate a tanker wake flow field grid data file.

[0072] Optionally, numerical simulation software is used to calculate the wake field of the tanker. Grid division and parameter setting are required during software calculation, including boundary conditions, atmospheric temperature, atmospheric pressure, Mach number, etc. The grid is divided into 1m×1m×1m in the tanker coordinate system, and the aircraft wake is calculated in the entire space range of 600m×20m×20m, where the X axis is (0,-600)m, the Y axis is (-10,10)m, and the Z axis is (0,-20)m.

[0073] Optionally, the wake CFD calculation is used to calculate the tail vortex flow field distribution of the tanker wing, and the calculation results are saved in a data file.

[0074] Optionally, the data file includes a wake field grid data file, a two-machine interference aerodynamic data file, and a drogue aerodynamic coefficient correction table data file. The data file is read into the memory when the model is initialized, and is used to correct the currently used calculation model to obtain higher calculation accuracy.

[0075] In this embodiment, Figure 3 As shown in the figure, the meshing module of ANSYS software is used to divide the mesh of the tanker, and the mesh uses structured hexahedron. Figure 3 It can be seen that the smaller the grid division, the more accurate the calculated data, but the number of grids is also greater, resulting in a large amount of CFD calculation. The two-machine interference aerodynamic data file in this embodiment provides wake field related data within a certain refueling range, and the wake data at a long distance can be calculated by the horseshoe vortex model, which can greatly reduce the number of grid divisions of the refueling machine. Since the wake model used in this embodiment uses the two-machine interference data and CFD grid data in the medium and short distance range of the refueling process, the model has higher calculation accuracy than the pure horseshoe vortex model.

[0076] In this embodiment, Figure 4 As shown in the figure, the data files used in the model calculation process include the two-machine interference aerodynamic data file obtained through wind tunnel tests, the grid data file obtained through CFD calculations, and the drogue aerodynamic coefficient correction table data file. The two-machine interference aerodynamic data file is the aerodynamic coefficient data file of the receiving aircraft under the influence of wake, which can be used to calculate the wake at the receiving aircraft. This file is used together with the grid data file obtained through CFD calculations to calculate the wake of the tanker.

[0077] Optionally, the wake CFD calculation process is as follows Fig.11The wake CFD calculation uses the RANS (Reynolds Average Navier-Stokes) solver to solve the wake of the tanker under different incoming flow conditions. The RANS control equation in three-dimensional integral form is:

[0078]

[0079] Where V is the volume of the control volume; S is the surface area of ​​the control volume; Q is the conserved quantity; f is a vector representing the sum of the inviscid flux and the viscous flux through the surface S; and n is the external normal unit vector of the surface S of the control volume.

[0080] The wake model adopts the eddy viscosity model, which uses a two-equation Realizable k-ε model, and the calculation results of the model are more accurate.

[0081] The above process uses ANSYS finite element analysis software to complete the calculation, which requires the use of the software's model design module (DesignModeler), meshing module (ICEM CFD, MESHING), flow field calculation module (FLUENT) and post-processing module (RESULTS).

[0082] In the tanker coordinate system, the aircraft wake is calculated within a spatial range of 600m×20m×20m, where the X axis is (0,-600)m, the Y axis is (-10,10)m, and the Z axis is (0,-20)m. The wake distribution under the Mach flow conditions of 0.5, 0.6, 0.7, and 0.76 is calculated, and the obtained wake data is stored in a file. Since the wind tunnel interference data is used within the spatial range of the X axis (0,-100)m, the Y axis (-10,10)m, and the Z axis (0,-20)m, a larger grid can be used to reduce the amount of CFD calculations. The present invention uses a hexahedral grid of 1m×1m×1m in size.

[0083] In step 102, a wake model is constructed based on the wake field grid data file of the tanker, and the aerodynamic data of the interference between the two machines is input into the wake model to obtain the wake data; a hose-drogue assembly model is established based on the wake data, the drogue sinking amount data is obtained and the drogue aerodynamic correction coefficient is adjusted, and the drogue aerodynamic correction coefficient is input into the hose-drogue assembly model to generate a hose-drogue assembly model drogue aerodynamic coefficient correction table data file.

