CN114330080B - Prediction method for aircraft surface-symmetric cross-basin flow field - Google Patents

Prediction method for aircraft surface-symmetric cross-basin flow field Download PDF

Info

Publication number
CN114330080B
CN114330080B CN202210207936.6A CN202210207936A CN114330080B CN 114330080 B CN114330080 B CN 114330080B CN 202210207936 A CN202210207936 A CN 202210207936A CN 114330080 B CN114330080 B CN 114330080B
Authority
CN
China
Prior art keywords
velocity
flow field
grid
aircraft
virtual point
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210207936.6A
Other languages
Chinese (zh)
Other versions
CN114330080A (en
Inventor
王沛
江定武
李锦�
黎昊旻
郭勇颜
万钊
毛枚良
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Computational Aerodynamics Institute of China Aerodynamics Research and Development Center
Original Assignee
Computational Aerodynamics Institute of China Aerodynamics Research and Development Center
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Computational Aerodynamics Institute of China Aerodynamics Research and Development Center filed Critical Computational Aerodynamics Institute of China Aerodynamics Research and Development Center
Priority to CN202210207936.6A priority Critical patent/CN114330080B/en
Publication of CN114330080A publication Critical patent/CN114330080A/en
Application granted granted Critical
Publication of CN114330080B publication Critical patent/CN114330080B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Aerodynamic Tests, Hydrodynamic Tests, Wind Tunnels, And Water Tanks (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a method for predicting a cross-basin flow field with symmetrical aircraft surface, which relates to the field of cross-basin flow field simulation and comprises the following steps: performing flow field solution based on a first physical space grid corresponding to the aircraft and the inflow conditions to obtain speed and temperature information of the flow field; generating a three-dimensional speed space grid, setting the grid range of the three-dimensional speed space grid based on an outer boundary to obtain a three-dimensional hemispherical area, obtaining a hemispherical encryption area and a spherical encryption area, generating a hemispherical speed space grid based on grid spacing distribution information, the hemispherical encryption area and the spherical encryption area, and symmetrically copying the hemispherical speed space grid to obtain a spherical speed space grid; performing iterative solution on the basis of the first physical space grid and the spherical three-dimensional velocity space grid to obtain a three-dimensional physical space flow field of the aircraft; the method realizes the rapid prediction of the aircraft surface-symmetric cross-basin flow field.

