CN115952752A - Data processing method based on flow field simulation robustness calculation under enhanced inclined grid - Google Patents
Data processing method based on flow field simulation robustness calculation under enhanced inclined grid Download PDFInfo
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Abstract
The application discloses a data processing method based on flow field simulation robustness calculation under an enhanced inclined grid, which is characterized in that an interpolation method applied to an internal interface of a target body is matched with an interpolation method applied to an outlet boundary, so that the value on the internal interface and the value on the outlet boundary consider the inclination correction of the grid at the same time, and the interpolated value is more fit. By adopting the method, the robustness can be improved, and the data processing effect can be further improved.
Description
Technical Field
The application belongs to the field of simulation data processing research, and particularly relates to a data processing method based on enhanced flow field simulation robustness calculation under an inclined grid.
Background
The simulation data processing is based on the simulation theory, takes a computer system and physical effect equipment as tools, establishes and operates a model according to a target body, recognizes and reforms a research object, and is an information-class selectable technology generated in the process that the industrialized society advances to the information society.
In the related art, when a SIMPLE algorithm is adopted to solve low-speed flow in the simulation data processing process, grids with large skewness are often encountered, and the grids can cause that the calculation cannot be converged. The robustness is poor, so that the data processing effect is not ideal.
Disclosure of Invention
In order to solve the defects of the prior art, the application provides a data processing method based on flow field simulation robustness calculation under an enhanced inclined grid, and an interpolation method applied to an internal interface of a target body is matched with an interpolation method of an outlet boundary, so that the value on the internal interface and the value on the outlet boundary consider the inclined correction of the grid at the same time, and the interpolated value is more fit. By adopting the method, the robustness can be improved, and the data processing effect can be further improved.
The technical effect that this application will reach is realized through following scheme:
in a first aspect, the present specification provides a data processing method based on enhanced diagonal grid flow field simulation robustness calculation, the method including:
obtaining a model of a target volume, wherein the model represents an internal interface and an exit boundary surface of the target volume; dividing at least part of the flow field formed by the model into a plurality of grid cells; one part of the grid units is an inclined grid, and the other part of the grid units is a non-inclined grid;
setting an initial speed field and an initial pressure field;
correcting the inclined grid to be a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of a target velocity field expressed by a target pressure field;
establishing a pressure correction equation by adopting a calculation model of the target velocity field;
obtaining a pressure correction intermediate value through the calculation of the pressure correction equation;
performing interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value;
obtaining a target speed field output by a calculation model of the target speed field based on a target pressure field obtained according to the pressure correction target value;
and processing data based on the target speed field and the target pressure field.
In an alternative embodiment of the present description, the formula of the calculation model of the target velocity field is represented as:
In an optional embodiment of the present specification, for a target unit, a value of the pressure gradient on the interface is calculated by the following formula; wherein the target cell is any one of the grid cells:
in the formula: c represents the target unit; n represents a neighboring cell, wherein the neighboring cell is a grid cell adjacent to the target cell; p N A pressure value representing the center of an adjacent cell; pc represents a pressure value of the target cell center;
represents->
The projected point of (a);
Represents->
The projected point of (a);
Representing a pressure gradient in the center of the adjacent cell;
representing a pressure gradient in the center of the target cell;
A vector representing the center point of the neighboring cell;
A vector representing the center point of the target cell;
A vector representing a center point of an interface between the target cell and the neighboring cell;
And comparing a first distance with a second distance, and then taking the minimum value, wherein the first distance is the projection distance of the distance from the center point of the target unit to the center point of the interface in the normal direction, and the second distance is the projection distance of the distance from the center point of the adjacent unit to the center point of the interface in the normal direction.
In an optional embodiment of the present specification, for a target unit, a value of the pressure gradient on the interface is calculated by the following formula:
In an alternative embodiment of the present description, the formula of the pressure correction equation is expressed as:
In an alternative embodiment of the present specification, the pressure correction intermediate value belonging to the outlet boundary surface is interpolated to obtain a pressure correction target value by using an interpolation formula as follows:
In an optional embodiment of the present disclosure, obtaining a target velocity field output by a calculation model of the target velocity field based on a target pressure field obtained according to the pressure correction target value includes:
solving a calculation model of the target speed field based on the target pressure field to obtain a speed correction target value;
and correcting the initial speed field by adopting the speed correction target value to obtain a target speed field.