[0084] Optionally, by continuously adjusting the HDA model cone sleeve aerodynamic model correction coefficient, the simulated cone sleeve sinking amount data is made consistent with the test data, and a final HDA model cone sleeve aerodynamic coefficient correction table data file is formed.

[0085] In this embodiment, the HDA model includes a hose reel model, a hose model and a cone sleeve model, and its main function is to simulate and calculate the dynamic characteristics of the hose retraction, extension and docking process.

[0086] Optionally, the reel model adopts a constant force spring control model, the principle of which is as follows:

[0087] T reel =T static [1-(L0-L) / L1]

[0088] Where, T reel is the real-time tension of the hose reel, T static is the hose tension at the pod outlet under the steady hose dragging state before docking; L0, L and L1 are the initial length of the hose in the dragging state, the instantaneous length of the hose and the controllable length of the constant force spring, respectively.

[0089] Under the control of the constant force spring, the retraction and extension acceleration of the hose is:

[0090]

[0091] Where, T hose is the real-time tension of the hose at the pod outlet; M is the mass of the reel; Δm is the mass of the hose reeled back to the reel.

[0092] The calculation model of the hose reel is as follows Figure 5 As shown, after calculating the hose retraction and extension acceleration, the hose retraction and extension speed can be obtained by integration.

[0093] In this embodiment, Figure 6 As shown in the hose dynamics modeling, the hose is abstracted into several rigid links with variable lengths in series. Adjacent links are connected by frictionless spherical hinges, and the mass and force of each link are concentrated on the hinge. The damping of the hose material, linear elasticity, torsional motion around the axis, and fuel pulsation are not considered.

[0094] Optionally, (1) the equation of motion of the hose includes:

[0095] The position vector of the hinge node k in the drag system can be expressed as follows:

[0096]

[0097] Where N is the number of connecting rods, l k is the length of the kth connecting rod, θ k and φ k It represents the deflection angle of the connecting rod relative to the OXY and OXZ planes of the dragging coordinate system.

[0098] The velocity and acceleration of the hinge relative to the drag system are calculated as follows:

[0099]

[0100] Differentiate the above formula to get

[0101]

[0102] In the formula and are the retraction and extension speed and acceleration of the hose respectively. The mass of each connecting rod is small and changes slowly, so the above formula ignores the additional acceleration caused by the mass change.

[0103] By definition

[0104]

[0105] From this we can get

[0106]

[0107] The above equation is the general motion equation of the connecting rod. Through cyclic iteration, the motion law of all connecting rods under the influence of the tanker posture change can be obtained.

[0108] (2) The dynamic equations of the hose include:

[0109] According to Newton's second law, the acceleration a of the hinge k is k for

[0110] α k =(Q k +t k -t k-1 ) / m k

[0111] In the formula, Q k The external force on the hinge k includes the aerodynamic resistance formed by the steady flow, the wake of the tanker and the atmospheric disturbance, as well as the bending restoring force of the hose and gravity; t k is the internal tension of the k-node connecting rod; m k =μl k is the mass of the k-node connecting rod, and μ is the mass per unit length of the k-node connecting rod.

[0112] The acceleration relationship between adjacent hinges can be expressed as

[0113]

[0114] Further, we can obtain the algebraic linear equations of the tension between two adjacent rods:

[0115]

[0116] Since each section of the hose is of equal length, the above formula can be simplified to

[0117]

[0118] It can be expressed in matrix form as

[0119]

[0120] (3) Resultant external force of the hose

[0121] The resultant external force Q on hinge k k for

[0122]

[0123] The hose bending is abstracted as follows Figure 7 Two adjacent connecting rods are shown.

[0124] The bending restoring force can be calculated as follows:

[0125]

[0126] Where, E is the elastic modulus of the hose material; I is the area moment of inertia of the hose cross section; γ is the angle between adjacent connecting rods; d0, d i are the outer and inner diameters of the hose respectively.

[0127] Aerodynamic drag D k Including surface friction and pressure resistance:

[0128]

[0129] Where ρ is the air density; c t,k and c n,k are the surface friction coefficient and the pressure difference resistance coefficient, V k is the difference between the inertial velocity of the hinge node k and the wake.

[0130] Alternatively, in the cone sleeve model, the cone sleeve is generally simplified as a mass point, and the resultant external force Q acting on the cone sleeve is N It can be expressed as:

[0131]

[0132] In the formula, m drogue is the mass of the cone sleeve; D drogue is the aerodynamic resistance of the cone sleeve.