Description

Prediction method for aircraft surface-symmetric cross-basin flow field
Technical Field
The invention relates to the field of cross-basin flow field simulation, in particular to a prediction method of an aircraft surface-symmetric cross-basin flow field.
Background
With the development of adjacent space aircrafts, cross-flow-area flow fields with continuous flow and thin flow coexisting are more and more common, which are generally solved by NS/DSMC zone overlapping or Boltzmann equation at present, but the selection of continuity failure parameters and the judgment process of interfaces are more complicated in the former, and the latter is rapidly developed in recent years due to the fact that the same control equation is adopted in a plurality of flow areas. Xu et al propose a Unified Gas dynamics Scheme (UGKS) that couples particle collision and migration processes and achieves automatic transition of equations between continuous and dilute flows by adjusting relaxation time, and this method is widely used in full-flow-domain full-speed-domain flow prediction, such as multiple physical flows, turbulence simulation, etc. However, the method brings huge calculation cost due to the fact that the method is dispersed in a physical space and a speed space simultaneously.
To improve computational efficiency, many optimization techniques have emerged for velocity space grids, such as cartesian grid adaptation, unstructured grids, and the like. In comparison, the unstructured grid program is simpler to implement, the far-field boundary can be any shape, and the encryption of a designated area is easy to perform, so that the unstructured grid program is favored by many scholars. A common aircraft model is generally a plane-symmetric shape (the plane of symmetry is typically the z =0 plane), and the spatial flow is also plane-symmetric when the incoming flow does not sideslip. In the numerical simulation process, the flow field of the half-mode aircraft is calculated only by adopting a symmetric boundary condition on a symmetric plane, and then the result of the full flow field is obtained through the symmetric boundary. The half-mold calculation method can reduce about half of calculated amount and memory, and is a common method for predicting the plane symmetric flow field of the aircraft with the complex plane symmetric appearance in engineering. However, in the UGKS algorithm, the unstructured velocity space grid generated by the conventional method often cannot ensure the plane symmetry of the grid, so that the processing of distribution functions in symmetric boundaries is very complex, and interpolation processing is required in most cases, which affects the calculation accuracy. In order to avoid complex symmetrical boundary processing and ensure calculation accuracy, even if the surface-symmetrical flow field simulation with a surface-symmetrical appearance is adopted, a plurality of researchers directly carry out cross-basin flow field simulation on the full-mode aircraft, and the waste of calculation resources is caused.
Disclosure of Invention
The invention aims to realize rapid prediction of a plane-symmetric cross-basin flow field of an aircraft.
In order to achieve the above object, the present invention provides a method for predicting a cross-basin flow field with plane symmetry of an aircraft, where the method includes:
step 1: the method comprises the steps of obtaining overall dimension information of an aircraft, wherein the aircraft is a plane-symmetric aircraft, constructing a first model corresponding to the aircraft based on the overall dimension information of the aircraft, cutting half of the first model to obtain a second model, and generating a first physical space grid based on the second model;
step 2: performing flow field solution based on the first physical space grid and the inflow conditions to obtain the speed and temperature information of the flow field, determining a first position corresponding to a temperature lowest point according to the flow field temperature information, and marking the speeds of the first position in the x direction, the y direction and the z direction as follows:
Figure 100002_DEST_PATH_IMAGE001
、
Figure 746792DEST_PATH_IMAGE002
and
Figure 100002_DEST_PATH_IMAGE003
；
and step 3: generating a three-dimensional velocity space grid, generating an outer boundary of the three-dimensional velocity space grid based on the incoming flow condition, and aligning the three-dimensional velocity space grid based on the outer boundary
Figure 460670DEST_PATH_IMAGE004
、
Figure 100002_DEST_PATH_IMAGE005
And
Figure 974828DEST_PATH_IMAGE006
the grid ranges in three directions are arranged to obtain a three-dimensional hemispherical area,
Figure 714245DEST_PATH_IMAGE004
、
Figure 731880DEST_PATH_IMAGE005
and
Figure 199682DEST_PATH_IMAGE006
the grid spacing increases in equal proportion from the origin of coordinates in three directions. With origin of coordinates (
Figure 100002_DEST_PATH_IMAGE007
，
Figure 60191DEST_PATH_IMAGE008
，
Figure 100002_DEST_PATH_IMAGE009
) Macroscopic velocity corresponding to the lowest point of temperature: (
Figure 727932DEST_PATH_IMAGE010
，
Figure 100002_DEST_PATH_IMAGE011
，
Figure 944281DEST_PATH_IMAGE012