In an alternative embodiment of the present disclosure, the target velocity field is calculated by the following formula:
In an optional embodiment of this specification, before obtaining the target velocity field output by the calculation model of the target velocity field based on the target pressure field obtained according to the pressure correction target value, the method further includes:
and correcting the initial pressure field by adopting the pressure correction target value to obtain a target pressure field.
In an alternative embodiment of the present disclosure, the target pressure field is calculated by the following formula:
The present specification provides an apparatus for data processing based on enhanced diagonal grid flow field simulation robustness computation, for implementing the method in the first aspect, the apparatus comprising:
a model acquisition module configured to: obtaining a model of a target volume, wherein the model represents internal and exit boundary surfaces of the target volume; dividing at least part of the flow field formed by the model into a plurality of grid cells; one part of the grid units is an inclined grid, and the other part of the grid units is a non-inclined grid;
a setting module configured to: setting an initial speed field and an initial pressure field;
a computational model generation module of the target velocity field configured to: correcting the inclined grid to be a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of a target velocity field expressed by a target pressure field;
a pressure correction equation establishment module configured to: establishing a pressure correction equation by adopting a calculation model of the target velocity field;
a pressure correction intermediate value determination module configured to: obtaining a pressure correction intermediate value through the calculation of the pressure correction equation;
a pressure correction target value determination module configured to: performing interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value;
a target velocity field determination module configured to: obtaining a target speed field output by a calculation model of the target speed field based on a target pressure field obtained according to the pressure correction target value;
a data processing module configured to: and processing data based on the target speed field and the target pressure field.
In a third aspect, the present specification provides an electronic device comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of the first aspect.
In a fourth aspect, the present specification provides a computer readable storage medium storing one or more programs which, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of the first aspect.
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In order to more clearly illustrate the embodiments or prior art solutions of the present application, the drawings needed for describing the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and that other drawings can be obtained by those skilled in the art without inventive exercise.
Fig. 1 is a flowchart of a data processing method based on enhanced diagonal grid flow field simulation robustness calculation in an embodiment of the present application;
FIG. 2 is a flowchart of a data processing method based on enhanced diagonal grid lower flow field simulation robustness computation in an alternative embodiment of the present application;
FIG. 3 is a schematic center projection of an unstructured grid cell in an embodiment of the present application;
FIG. 4 is a simplified 2D schematic of a slanted grid at the exit boundary surface in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a data processing apparatus based on enhanced diagonal grid lower flow field simulation robustness calculation in an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following embodiments and accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings. Wherein like elements in different embodiments are numbered with like associated elements. In the following description, numerous specific details are set forth in order to provide a better understanding of the present application. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present application have not been shown or described in detail in order to avoid obscuring the core of the present application from excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they may be fully understood from the description in the specification and the general knowledge in the art.
Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the method descriptions may be transposed or transposed in order, as will be apparent to one of ordinary skill in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.
The numbering of the components as such, e.g., "first", "second", etc., is used herein only to distinguish the objects as described, and does not have any sequential or technical meaning. The term "connected" and "coupled" when used in this application, unless otherwise indicated, includes both direct and indirect connections (couplings).
Various non-limiting embodiments of the present application are described in detail below with reference to the attached drawing figures. In this specification, a data processing method based on enhanced calculation of robustness of flow field simulation under an oblique grid, as shown in fig. 1, includes the following steps:
s100: a model of the target volume is obtained.
The model of the present specification represents the internal and exit boundary surfaces of the target volume. At least part of the flow field formed by the model is divided into a number of grid cells. One part of the grid units is a slant grid, and the other part is a non-slant grid.
The model in this specification may be a CAD file, for example. The obtaining mode in this step may be determined according to actual requirements. For example, the model may be obtained by way of file import or may be obtained by way of modeling.
A target in this specification is a component through which an airflow may flow during operation of the target. Illustratively, the target may be an engine (e.g., an engine of an aircraft), a turbine, or the like. When the airflow flows through the target body, a space provided for the airflow to flow around and/or inside the target body is a flow field. The interface inside the flow field is an internal interface; the interface as the gas stream exits the flow field is the outlet boundary surface.
The specification does not limit the specific shape of the mesh unit, and the mesh unit may be a tetrahedron, a hexahedron, or the like, for example. In the same model, there may be grid cells of different shapes. It can be seen that a model divides a plurality of grid cells.