[0133] The docking process also requires the binding force of the plug:

[0134]

[0135] Where κ is the constraint coefficient; x drogue 、x drogue and zdrogue is the spatial position coordinate of the cone sleeve; x probe 、x probe and z probe is the spatial position coordinate of the plug.

[0136] The aerodynamic resistance of the drogue can be expressed as:

[0137]

[0138] Where ρ is the air density; C drogue is the aerodynamic drag coefficient of the drogue, V N It is the difference between the inertial velocity of the drogue and the wake.

[0139] The HDA model calculation process is as follows Figure 8 shown.

[0140] In this embodiment, the aerodynamic parameters of the cone sleeve are corrected using the cone sleeve aerodynamic coefficient correction table data file to improve the calculation accuracy of the model.

[0141] Corrected C drogue ′ It is expressed by the following formula.

[0142]

[0143] Where interp2D is a two-dimensional interpolation function; h0, v0, data are the required height and speed for interpolation and the corresponding two-dimensional drogue aerodynamic coefficient correction table data; h and v are the current height and speed of the receiving aircraft.

[0144] The correction process of the cone sleeve aerodynamic damping coefficient is as follows: Fig. 9 As shown, the cone sleeve sinking data is shown in the following Table 1.

[0145] Table 1 Example of cone sleeve sinking data

[0146]

[0147] Optionally, the wake model includes a horseshoe vortex calculation model for the tanker wake field and wake field data generation. The horseshoe vortex calculation model can be used to calculate the wake data of the tanker in any scale range. The wake field grid data file and the two-machine interference aerodynamic data file input by the model can correct the wake data calculated by the model within a limited scale range to improve the simulation accuracy of the wake. The tanker wake field data generation module first converts the two-machine interference aerodynamic data into wake data, and then combines the wake field grid data and the horseshoe vortex model calculation data to obtain the final wake data.

[0148] As an example, the wake model first calculates the real-time wake data at the current position of the receiving aircraft based on the horseshoe vortex model, and then searches for the current position of the receiving aircraft. If the receiving aircraft is within the acquisition range of the two-machine interference data file, the two-machine interference data file data is converted into wake data output; if the receiving aircraft is outside the acquisition range of the two-machine interference data file, but within the CFD grid data range, the CFD grid wake data is output; if the receiving aircraft is neither within the acquisition range of the two-machine interference data file nor within the CFD grid data range, the horseshoe vortex model is output to calculate the wake data.

[0149] In this embodiment, since the accuracy of wind tunnel test data and CFD calculation data is higher than that of the horseshoe vortex calculation model, the method of this embodiment can obtain higher calculation accuracy than the horseshoe vortex calculation model.

[0150] Optionally, the wake model calculation process is as follows Fig.10 As shown, including:

[0151] Step (1), calculating the relative positions of the two aircraft and the wake data of the horseshoe vortex model;

[0152] Step (2), searching the spatial grid where the receiving aircraft is currently located according to the relative positions of the two aircraft;

[0153] Step (3), determine whether the receiving aircraft is within the range of wind tunnel interference data (X axis (0, -100) m, Y axis (-10, 10) m, Z axis (0, -20) m). If it is within the range of wind tunnel interference data, convert the wind tunnel data into wake data and proceed to step (5); if it is not within the range, proceed to step (4);

[0154] Step (4), determine whether the receiving machine is within the CFD grid data range (X axis (-100, -600) m, Y axis (-10, 10) m, Z axis (0, -20) m). If it is within the grid data range, calculate the grid data of this position and then enter step (5). If it is not within the range, output the horseshoe vortex model data and then enter step 5;

[0155] Step (5), data processing, generating the final wake data.

[0156] Optionally, the horseshoe vortex model includes that the horseshoe vortex is composed of an attached vortex and a tail vortex, and the wake at any position in space can be represented by the induced composite velocity of the two. The calculation model is as follows:

[0157] The velocity field induced by the attached vortex is:

[0158]

[0159] Where Γ0 is the initial strength of the tail vortex, Γ0=2C LVS / πb; V is the incoming flow velocity, S is the wing reference area, b is the span; y s =b / 2 is the half-length; C L is the lift coefficient.