) The part is the sphere center, a hemispherical encryption area and a spherical encryption area are respectively arranged, the radius of the hemisphere and the radius of the sphere are determined by the size of the local temperature, and the radius is larger when the temperature is lower. And generating a hemispherical speed space grid based on the constraint conditions. Relating the hemispherical grid to
Figure 203224DEST_PATH_IMAGE009
Symmetrically copying the plane to obtain a spherical speed space grid;
and 4, step 4: and carrying out iterative solution on the basis of the first physical space grid and the spherical three-dimensional velocity space grid to obtain the three-dimensional physical space flow field of the aircraft.
The method comprises the following steps: according to the method, the velocity space grid with the plane symmetry characteristic is generated through the local encryption and plane symmetry methods of the velocity space grid, and then the distribution function symmetric boundary conditions are combined, and the half-mode aircraft is adopted for calculation, so that the rapid prediction of the plane symmetry cross-basin flow field is realized.
Preferably, the first model is symmetrical about a z =0 plane in a three-dimensional physical space in which the x-axis, the y-axis and the z-axis are located.
Preferably, in step 2 of the method, an NS solver is used to solve the flow field. The NS solver can be used for realizing rapid and accurate solution of the flow field.
Preferably, the incoming flow conditions in the method are as follows: density of incoming flow
Figure 100002_DEST_PATH_IMAGE013
Speed of incoming flow in x direction
Figure 754291DEST_PATH_IMAGE014
Y-direction upward flow velocity
Figure 100002_DEST_PATH_IMAGE015
Velocity of incoming flow in z-direction
Figure 802888DEST_PATH_IMAGE016
And pressure of incoming flow
Figure 100002_DEST_PATH_IMAGE017
。
Preferably, in the method, the three-dimensional velocity space grid is based on the outer boundary
Figure 388590DEST_PATH_IMAGE004
、
Figure 84013DEST_PATH_IMAGE005
And
Figure 669847DEST_PATH_IMAGE006
the grid ranges in three directions are set, including: gridding the three-dimensional velocity space in
Figure 413812DEST_PATH_IMAGE018
The grid range of the direction is set to be greater than or equal to
Figure 100002_DEST_PATH_IMAGE019
And is less than or equal to
Figure 854020DEST_PATH_IMAGE020
Wherein, in the step (A),
Figure 100002_DEST_PATH_IMAGE021
is a mode of the incoming flow velocity,
Figure 297509DEST_PATH_IMAGE006
the grid range of the direction is set to be greater than or equal to
Figure 229693DEST_PATH_IMAGE019
And is less than or equal to 0.
Preferably, the iterative solution is performed by using a unified gas dynamics method in step 4 of the method. The method adopts a unified gas dynamics method to carry out iterative solution, can quickly and accurately realize the flow field simulation of the half-mode aircraft, and further can quickly and accurately calculate to obtain the three-dimensional space flow field.
Preferably, the step 4 in the method specifically includes: and carrying out iterative solution on the three-dimensional physical space grid and points in the three-dimensional velocity space grid based on the first physical space grid and the spherical three-dimensional velocity space grid, and processing related boundaries to obtain the three-dimensional physical space flow field of the aircraft.
Preferably, step 1 of the method further comprises: symmetric boundary conditions are specified, and the processing of the relevant boundary in step 4 comprises processing the symmetric boundary.
Preferably, the processing the symmetric boundary in the method includes: setting the macroscopic quantity of the first virtual point and the second virtual point in the symmetric boundary condition and setting the distribution function of the first virtual point and the second virtual point;
wherein, the macroscopic quantity of the first virtual point and the second virtual point in the symmetric boundary condition is set as:
Figure 574086DEST_PATH_IMAGE022
，
Figure 100002_DEST_PATH_IMAGE023
，
Figure 665539DEST_PATH_IMAGE024
，
Figure 100002_DEST_PATH_IMAGE025
，
Figure 984656DEST_PATH_IMAGE026
，
Figure 100002_DEST_PATH_IMAGE027
，
Figure 404136DEST_PATH_IMAGE028
，
Figure 100002_DEST_PATH_IMAGE029
，
Figure 145696DEST_PATH_IMAGE030
，
Figure 100002_DEST_PATH_IMAGE031
；
Figure 967022DEST_PATH_IMAGE032
is the density at the first virtual point and,
Figure 100002_DEST_PATH_IMAGE033
is the density at the first interior point,
Figure 549050DEST_PATH_IMAGE034
is the density at the second virtual point and,
Figure 100002_DEST_PATH_IMAGE035
is the density at the second interior point,
Figure 721406DEST_PATH_IMAGE036
is the velocity in the x direction at the first virtual point,
Figure 100002_DEST_PATH_IMAGE037
is the velocity in the x-direction at the first interior point,
Figure 689493DEST_PATH_IMAGE038
is the speed in the x direction at the second virtual point,
Figure 100002_DEST_PATH_IMAGE039
is the velocity in the x-direction at the second interior point,
Figure 530105DEST_PATH_IMAGE040
is the velocity in the y direction at the first virtual point,
Figure 100002_DEST_PATH_IMAGE041
is the velocity in the y-direction at the first interior point,
Figure 502609DEST_PATH_IMAGE042
is the velocity in the y direction at the second virtual point,
Figure 100002_DEST_PATH_IMAGE043
is the velocity in the y-direction at the second interior point,
Figure 37626DEST_PATH_IMAGE044
is the velocity in the z direction at the first virtual point,
Figure 100002_DEST_PATH_IMAGE045
is the velocity in the z direction at the first interior point,