In an alternative embodiment of the present description, the grid cells in the present description are unstructured grids. Alternatively, the concrete implementation of this step may be to introduce the grid cells constituting the model into the solver.
S102: setting an initial velocity field and an initial pressure field.
In an alternative embodiment of the present description, the initial velocity field and/or the initial pressure field may be set under the triggering of a person; in another alternative embodiment of the present description, the initial velocity field and/or the initial pressure field are automatically set by the executive body of the present application.
S104: and correcting the inclined grid to be a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of the target velocity field represented by the target pressure field.
The target pressure field in this specification is a pressure field actually used when data processing is performed, and the target pressure field is different from the initial pressure field by a certain amount. The target velocity field in this specification is a velocity field actually used when data processing is performed, and the target velocity field is different from the initial velocity field to some extent.
In this step, the target pressure field is not yet obtained, and the target pressure field may be characterized by a calculation model of the target pressure field. The calculation model in this specification can be characterized in the form of a formula. After the target pressure field is obtained in the subsequent steps, a target speed field can be further obtained based on the target pressure field.
In an alternative embodiment of the present disclosure, a SIMPLE algorithm may be used to calculate a momentum equation based on a given initial velocity field and initial pressure field, so as to obtain a calculation model of the target velocity field.
In an alternative embodiment of the present specification, a pre-processing of the grid cells is also performed before the step is performed.
S106: and establishing a pressure correction equation by adopting the calculation model of the target velocity field.
From this step, the target pressure field needs to be obtained by calculation. The pressure correction equation in this step is used to output a pressure correction intermediate value.
S108: and obtaining a pressure correction intermediate value through calculation of the pressure correction equation.
After the pressure correction intermediate value is obtained, it may be processed to obtain a pressure correction target value, and further a target pressure field may be obtained based on the pressure correction target value.
In an optional embodiment of the present description, the pressure correction equation may be solved discretely according to the divergence theorem, so as to obtain a pressure correction intermediate value.
S110: performing interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value;
based on the steps, the interpolation method on the outlet boundary is matched with the internal interface interpolation method in the momentum correction process, so that the values on the internal interface and the outlet boundary simultaneously consider the inclination correction of the grid, and the calculation precision is ensured.
S112: and obtaining a target speed field output by a calculation model of the target speed field based on the target pressure field obtained according to the pressure correction target value.
After the target pressure field is obtained, the calculation model of the target velocity field may be calculated based on the target pressure field, so as to obtain the target velocity field.
S114: and processing data based on the target speed field and the target pressure field.
Data relating to the flow field can be processed by the method in the present specification, where conditions permit. For example, the data processed by the method of the present specification may be pneumatic data. In this specification, the process of generating a target velocity field and/or generating a target pressure field may also be considered as a kind of data processing.
When the SIMPLE algorithm is used for solving the low-speed flow, grid units with large skewness are frequently encountered, and the grid units can cause the calculation to be incapable of converging. The main reason why convergence cannot be achieved is that interpolation on an interface is performed in the calculation process, when a grid unit is inclined, a general interpolation method ignores calculation errors caused by inclination of the grid unit, especially the position of an outlet boundary surface, and often ignores interpolation, so that a value interpolated on the interface has a large deviation from a real value, and convergence of flow field simulation cannot be achieved.
Because the flow correction of the inlet and outlet is performed in the SIMPLE algorithm, and the correction method mainly performs specific processing on the value of the outlet boundary surface, the correctness of the variable value on the outlet boundary surface is important. In order to obtain a flow field with computational convergence, it is necessary to perform a tilt correction interpolation on a mesh cell having a tilt, however, in general, the tilt correction of the interface interpolation is ignored, and even a value obtained by duplicating an internal cell is used for a value on an exit boundary surface without performing the interface interpolation, and thus, an abnormal value occurs in numerical simulation.
At present, for such a grid unit with an inclination, interpolation at an outlet boundary surface is often ignored, so that a value of an internal interface and a value of the outlet boundary surface do not reach effective fitting, the inclination correction of the grid unit is considered for a value after interpolation of the internal interface, but the value on the outlet boundary surface is not subjected to the inclination correction, and a flow correction process makes a value deviation on the outlet boundary surface larger, so that an abnormal value occurs in a flow field calculation result, the convergence cannot be good, and the robustness is reduced.