[0160] The velocity field induced by the trailing vortex is:

[0161]

[0162] The total induced velocity of the horseshoe vortex system is

[0163]

[0164] Optionally, the CFD mesh data file format in mesh data processing is shown in Table 2 below.

[0165] Table 2 Grid data example

[0166] X(m) Y(m) Z(m) V(m / s) -10 0 0 10.446 -20 0 0 10.448

[0167] After calculating the relative position of the two aircraft, the wake data at the current position is obtained by looking up the table.

[0168] Optionally, the file format of the two-machine interference aerodynamic data in interference data processing is shown in Table 3 below.

[0169] Table 3 Examples of aerodynamic data of two aircraft interference

[0170] <![CDATA[M a ]]> X(m) Y(m) Z(m) Cx Cy C Mx My Mz Δα Δβ 0.5 -10 0 0 0.022 0.0008 0.09 -0.0006 0.07 0.0004 -0.06 0.1

[0171] Among them, Δα is the angle of attack of the receiving aircraft under the influence of the wake, and Δβ is the sideslip angle of the receiving aircraft under the influence of the wake.

[0172] The angle of attack calculation formula is as follows:

[0173]

[0174] Among them, α is the angle of attack, u is the forward velocity of the aircraft system, and w is the downward velocity of the aircraft system.

[0175]

[0176] Among them, β is the sideslip angle, u is the forward speed of the aircraft system, v is the right speed of the aircraft system, and w is the downward speed of the aircraft system.

[0177] By combining the above two formulas, we can get the speed of the receiving aircraft at the current Mach number, and then the wake can be calculated according to the following formula.

[0178]

[0179] Among them, u w is the forward wake velocity of the aircraft system, v wis the right wake velocity of the aircraft system, w w is the downward wake velocity of the aircraft system, c is the local speed of sound, M a is the Mach number.

[0180] The invention proposes an aerial refueling simulation method, which improves the hose-cone sleeve model and the horseshoe vortex wake calculation model based on the finite element concept and multi-rigid body dynamics, and improves the simulation accuracy of the refueling simulation method by using CFD grid data files and wind tunnel test data files, and greatly reduces the calculation amount of the CFD grid data file generation process.

[0181] Those skilled in the art can understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for simulating aerial refueling, characterized in that: include: Grid division is performed in the tanker coordinate system, and the distribution of the tanker wake vortex flow field is calculated within the grid division space to generate a tanker wake flow field grid data file; A wake model is constructed according to the wake field grid data file of the tanker, and the interference aerodynamic data of the two aircrafts are input into the wake model to obtain wake data; A hose-drogue-sleeve combination model is established according to the wake data, the drogue-sleeve sinking amount data is obtained and the drogue-sleeve aerodynamic correction coefficient is adjusted, and the drogue-sleeve aerodynamic correction coefficient is input into the hose-drogue-sleeve combination model to generate a hose-drogue-sleeve combination model drogue-sleeve aerodynamic coefficient correction table data file.

2. The aerial refueling simulation method according to claim 1, characterized in that: The grid division is performed in the tanker coordinate system, and the distribution of the tanker wake vortex flow field is calculated within the grid division space range, and the grid data file of the tanker wake flow field is generated, including: The wake calculation includes calculating the tail vortex flow field distribution of the tanker wing and saving the calculation results in the data file; The data files include a wake field grid data file, a two-machine interference aerodynamic data file, and a cone sleeve aerodynamic coefficient correction table data file.

3. The aerial refueling simulation method according to claim 2, characterized in that: The step of constructing a wake model according to the wake field grid data file of the tanker and inputting the interference aerodynamic data of the two aircraft into the wake model to obtain the wake data comprises: S301, calculating the relative positions of the two aircraft and the wake data of the horseshoe vortex model; S302, searching the spatial grid where the receiving aircraft is currently located according to the relative positions of the two aircraft; S303, judging whether the receiving aircraft is within the range of wind tunnel interference data, if so, converting the wind tunnel data into wake data and proceeding to step S305, if not, proceeding to step S304; S304, judging whether the receiving aircraft is within the grid data range of the wake field, if it is within the grid data range, then calculating the grid data of this position and then proceeding to step S305, if it is not within the range, then outputting the horseshoe vortex model data and then proceeding to step S305; S305: Perform data processing to generate final wake data.