Figure 996355DEST_PATH_IMAGE046
is the velocity in the z direction at the second virtual point,
Figure 100002_DEST_PATH_IMAGE047
is the velocity in the z direction at the second interior point,
Figure 775961DEST_PATH_IMAGE048
is the pressure at the first virtual point and,
Figure 100002_DEST_PATH_IMAGE049
is the pressure at the first interior point,
Figure 857050DEST_PATH_IMAGE050
is the pressure at the second virtual point and,
Figure 100002_DEST_PATH_IMAGE051
is the pressure at the second interior point;
the distribution function of the first virtual point and the second virtual point is set as:
Figure 738418DEST_PATH_IMAGE052
；
Figure 100002_DEST_PATH_IMAGE053
；
wherein f is a distribution function defined in a three-dimensional physical space and a three-dimensional velocity space in the unified gas dynamics method, the first virtual point is symmetrical with the first interior point about the symmetrical boundary, and the second virtual point is symmetrical with the second interior point about the symmetrical boundary.
The density, speed, pressure and distribution functions on two sides of the symmetric boundary can meet the physical fact of mirror symmetry through the arrangement, and the iterative solution of the step 4 can obtain a correct space flow field result.
Preferably, the processing of the relevant boundary in step 4 of the method further includes processing a fixed wall boundary, an incoming flow boundary, and an outgoing flow boundary.
One or more technical schemes provided by the invention at least have the following technical effects or advantages:
the invention encrypts the designated area of the velocity space unstructured grid based on the flow field calculation result, then generates the plane symmetric velocity space grid, and combines the symmetric boundary processing of the distribution function to realize the rapid prediction of the aircraft cross-flow field plane symmetric flow field. According to the method, local grid encryption is performed, so that the grid quantity is reduced, the calculation time is reduced, and the prediction of the method is quicker; the plane symmetric shape is calculated by adopting an aircraft half-mold, so that the calculated amount is reduced by half; the invention adopts the symmetric processing of the velocity space grid, facilitates the search of the velocity space symmetric points in the symmetric boundary and avoids the complex and fussy interpolation calculation process.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention;
FIG. 1 is a schematic flow chart of a prediction method of an aircraft surface-symmetric cross-basin flow field;
FIG. 2 is a schematic view of a scaled model of an X38-like aircraft;
FIG. 3 is a grid schematic of the entire velocity space;
FIG. 4 is a velocity space grid
Figure 874739DEST_PATH_IMAGE007
A sectional view;
FIG. 5 is a velocity space grid
Figure 259584DEST_PATH_IMAGE008
A sectional view;
FIG. 6 is a velocity space grid
Figure 714836DEST_PATH_IMAGE009
A sectional view;
fig. 7 is a schematic diagram of symmetric boundary processing.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflicting with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced otherwise than as specifically described and thus the scope of the present invention is not limited by the specific embodiments disclosed below.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for predicting a planar symmetric cross-basin flow field of an aircraft, an embodiment of the present invention provides a method for predicting a planar symmetric cross-basin flow field of an aircraft, where the method includes:
step 1: the method comprises the steps of obtaining overall dimension information of an aircraft, wherein the aircraft is a plane-symmetric aircraft, constructing a first model corresponding to the aircraft based on the overall dimension information of the aircraft, cutting half of the first model to obtain a second model, and generating a first physical space grid based on the second model; for a certain plane-symmetric shape aircraft (assuming that an aircraft model is symmetric about a z =0 plane, a coordinate system of a three-dimensional physical space is composed of three coordinate axes (x, y and z) which are perpendicular to each other, and z is a third coordinate axis), a physical space grid is generated for the half-model shape of the aircraft by adopting commercial software, wherein the commercial software can be Gridgen software, ICEM software or other software capable of generating the physical space grid.
And 2, step: based on the physical space grid, a specified incoming flow condition is adopted (the incoming flow condition comprises the following parameters of incoming flow density
Figure 208134DEST_PATH_IMAGE013
Speed of incoming flow in x direction
Figure 384032DEST_PATH_IMAGE014
Y-direction upward flow velocity
Figure 951279DEST_PATH_IMAGE015
Velocity of incoming flow in z-direction
Figure 515116DEST_PATH_IMAGE016
And pressure of incoming flow
Figure 744978DEST_PATH_IMAGE017
) And solving the flow field by using an NS solver to obtain macroscopic conservation quantities such as the speed, the temperature and the like of the flow field. Determining the position of the lowest temperature point according to the temperature distribution condition and marking the macroscopic velocity value of the position (
Figure 380358DEST_PATH_IMAGE001
，
Figure 474216DEST_PATH_IMAGE002
，