According to the data processing method based on the flow field simulation robustness calculation under the enhanced inclined grid, the interpolation method applied to the internal interface of the target body is matched with the interpolation method applied to the outlet boundary, so that the value on the internal interface and the value on the outlet boundary consider the inclined correction of the grid at the same time, and the interpolated value is more fit. By adopting the method, the robustness can be improved, and the data processing effect can be further improved.
To further improve the robustness in the data processing process and improve the data processing effect, a further alternative embodiment of the present application is now described, and an exemplary flow of at least part of the alternative embodiment is shown in fig. 2.
Before describing alternative embodiments, several concepts involved will be described.
SIMPLE algorithm: semi-Implicit algorithm for solving Pressure Linked Equations, semi-Implicit Method for solving Pressure coupled Equations.
SIMPLE type algorithm: based on the SIMPLE algorithm, a series of algorithms are generated by correspondingly improving the defects of the SIMPLE algorithm, and the algorithms are collectively called SIMPLE algorithms.
The momentum equation: the SIMPLE algorithm solves the equation of the velocity field, and the equation is derived from the momentum conservation principle of the fluid.
Pressure correction equation: the SIMPLE algorithm solves the equation for the pressure correction value, which reflects the conservation of mass of the fluid.
Grid cell: because the calculation of the flow field needs to solve a partial differential equation set, the existing method for solving the equation adopts a numerical solution, namely, the whole calculation domain is discrete, and the continuous flow field is decomposed into small units, wherein the small units are grids.
Grid skewness: because the shape of the flow field is irregular in reality, grid units with larger deflection angles often appear when the grid is divided, and the grid units are dispersed, which can cause adverse effects on the solution of the equation and is not beneficial to the convergence of the equation. Such a grid cell is also referred to as a slanted grid.
Boundary conditions: the change rule of the variable or derivative thereof solved on the boundary of the solving area along with time and position is the premise that the control equation has definite solution. A zone boundary such as an exit boundary surface.
Internal interface: refers to the law of change over time and position of the variable or its derivative being solved for on the non-boundary of the solution area.
In an alternative embodiment, the formula of the calculation model of the target velocity field in step S104 is represented as the following formula (one).
In the calculation process of the pressure correction equation, velocity interpolation on a unit surface is used, and if the interpolation is not proper, the solution of the pressure value or the velocity value is oscillated. The problem of velocity interpolation can be solved by the momentum interpolation of the updated velocity field through the formula (I).
Any one of the grid cells is taken as a target cell.
In an alternative embodiment of the present description, the pressure gradient is at the interface for the target cellValue of
The calculation can be obtained by the following formula (two):
The pressure gradient solving realized by the formula (II) has the characteristics of simplicity and high efficiency. But the correction capability of the inclined grid unit is poor, so that the robustness is still improved.
In another alternative embodiment of the present description, the pressure gradient takes on values on the interface for the target cell
The calculation can be obtained by the following formulas (three) to (six):
In the formula: c represents the target unit; n represents a neighboring cell, wherein the neighboring cell is a net adjacent to the target cellA grid cell;
represents->
The projected point of (a);
Represents->
The projected point of (a);
Representing a pressure gradient in the center of the adjacent cell;
Representing a pressure gradient in the center of the target cell;
A vector representing the center point of the neighboring cell;
A vector representing the center point of the target cell;
A vector representing the center point of the interface between the target cell and the neighboring cell;
And comparing a first distance with a second distance, and then taking the minimum value, wherein the first distance is the projection distance of the distance from the center point of the target unit to the center point of the interface in the normal direction, and the second distance is the projection distance of the distance from the center point of the adjacent unit to the center point of the interface in the normal direction.
The pressure gradient solution realized by the formulas (three) to (six) increases the calculation of the correction quantity of the inclined grid unit, and the advantage of doing so is that in the face of the grid unit with larger inclination, the calculation result after the interpolation of the formula (two) can have a relaxation effect, so that the calculation of the inclination correction quantity cannot be overlarge, and the stability of the calculation process is ensured.
In an alternative embodiment, the formula of the target pressure correction equation in step S106 is expressed as the following formula (seven).
In the formula (I), the compound is shown in the specification,
is a diffusion term; p' is a pressure correction intermediate value; u shape * Is the initial pressure field.
The projection diagram of the center point of the unstructured grid unit is shown in fig. 3, and considering that the improvement only by momentum interpolation is still insufficient, if the calculation of the exit boundary surface value still does not adopt the interpolation method, it is difficult to improve the overall robustness.