4. The aerial refueling simulation method according to claim 1, characterized in that: The wake calculation includes using the Reynolds average solver to solve the wake of the tanker under different incoming flow conditions. The RANS control equation in three-dimensional integral form is: Where V is the volume of the control volume; S is the surface area of ​​the control volume; Q is the conserved quantity; f is a vector representing the sum of the inviscid flux and the viscous flux through the surface S; n is the external normal unit vector of the control volume surface S; The wake model adopts an eddy viscosity model, and the eddy viscosity model adopts a two-equation Realizable k-ε model.

5. The aerial refueling simulation method according to claim 1, characterized in that: The hose cone sleeve assembly model calculation includes: setting the initial values ​​of the azimuth angle and the first-order differential of the segmented hose, calculating the position and velocity of the hose mass point, calculating the resultant force other than the tension at the hose mass point, calculating the hose mass point tension matrix, calculating the acceleration of all the hose mass points, calculating the second-order differential of the azimuth angle of the hose segment, integrating the first-order differential of the azimuth angle and the azimuth angle of the hose segment, judging whether the velocity and acceleration are zero, if so, terminating the model calculation, otherwise, re-calculating the model.

6. The aerial refueling simulation method according to claim 1 or 5, characterized in that: The hose-cone-sleeve assembly model includes a hose reel model, a hose model and a cone-sleeve model; The hose reel model adopts a constant force spring control model, including: T reel =T static [1-(L0-L) / L1] Among them, T reel is the real-time tension of the hose reel, T static is the hose tension at the pod outlet position in the state of steady hose dragging before docking; L0, L and L1 are the initial length of the hose in the dragging state, the instantaneous length of the hose and the controllable length of the constant force spring respectively; Under the control of the constant force spring, the retraction and extension acceleration of the hose is: Among them, T hose is the real-time tension of the hose at the pod outlet; M is the mass of the reel; Δm is the mass of the hose reeled back to the reel.

7. The aerial refueling simulation method according to claim 6, characterized in that: The hose model includes treating the hose as a number of rigid links with variable lengths in series, with adjacent links connected by frictionless spherical hinges, with the mass and force of each link concentrated on the hinge, and obtaining the motion law of all links under the influence of the attitude change of the tanker according to the number of links, the length of the kth link, the deflection angle of the link relative to the plane of the towing coordinate system OXY and OXZ, the retraction and extension speed and acceleration of the hose, and the motion equation of the hose; The resultant external force of hinge k is calculated based on the external forces on the hinge, including the aerodynamic resistance formed by the steady flow, the tanker wake and the atmospheric disturbance, as well as the bending restoring force of the hose and gravity, the internal tension of the connecting rod, the mass of the connecting rod, the mass per unit length of the connecting rod, the acceleration of the hinge and the acceleration of the adjacent hinge, and the algebraic linear equation system of the tension of the two adjacent rods; The bending restoring force is calculated based on the elastic modulus of the hose material, the area moment of inertia of the hose cross section, the angle between adjacent connecting rods, the outer diameter of the hose, and the resultant external force of the hose; The aerodynamic drag is calculated based on air density, surface friction coefficient and pressure differential drag coefficient, and the difference between the inertial velocity of the hinge node and the wake, wherein the aerodynamic drag includes surface friction and pressure differential drag.

8. The aerial refueling simulation method according to claim 6, characterized in that: The cone sleeve model includes simplifying the cone sleeve into a mass point, and the resultant external force Q acting on the cone sleeve N It is expressed as: Among them, m drogue is the mass of the cone sleeve; D drogue is the aerodynamic resistance of the drogue; The binding force of the plug is added during the docking process: Where κ is the constraint coefficient; x drogue 、x drogue and z drogue is the spatial position coordinate of the cone sleeve; x probe 、x probe and z probe is the spatial position coordinate of the plug; The aerodynamic resistance of the drogue is expressed as Where ρ is the air density; C drogue is the aerodynamic drag coefficient of the drogue, V N It is the difference between the inertial velocity of the drogue and the wake.

9. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a program running on the processor, and the processor executes an aerial refueling simulation method according to any one of claims 1 to 8 when running the program.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed, an aerial refueling simulation method as described in any one of claims 1 to 8 is executed.

Images