Figure 599167DEST_PATH_IMAGE003
). The NS solver calculation method can be found in the following documents: method for super-Yan, computing hydrodynamics and application]Beijing: beijing university of aerospace publisher, 2006. Other solvers may also be used in this embodiment, and the specific name and type of the solver are not limited in the embodiment of the present invention.
And step 3: an unstructured velocity space grid is generated using commercial software. The commercial software may be gridggen software, ICEM software, or other software capable of generating a physical space grid, and the type of software for generating the physical space grid is not particularly limited by the invention. The three directions of the three-dimensional velocity space grid are respectively
Figure 286632DEST_PATH_IMAGE004
、
Figure 725703DEST_PATH_IMAGE005
And
Figure 205226DEST_PATH_IMAGE006
. To facilitate symmetric boundary processing (see below for details), a velocity space grid is set with respect to
Figure 501078DEST_PATH_IMAGE009
Plane symmetry. According to the characteristics of distribution functionWill be a velocity space
Figure 862789DEST_PATH_IMAGE018
The grid range of the direction is set as
Figure 777656DEST_PATH_IMAGE054
. Wherein
Figure 908423DEST_PATH_IMAGE021
Is the mode of the incoming flow velocity.
Figure 692620DEST_PATH_IMAGE006
The direction is set as
Figure 744890DEST_PATH_IMAGE019
,0). Forming a three-dimensional hemispherical region.
Figure 260185DEST_PATH_IMAGE004
、
Figure 324087DEST_PATH_IMAGE005
And
Figure 102687DEST_PATH_IMAGE006
the grid spacing increases in equal proportion from the origin of coordinates in three directions. With origin of coordinates (
Figure 438990DEST_PATH_IMAGE007
，
Figure 820293DEST_PATH_IMAGE008
，
Figure 925652DEST_PATH_IMAGE009
) Macroscopic velocity corresponding to the lowest point of temperature: (
Figure 609575DEST_PATH_IMAGE010
，
Figure 744759DEST_PATH_IMAGE011
，
Figure 70698DEST_PATH_IMAGE012
) The part is the sphere center, a hemispherical encryption area and a spherical encryption area are respectively arranged, the radius of the hemisphere and the radius of the sphere are determined by the size of the local temperature, and the radius is larger when the temperature is lower. And generating a hemispherical speed space grid based on the constraint conditions. Relating the hemispherical grid to
Figure 358460DEST_PATH_IMAGE009
And symmetrically copying the plane to obtain the spherical speed space grid.
Wherein, the velocity space grid is determined by two aspects: the size of the outer boundary of the mesh and the spatial distribution of the mesh. The outer grid boundaries are generally determined by the flow velocity (given in step 2). The spatial distribution of the unstructured velocity spatial grid is not uniform, and encryption processing is generally performed near a macroscopic velocity corresponding to a coordinate origin and a temperature minimum point to ensure the accuracy and the effectiveness of a calculation result.
And 4, step 4: and (3) based on the half-mode physical space grid in the step (1) and the spherical velocity space grid in the step (3), performing iterative solution by adopting a unified gas dynamics method, realizing flow field simulation of the half-mode aircraft, and calculating to obtain a three-dimensional space flow field. The specific solving process of the unified gas dynamics method refers to the following documents: jiang Ding Wu, a research on gas dynamics algorithm based on analytical solution of model equation, a doctor paper of the Chinese aerodynamic research and development center, 2016 (6 months).
Step 1 in the method also comprises the step of specifying symmetrical boundaries, and in the calculation process of step 4, various boundary processing is involved besides iterative calculation of points in the grid. Such as a solid wall boundary, an incoming flow boundary, an outgoing flow boundary, a symmetric boundary. Wherein the solid wall boundary refers to the boundary of the contact part of the aircraft surface and the external gas, and is used for identifying the solid area; the inflow boundary refers to a boundary flowing into the calculation region and is used for controlling the gas inflow characteristic; outflow boundary refers to the boundary of the outflow calculation region for controlling the gas outflow characteristics; the symmetric boundary is a boundary set for a flow having symmetry, and its normal velocity is generally 0 in order to avoid repetition of a large number of calculations. The fixed wall boundary, the incoming flow boundary and the outgoing flow boundary all adopt conventional processing methods, and the specific implementation process can refer to documents: jiang Ding Wu, a research on gas dynamics algorithm based on analytical solution of model equation, a doctor paper of the Chinese aerodynamic research and development center, 2016 (6 months).
The symmetric boundary processing is used in combination with the plane-symmetric velocity space grid in the invention, and the symmetric boundary condition processing method in the method is as follows:
in this embodiment, the processing the symmetric boundary in the method includes: setting the macroscopic quantity of the first virtual point and the second virtual point in the symmetric boundary condition and setting the distribution function of the first virtual point and the second virtual point;