The pressure correction amount can be obtained by solving the pressure correction equation discretely. The right end of the above equation is the velocity field after momentum interpolation, which is a known source term. The left end is a diffusion item, and discrete solution can be carried out according to the divergence theorem.
In different boundary conditions, because the SIMPLE algorithm is adopted, the calculation process has flow correction of the outlet and the inlet, and the correction processing process mainly adjusts the variable value on the outlet boundary surface, so the influence of the grid inclination at the outlet boundary surface is larger than that at other positions, and the inclined grid of the outlet boundary surface is briefly shown in fig. 4.
In the related art, the calculation of the pressure correction value P' at the outlet boundary is usually performed by directly assigning the value inside the cell to the boundary without performing interpolation processing, and the calculation method is as follows:
As is evident from the schematic diagram of figure 4,
and &>
The positions of the center points of the two boundary surfaces are not at the same distance from the cell center C, but it is obviously not reasonable to assign values so that they are treated indiscriminately.
Therefore, the calculation of the value on the exit boundary is preferably performed by interpolation. By the known value of the cell center C
And performing gradient interpolation according to the distance from the cell center C to the center of different boundary surfaces. In an alternative embodiment, the interpolation calculation formula used in step S110 to obtain the pressure correction target value is as shown in the following formula (eight). />
Wherein d represents an interpolated distance from the center of the target cell to the center of the exit boundary surface;
indicating the pressure correction target value;
A gradient field representing a pressure correction target value;
Is a pressure correction target value for the center of the known unit.
Through the interpolation calculation formula shown in the formula (eight), different interpolation distances exist between the centers of different outlet boundary surfaces and the center C of the unit, so that different pressure correction values can be obtained, and the inclined grid is corrected to a certain extent, so that the calculated value of the outlet boundary surface is more reasonable.
Based on the above description, the present specification creatively matches the interpolation method on the exit boundary with the interpolation method on the internal interface in the momentum correction process, so that the values on the internal interface and the exit boundary surface simultaneously consider the inclination correction of the grid, thereby ensuring the accuracy of the calculation.
According to the processing method of the present specification, even if there is a grid tilt, the interpolation accuracy on the interface can be satisfied. When the grid unit is orthogonal and has no inclination, the calculation result of the inclination correction amount is 0, and the original calculation result is still not influenced. Therefore, the method can greatly improve abnormal values of calculation caused by grid inclination, and further improves the robustness of the algorithm.
After solving for the resulting pressure correction value P ', the gradient field of the pressure correction value P' may be solved. In an alternative embodiment, the process of obtaining the target speed field in step S112 may be: and solving the calculation model of the target speed field based on the target pressure field to obtain a speed correction target value. And correcting the initial speed field by adopting the speed correction target value to obtain a target speed field.
Here, the velocity correction target value can be obtained by the following equation (nine).
In the formula, U' is a speed correction target value.
On the basis of obtaining the velocity correction target value, the target velocity field can be obtained by the following formula (ten).
In the formula: u shape * Is the target velocity field; u shape *-1 Is the historical target velocity field obtained from the last iteration; u' is a speed correction target value.
For a pressure field, in an optional embodiment of the present specification, before a target velocity field output by a calculation model of the target velocity field is obtained, the initial pressure field is corrected by using the pressure correction target value, so as to obtain a target pressure field. Then, the target pressure field is calculated by the following formula (eleven).
In the formula: p * Is the target pressure field; p *-1 Is the historical target pressure field obtained from the last iteration; p' is a pressure correction target value.
After obtaining the target velocity field and the target pressure field, calculating an equation residual, if a preset residual requirement (in an optional embodiment, an artificial rule may be satisfied), ending the calculation, and outputting a flow field result; and if the residual error requirement is not met, returning to the step S102 for iterative calculation until the residual error requirement is met. Optionally, the converged flow field is then post-processed for display.
Aiming at the problem of computational non-convergence caused by large grid skewness in the flow field computation process of the conventional SIMPLE algorithm, the specification creatively uses two modes of internal interface interpolation and outlet boundary interpolation in a matching manner, and successfully solves the problem. Compared with the prior art, the robustness of the method calculation is improved.
Based on the same idea, the embodiment of the present specification further provides a data processing apparatus based on the calculation of the robustness of the flow field simulation under the enhanced inclined grid corresponding to the partial process shown in fig. 1.