as shown in fig. 7, a virtual point 1 in fig. 7 is a first virtual point, a virtual point 2 is a second virtual point, an inner point 1 is a first inner point, and an inner point 2 is a second inner point, and macroscopic quantities of the first virtual point and the second virtual point in the symmetric boundary condition are set as:
Figure 744442DEST_PATH_IMAGE022
，
Figure 868387DEST_PATH_IMAGE023
，
Figure 794754DEST_PATH_IMAGE024
，
Figure 186290DEST_PATH_IMAGE025
，
Figure 539911DEST_PATH_IMAGE026
，
Figure 10207DEST_PATH_IMAGE027
，
Figure DEST_PATH_IMAGE055
，
Figure 68161DEST_PATH_IMAGE029
，
Figure 674723DEST_PATH_IMAGE030
，
Figure 199246DEST_PATH_IMAGE031
(ii) a The purpose of this is that if the flow is symmetric about a certain face, the face can be set as a symmetric boundary when generating the physical space grid, which can save half of the physical space grid.
Figure 32203DEST_PATH_IMAGE032
Is the density at the first virtual point or points,
Figure 238057DEST_PATH_IMAGE056
is the density at the first interior point,
Figure 27021DEST_PATH_IMAGE034
is the density at the second virtual point and,
Figure DEST_PATH_IMAGE057
is the density at the second interior point,
Figure 50341DEST_PATH_IMAGE036
is the velocity in the x direction at the first virtual point,
Figure 495229DEST_PATH_IMAGE037
is the velocity in the x-direction at the first interior point,
Figure 613095DEST_PATH_IMAGE038
is the speed in the x direction at the second virtual point,
Figure 990987DEST_PATH_IMAGE039
is the velocity in the x-direction at the second interior point,
Figure 654050DEST_PATH_IMAGE058
is the velocity in the y direction at the first virtual point,
Figure DEST_PATH_IMAGE059
is the velocity in the y-direction at the first interior point,
Figure 117392DEST_PATH_IMAGE042
is the velocity in the y direction at the second virtual point,
Figure 274835DEST_PATH_IMAGE043
is the velocity in the y-direction at the second interior point,
Figure 38392DEST_PATH_IMAGE044
is the velocity in the z direction at the first virtual point,
Figure 13301DEST_PATH_IMAGE045
is the velocity in the z direction at the first interior point,
Figure 557415DEST_PATH_IMAGE060
is the velocity in the z direction at the second virtual point,
Figure 769083DEST_PATH_IMAGE047
is the velocity in the z direction at the second interior point,
Figure 590408DEST_PATH_IMAGE048
is the pressure at the first virtual point and,
Figure 798535DEST_PATH_IMAGE049
is the pressure at the first interior point,
Figure 564366DEST_PATH_IMAGE050
is the pressure at the second virtual point and,
Figure 250562DEST_PATH_IMAGE051
is the pressure at the second interior point;
the distribution function of the first virtual point and the second virtual point is set as:
Figure 926394DEST_PATH_IMAGE052
；
Figure 118472DEST_PATH_IMAGE053
；
wherein f is a distribution function defined in a three-dimensional physical space and a three-dimensional velocity space in the unified gas dynamics method, the first virtual point is symmetrical with the first interior point about the symmetrical boundary, and the second virtual point is symmetrical with the second interior point about the symmetrical boundary.
By means of the arrangement, density, speed, pressure and distribution functions in the symmetric boundary can meet the physical fact of mirror symmetry, and by doing so, the iterative solution of the step 4 can obtain a correct space flow field result.
Due to the adoption of the method in step 3
Figure DEST_PATH_IMAGE061
The velocity space grid with plane symmetry does not need any interpolation processing in the assignment process of the virtual point distribution function, thereby reducing the calculation amount and ensuring the calculation precision.
Specific implementation examples of the X38-like aircraft scale model flow field simulation are given below.
The incoming flow conditions are set as follows: mach number 8.0, angle of attack 20 degrees, knudsen number 0.275, reference length 0.28 m. Fig. 2 shows a schematic diagram of the appearance of a scaled model of an aircraft of class X38, X, y, and z in fig. 2 are coordinate axes of a three-dimensional physical space, and fig. 3 shows a schematic diagram of the whole velocity space grid generated in step 3. FIG. 4 is a velocity space grid
Figure 371599DEST_PATH_IMAGE007
A cross-sectional view. FIG. 5 is a velocity space grid
Figure 799170DEST_PATH_IMAGE008
A cross-sectional view. FIG. 6 is a velocity space grid
Figure 391825DEST_PATH_IMAGE061
A cross-sectional view. Local encryption is performed near the origin of coordinates and the lowest point of the temperature of the NS prediction solution. The time consumption of symmetric boundaries in the half-mold physical space grid calculation is negligible, so the single-step time is reduced by about 50%. Therefore, aiming at the aircraft surface-symmetric cross-basin flow field, the speed space unstructured grid optimization technology reduces the calculation time and improves the calculation efficiency, and the method is a rapid flow field prediction method.
In the embodiment, the designated area of the velocity space unstructured grid is encrypted based on the flow field calculation result of the NS solver, then the surface symmetric velocity space grid is generated, and the rapid prediction of the aircraft cross-flow-field surface symmetric flow field is realized by combining the distribution function symmetric boundary processing.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (7)