As shown in fig. 5, a data processing apparatus based on enhanced robustness computation of flow field simulation under a slanted grid in the present specification may include one or more of the following modules:
a model acquisition module 500 configured to: obtaining a model of a target volume, wherein the model represents internal and exit boundary surfaces of the target volume; dividing at least part of the flow field formed by the model into a plurality of grid cells; one part of the grid units is an inclined grid, and the other part of the grid units is a non-inclined grid;
a setup module 502 configured to: setting an initial speed field and an initial pressure field;
a computational model generation module 504 of the target velocity field configured to: correcting the inclined grid to be a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of a target velocity field expressed by a target pressure field;
a pressure correction equation establishment module 506 configured to: establishing a pressure correction equation by adopting a calculation model of the target velocity field;
a pressure correction intermediate determination module 508 configured to: obtaining a pressure correction intermediate value through the calculation of the pressure correction equation;
a pressure correction target determination module 510 configured to: performing interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value;
a target velocity field determination module 512 configured to: obtaining a target speed field output by a calculation model of the target speed field based on a target pressure field obtained according to the pressure correction target value;
a data processing module 514 configured to: and processing data based on the target speed field and the target pressure field.
In an alternative embodiment of the present description, the formula of the computational model of the target velocity field is represented as:
in the formula: f represents the value of the quantity on the interface, wherein the interface comprises the internal interface and/or the outlet boundary surface; the upper dash represents the average;
representing the value of the pressure gradient on the interface;
Representing a known coefficient;
Representing a normal direction of the interface;
Representing a target speed field obtained by the iterative computation;
An average value of a historical target velocity field representing a previous iteration calculation; p represents the target pressure field.
In an alternative embodiment of the present specification, the calculation model generation module 504 of the target velocity field is specifically configured to: the value of the pressure gradient on the interface is calculated by the following formula; wherein the target cell is any one of the grid cells:
In an alternative embodiment of the present description, the calculation model generation module 504 of the target velocity field is specifically configured to: for the target unit, the value of the pressure gradient on the interface is calculated by the following formula:
In an alternative embodiment of the present description, the pressure correction equation is formulated as:
In an alternative embodiment of the present disclosure, the pressure correction target value determination module 510 is specifically configured to: and performing interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value by adopting an interpolation calculation formula as follows:
In an alternative embodiment of the present disclosure, the target velocity field determination module 512 is specifically configured to: solving a calculation model of the target velocity field based on the target pressure field to obtain a velocity correction target value; and correcting the initial speed field by adopting the speed correction target value to obtain a target speed field.
In an alternative embodiment of the present description, the target velocity field is calculated by the following formula:
in the formula: u shape * Is the target velocity field; u shape *-1 Is the historical target velocity field obtained from the last iteration; u' is a speed correction target value.
In an optional embodiment of the present description, the apparatus further comprises a target pressure field determination module configured to: and correcting the initial pressure field by adopting the pressure correction target value to obtain a target pressure field.
In an alternative embodiment of the present description, the target pressure field determination module is specifically configured to:
in the formula: p * Is the target pressure field; p *-1 Is the historical target pressure field obtained from the last iteration; p' is a pressure correction target value.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 6, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral component interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 6, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads a corresponding computer program from the nonvolatile memory to the memory and then runs the computer program, and a data processing method based on flow field simulation robustness calculation under the enhanced inclined grid is formed on a logic level. And the processor is used for executing the program stored in the memory and is particularly used for executing any one of the data processing methods based on the calculation of the enhanced flow field simulation robustness under the inclined grid.
The data processing method based on the flow field simulation robustness calculation under the enhanced diagonal grid as disclosed in the embodiment of fig. 1 of the present application can be applied to a processor (i.e., a deletion control module in this specification), or implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute a data processing method based on enhanced diagonal grid lower flow field simulation robustness calculation in fig. 1, and implement the functions of the embodiment shown in fig. 1, which is not described herein again in this embodiment of the present application.