1. A prediction method for an aircraft surface-symmetric cross-basin flow field is characterized by comprising the following steps:
step 1: the method comprises the steps of obtaining overall dimension information of an aircraft, wherein the aircraft is a plane-symmetric aircraft, constructing a first model corresponding to the aircraft based on the overall dimension information of the aircraft, cutting half of the first model to obtain a second model, and generating a first physical space grid based on the second model;
step 2: performing flow field solving based on the first physical space grid and the incoming flow conditions to obtain speed and temperature information of the flow field, and determining a first bit corresponding to a temperature lowest point according to the flow field temperature informationSetting and marking the speed of the first position in the x direction, the y direction and the z direction as follows:
Figure DEST_PATH_IMAGE001
、
Figure DEST_PATH_IMAGE002
and
Figure DEST_PATH_IMAGE003
；
and step 3: generating a three-dimensional velocity space grid, generating an outer boundary of the three-dimensional velocity space grid based on the incoming flow condition, and aligning the three-dimensional velocity space grid based on the outer boundary
Figure DEST_PATH_IMAGE004
、
Figure DEST_PATH_IMAGE005
And
Figure DEST_PATH_IMAGE006
the grid ranges in three directions are arranged to obtain a three-dimensional hemispherical area,
Figure DEST_PATH_IMAGE007
、
Figure DEST_PATH_IMAGE008
and
Figure DEST_PATH_IMAGE009
the position is a coordinate origin, and a hemispherical encryption area is obtained by taking the coordinate origin as a sphere center so as to
Figure DEST_PATH_IMAGE010
、
Figure DEST_PATH_IMAGE011
And
Figure DEST_PATH_IMAGE012
obtaining a spherical encryption area for the center of sphere, generating a hemispherical velocity space grid based on grid spacing distribution information, the hemispherical encryption area and the spherical encryption area, relating the hemispherical velocity space grid to
Figure 793804DEST_PATH_IMAGE009
Symmetrically copying the plane to obtain a spherical speed space grid;
and 4, step 4: performing iterative solution on the basis of the first physical space grid and the spherical three-dimensional velocity space grid to obtain a three-dimensional physical space flow field of the aircraft;
the step 4 specifically includes: based on the first physical space grid and the spherical three-dimensional velocity space grid, carrying out iterative solution on the three-dimensional physical space grid and points in the three-dimensional velocity space grid, and processing related boundaries to obtain a three-dimensional physical space flow field of the aircraft;
the step 1 further comprises: specifying symmetric boundary conditions, wherein the processing of the relevant boundary in step 4 comprises processing the symmetric boundary;
processing the symmetric boundary includes: setting the macroscopic quantity of the first virtual point and the second virtual point in the symmetric boundary condition and setting the distribution function of the first virtual point and the second virtual point;
wherein, the macroscopic quantity of the first virtual point and the second virtual point in the symmetric boundary condition is set as:
Figure DEST_PATH_IMAGE013
，
Figure DEST_PATH_IMAGE014
，
Figure DEST_PATH_IMAGE015
，
Figure DEST_PATH_IMAGE016
，
Figure DEST_PATH_IMAGE017
，
Figure DEST_PATH_IMAGE018
，
Figure DEST_PATH_IMAGE019
，
Figure DEST_PATH_IMAGE020
，
Figure DEST_PATH_IMAGE021
，
Figure DEST_PATH_IMAGE022
；
Figure DEST_PATH_IMAGE023
is the density at the first virtual point and,
Figure DEST_PATH_IMAGE024
is the density at the first interior point,
Figure DEST_PATH_IMAGE025
is the density at the second virtual point and,
Figure DEST_PATH_IMAGE026
is the density at the second interior point,
Figure DEST_PATH_IMAGE027
is the velocity in the x direction at the first virtual point,
Figure DEST_PATH_IMAGE028
is the velocity in the x-direction at the first interior point,
Figure DEST_PATH_IMAGE029
is the speed in the x direction at the second virtual point,
Figure DEST_PATH_IMAGE030
is the velocity in the x-direction at the second interior point,
Figure DEST_PATH_IMAGE031
is the velocity in the y direction at the first virtual point,
Figure DEST_PATH_IMAGE032
is the velocity in the y-direction at the first interior point,
Figure DEST_PATH_IMAGE033
is the velocity in the y direction at the second virtual point,
Figure DEST_PATH_IMAGE034
is the velocity in the y-direction at the second interior point,
Figure DEST_PATH_IMAGE035
is the velocity in the z direction at the first virtual point,
Figure DEST_PATH_IMAGE036
is the velocity in the z direction at the first interior point,
Figure DEST_PATH_IMAGE037
is the velocity in the z direction at the second virtual point,
Figure DEST_PATH_IMAGE038
is the velocity in the z direction at the second interior point,
Figure DEST_PATH_IMAGE039
is the pressure at the first virtual point and,
Figure DEST_PATH_IMAGE040
is the pressure at the first interior point,
Figure DEST_PATH_IMAGE041
is the pressure at the second virtual point and,
Figure DEST_PATH_IMAGE042
is the pressure at the second interior point;
the distribution function of the first virtual point and the second virtual point is set as:
Figure DEST_PATH_IMAGE043
；
Figure DEST_PATH_IMAGE044
；
wherein f is a distribution function defined in a three-dimensional physical space and a three-dimensional velocity space in the unified gas dynamics method, the first virtual point is symmetrical with the first interior point about the symmetrical boundary, and the second virtual point is symmetrical with the second interior point about the symmetrical boundary.
2. The method for predicting the aircraft surface-symmetric cross-basin flow field according to claim 1, wherein the first model is symmetric about a z =0 plane in a three-dimensional physical space where an x-axis, a y-axis and a z-axis are located.
3. The method for predicting the aircraft surface-symmetric cross-basin flow field according to claim 1, wherein an NS solver is adopted to solve the flow field in step 2 of the method.
4. The method for predicting the aircraft surface-symmetric cross-basin flow field according to claim 1, wherein the inflow conditions are as follows: density of incoming flow
Figure DEST_PATH_IMAGE045
Speed of incoming flow in x direction
Figure DEST_PATH_IMAGE046
Y-direction upward flow velocity
Figure DEST_PATH_IMAGE047
Velocity of incoming flow in z-direction
Figure DEST_PATH_IMAGE048
And pressure of incoming flow
Figure DEST_PATH_IMAGE049
。
5. The method for predicting the cross-basin flow field of the aircraft according to claim 4, wherein the three-dimensional velocity space grid based on the outer boundary is
Figure DEST_PATH_IMAGE050
、
Figure 307350DEST_PATH_IMAGE005
And
Figure 555929DEST_PATH_IMAGE006
the grid ranges in three directions are set, including: gridding the three-dimensional velocity space in
Figure 216717DEST_PATH_IMAGE050
And
Figure 234352DEST_PATH_IMAGE005
the grid range of the direction is set to be greater than or equal to
Figure DEST_PATH_IMAGE051
And is less than or equal to
Figure DEST_PATH_IMAGE052
Wherein, in the step (A),
Figure DEST_PATH_IMAGE053
is a mode of the incoming flow velocity,
Figure DEST_PATH_IMAGE054
the grid range of the direction is set to be greater than or equal to
Figure 715536DEST_PATH_IMAGE051
And is less than or equal to 0.
6. The method for predicting the aircraft surface-symmetric cross-basin flow field according to claim 1, wherein the iterative solution is performed by using a unified gas dynamics method in step 4 of the method.
7. The method for predicting the aircraft surface-symmetric cross-basin flow field according to claim 1, wherein the processing of the relevant boundaries in step 4 further comprises processing of a fixed wall boundary, an inflow boundary and an outflow boundary.
CN202210207936.6A 2022-03-04 2022-03-04 Prediction method for aircraft surface-symmetric cross-basin flow field Active CN114330080B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210207936.6A CN114330080B (en) 2022-03-04 2022-03-04 Prediction method for aircraft surface-symmetric cross-basin flow field