The present application further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by an electronic device including a plurality of application programs, enable the electronic device to perform a method performed by the data processing method based on robustness calculation of flow field simulation under an enhanced diagonal grid in the embodiment shown in fig. 1, and are specifically configured to perform any one of the foregoing data processing methods based on robustness calculation of flow field simulation under an enhanced diagonal grid.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic tape cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (6)
1. A data processing method based on flow field simulation robustness calculation under an enhanced inclined grid is characterized by comprising the following steps:
obtaining a model of a target volume, wherein the model represents internal and exit boundary surfaces of the target volume; dividing at least part of the flow field formed by the model into a plurality of grid cells; one part of the grid units is an inclined grid, and the other part of the grid units is a non-inclined grid;
setting an initial speed field and an initial pressure field;
correcting the inclined grid to be a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of a target velocity field expressed by a target pressure field;
establishing a pressure correction equation by adopting a calculation model of the target velocity field;
obtaining a pressure correction intermediate value through the calculation of the pressure correction equation;
performing interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value;
obtaining a target speed field output by a calculation model of the target speed field based on a target pressure field obtained according to the pressure correction target value;
and processing data based on the target speed field and the target pressure field.
2. The method of claim 1, wherein the computational model of the target velocity field is formulated as:
3. The method of claim 2, wherein the value of the pressure gradient at the interface for a target cell is calculated by the following formula; wherein the target cell is any one of the grid cells:
4. The method of claim 2, wherein the value of the pressure gradient at the interface for a target cell is calculated by the formula:
5. The method of claim 1, wherein the pressure correction equation is formulated as:
in the formula (II)>
Is a diffusion term; p' is a pressure correction intermediate value; u shape * Is the initial pressure field.
6. The method according to claim 3 or 4, wherein the pressure correction intermediate value pertaining to the outlet boundary surface is interpolated to obtain a pressure correction target value using an interpolation formula of:
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116245049A (en) * | 2023-05-11 | 2023-06-09 | 中国空气动力研究与发展中心计算空气动力研究所 | Node type non-structural grid boundary correction method, device, equipment and medium |
| CN116384165A (en) * | 2023-06-05 | 2023-07-04 | 中国空气动力研究与发展中心计算空气动力研究所 | Ultra-relaxation processing method and device for enhancing computing efficiency and robustness |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040133350A1 (en) * | 2003-01-08 | 2004-07-08 | Schlumberger Technology Corporation | Digital pressure derivative method and program storage device |
| CN108319793A (en) * | 2018-02-12 | 2018-07-24 | 大连理工大学 | A kind of low speed based on CFD tilts into the water the analysis method of free movement |
| CN111814422A (en) * | 2020-09-15 | 2020-10-23 | 北京智芯仿真科技有限公司 | Interpolation matrix construction method and device of integrated circuit electromagnetic simulation multiple grid method |
| DE102021120727A1 (en) * | 2021-03-23 | 2022-09-29 | Huazhong University Of Science And Technology | Parallel calculation method and system for the numerical simulation of casting flow fields |
-
2023
- 2023-03-10 CN CN202310227478.7A patent/CN115952752B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040133350A1 (en) * | 2003-01-08 | 2004-07-08 | Schlumberger Technology Corporation | Digital pressure derivative method and program storage device |
| CN108319793A (en) * | 2018-02-12 | 2018-07-24 | 大连理工大学 | A kind of low speed based on CFD tilts into the water the analysis method of free movement |
| CN111814422A (en) * | 2020-09-15 | 2020-10-23 | 北京智芯仿真科技有限公司 | Interpolation matrix construction method and device of integrated circuit electromagnetic simulation multiple grid method |
| DE102021120727A1 (en) * | 2021-03-23 | 2022-09-29 | Huazhong University Of Science And Technology | Parallel calculation method and system for the numerical simulation of casting flow fields |
Non-Patent Citations (2)
| Title |
|---|
| PATANKAR,NA等: "Lagrarian numerical simulation of particulate flows", 《INTERNATIONAL NUMERICAL SIMULATION OF PARTICULAR FLOWS》 * |
| 高翔: "非结构CFD并行网格变形算法及其应用", 《中国博士学位论文全文数据库 (基础科学辑)》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116245049A (en) * | 2023-05-11 | 2023-06-09 | 中国空气动力研究与发展中心计算空气动力研究所 | Node type non-structural grid boundary correction method, device, equipment and medium |
| CN116384165A (en) * | 2023-06-05 | 2023-07-04 | 中国空气动力研究与发展中心计算空气动力研究所 | Ultra-relaxation processing method and device for enhancing computing efficiency and robustness |
| CN116384165B (en) * | 2023-06-05 | 2023-08-18 | 中国空气动力研究与发展中心计算空气动力研究所 | Ultra-relaxation processing method and device for enhancing computing efficiency and robustness |
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