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210207936.6A CN114330080B (en) 2022-03-04 2022-03-04 Prediction method for aircraft surface-symmetric cross-basin flow field

Publications (2)

Publication Number Publication Date
CN114330080A CN114330080A (en) 2022-04-12
CN114330080B true CN114330080B (en) 2022-05-13

Family

ID=81031278

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210207936.6A Active CN114330080B (en) 2022-03-04 2022-03-04 Prediction method for aircraft surface-symmetric cross-basin flow field

Country Status (1)

Country Link
CN (1) CN114330080B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115618498B (en) * 2022-11-08 2023-03-10 中国空气动力研究与发展中心计算空气动力研究所 Prediction method, device, equipment and medium for cross-basin flow field of aircraft

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2944623B1 (en) * 2009-04-21 2011-06-10 Airbus France METHOD AND TOOL FOR SIMULATING THE AERODYNAMIC BEHAVIOR OF AN AIRCRAFT IN FLIGHT IN THE NEIGHBORHOOD
US8523115B2 (en) * 2011-01-28 2013-09-03 Lockheed Martin Corporation System, apparatus, program product, and related methods for providing boundary layer flow control
US8912442B2 (en) * 2011-08-01 2014-12-16 SnapPower Active cover plate
CN109492240A (en) * 2018-07-05 2019-03-19 浙江大学 A kind of across basin multiscale simulation method based on second nonlinear constitutive model
CN113051820B (en) * 2021-03-24 2023-05-16 中国空气动力研究与发展中心超高速空气动力研究所 Cross-drainage-basin pneumatic parameter simulation method based on convolutional neural network
CN113343369B (en) * 2021-08-06 2021-10-01 中国空气动力研究与发展中心设备设计与测试技术研究所 Perturbation analysis method for spacecraft aerodynamic fusion orbit

Also Published As

Publication number Publication date
CN114330080A (en) 2022-04-12

Similar Documents

Publication Publication Date Title
Lian et al. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing
CN104298818B (en) A kind of end mill processing surface error prediction and emulation mode
JP5255714B2 (en) Three-dimensional fluid simulation method
CN114330080B (en) Prediction method for aircraft surface-symmetric cross-basin flow field
CN106792749B (en) wireless sensor network node deployment method based on CFD and clustering algorithm
CN116245049A (en) Node type non-structural grid boundary correction method, device, equipment and medium
CN114444216B (en) Aircraft attitude control method and system under high-altitude condition based on numerical simulation
CN112613243A (en) Method and device for fluid mechanics simulation and computer readable storage medium
Demirtas et al. A simplified mathematical model development for the design of free-form cathode surface in electrochemical machining
Tsiakas Development of shape parameterization techniques, a flow solver and its adjoint, for optimization on GPUs. Turbomachinery and external aerodynamics applications
Liu et al. Resistance and wake distortion optimization of JBC considering ship-propeller interaction
CN118070621A (en) Fixed wall boundary processing method and device, terminal equipment and storage medium
CN108920872A (en) For the BCP particle localization realization method and system of DSMC method
Chen et al. Developing an advanced neural network and physics solver coupled framework for accelerating flow field simulations
Strofylas et al. An agglomeration strategy for accelerating RBF-based mesh deformation
Yan et al. Tool path planning for flank milling of non-developable ruled surface based on immune particle swarm optimization algorithm
TWI406189B (en) Method for constructing triangular grids of point clouds
Siwei et al. Review of bounding box algorithm based on 3D point cloud
Fenwick et al. Development and validation of sliding and non-matching grid technology for control surface representation
CN108804791A (en) A kind of aircraft parameters method suitable for Submerged Inlet layout
Li et al. Numerical modeling of non-uniform indoor temperature distribution for coordinated air flow control
CN112883668A (en) LBM parallel optimization method based on multilayer grid
CN111931306A (en) Method and system for regulating and controlling interaction process of main vortex pair based on influence of auxiliary vortex pair
CN118313314B (en) Particle analog free incoming flow boundary processing method, device, equipment and medium
CN110796729B (en) Grid division method based on binary tree

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant