CN114186504A - Method, device and medium for predicting stable boundary of air compressor under intake distortion condition - Google Patents
Method, device and medium for predicting stable boundary of air compressor under intake distortion condition Download PDFInfo
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Abstract
The invention provides a method, equipment and a medium for predicting a stable boundary of a gas compressor under the condition of inlet distortion, wherein the method comprises the steps of calculating a blade domain by adopting a volume force model of a distributed force source, calculating a non-blade domain by adopting a Reynolds average method, and giving a distortion condition required by a target condition to an inlet boundary condition so as to obtain the spatial distribution of the load of the gas compressor. The method analyzes and predicts the flow stability based on the knowledge of the space distribution and the critical load of the compressor load, and considers that the instability is triggered when the load of the compressor in the existing region reaches the local critical load, and the prediction precision is higher; in addition, due to the adoption of a calculation method based on a distributed force source volume force model, the load space distribution of the compressor can be quickly acquired under the condition of intake distortion, so that the efficiency of stable boundary prediction work can be greatly improved.
Description
Technical Field
The invention relates to the field of aircraft engines, in particular to a method, equipment and medium for predicting a stable boundary of a gas compressor under the condition of intake distortion.
Background
The compressor is one of the core components of the aircraft engine and plays a decisive role in the performance and stability of the engine. If the compressor has flow instability, the performance of the aircraft engine is reduced slightly, and flight accidents are directly caused seriously, which brings serious consequences. With the continuous pursuit of high thrust-weight ratio and high efficiency of the engine, the design load of the compressor part is continuously improved, the flow complexity is continuously enhanced, and the problem of flow stability is increasingly highlighted. In addition, because the aero-engine does not always work under the condition of uniform air intake in the actual operation process, and various working conditions such as take-off, crosswind and maneuvering flight are encountered, the complex distortion condition encountered at the inlet of the compressor can further cause the stability boundary of the compressor to move to the right, and the stability working margin is reduced. Therefore, in the actual engineering links such as design and evaluation of the compressor, prediction of the stable boundary of the compressor needs to be carried out according to the intake distortion condition.
At present, prediction methods for the flow stability boundary of the gas compressor at home and abroad mainly comprise two main types, one type is a semi-analytic stability theoretical model method, and the prediction methods comprise a linear small disturbance theoretical model represented by an Emmons model and a Stenning model, a system stability model represented by a Moore-Greitzer model and the like; the other type is a numerical simulation method, namely the flow field characteristics of the gas compressor are obtained by solving a Reynolds average Navier-Stokes equation, and whether the gas compressor is stable or not is judged by calculating whether the gas compressor is converged or not after changing boundary conditions.
However, the stability theoretical model method greatly simplifies the geometry and the flow field of the compressor when establishing the model, and the prediction accuracy is difficult to guarantee under the requirement of fine design at the present stage. For the numerical simulation method, the method of judging the flow field stability through the convergence of the steady calculation lacks a theoretical basis, optimistic estimation is often made on a stable boundary, and for the prediction problem of the stable boundary of the compressor under the condition of the outburst matching, the problem can be solved only by carrying out the whole-cycle unsteady numerical simulation of the integration of the air inlet/the compressor, and the consumption of the work on the calculation resources and the time is hard to bear in the engineering application.
Disclosure of Invention
To this end, the present invention provides a method, system, apparatus and medium for compressor stability margin prediction of intake air distortion conditions in an effort to solve or at least alleviate at least one of the problems identified above.
According to an aspect of the embodiments of the present invention, there is provided a compressor stability boundary prediction method for intake distortion conditions, including:
s1: under the condition that the air compressor uniformly admits air, calculating by adopting a constant Reynolds average method to obtain flow field parameters of the air compressor;
s2: constructing a distributed force source volume force model according to the flow field parameters and the blade parameters of the gas compressor, and outputting the distributed force source volume force;
s3: the blade domain adopts the volume force model of the distributed force source to calculate, the non-blade domain adopts a Reynolds average method to perform non-constant calculation, and the inlet boundary condition gives a distortion condition required by a target condition, so that the spatial distribution of the load of the gas compressor is obtained;
s4: judging according to the spatial distribution of the compressor load, and returning to S3 if the load of the whole compressor or any local area does not reach the local critical load; and if the load of the whole or local area of the compressor reaches the local critical load, the compressor is unstable and outputs the last stable point.
Further, the compressor flow field parameters and the blade parameters include a local radius of the blade, a circumferential angle coordinate of the blade, a surface pressure of the blade, a projection speed of a local speed of the airflow along a meridian plane, a local tangential speed of the blade, a local tangential speed of the airflow, a local static temperature, a local airflow density, an airflow speed under a local relative coordinate system, an entropy gradient along a flow direction, and a mach number corresponding to the local flow direction speed.
Further, the non-blade area comprises all areas from the inlet of the compressor to the front edge of the first row of blade areas, between the adjacent blade areas and from the tail edge of the last row of blade areas to the outlet of the compressor.
Further, the local critical load is the local load when the compressor is locally unstable.
Further, the method also comprises the step of S5: obtaining a last stable point and a first instability point, and when the throttling step length between the last stable point and the first instability point is small enough, taking the last stable point as a prediction stable boundary of the compressor under the condition of the intake distortion air inlet channel; otherwise, return to S3.
Further, the distributed force source volume force comprises tangential volume force of the blade to the fluid, volume force along an equidirectional coordinate plane and volume force along an equivane height plane.
Further, the interface between the blade area and the non-blade area is a ZR coordinate plane of the curved blade leading edge and the curved blade trailing edge formed after the projection of the blade leading edge on the meridian plane rotates for one circle along the circumferential direction.
Furthermore, the inlet boundary condition gives total temperature, total pressure distribution and speed direction, the outlet boundary condition gives average static pressure condition, and the simulation of the throttling process of the compressor is realized by reducing the outlet static pressure, and the solid wall boundary including the casing and the hub is a non-slip boundary condition.
Further, the total pressure ratio, the D factor or the pressure rise coefficient of the inlet and the outlet of the blade are used as the characteristic quantities of the blade load.
According to yet another aspect of the present invention, there is provided a computing device comprising:
one or more processors;
a memory; and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors to perform the operations of the compressor stability boundary prediction method for intake air distortion conditions described above.
According to the technical scheme provided by the embodiment of the invention, the blade domain is calculated by adopting the volume force model of the distributed force source, the non-blade domain is calculated by adopting a Reynolds average method, and the inlet boundary condition gives a distortion condition required by a target condition, so that the spatial distribution of the load of the compressor is obtained. The method analyzes and predicts the flow stability based on the knowledge of the space distribution and the critical load of the compressor load, and considers that the instability is triggered when the load of the compressor in the existing region reaches the local critical load, and the prediction precision is higher; in addition, due to the adoption of a calculation method based on a distributed force source volume force model, the load space distribution of the compressor can be quickly acquired under the condition of intake distortion, so that the efficiency of stable boundary prediction work can be greatly improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the principles of the invention.
FIG. 1 is a block diagram of an exemplary computing device;
FIG. 2 is a flow chart of a compressor stability margin prediction method of intake distortion case according to the present invention;
FIG. 3 is a detailed flow chart of the method of FIG. 2;
FIG. 4 is a computational domain grid distribution diagram of the method of FIG. 2;
FIG. 5 is an inlet total pressure radial profile;
FIG. 6 is a radial pressure ratio distribution at various flow points using the method of FIG. 2;
fig. 7 is a graph comparing the predicted results with the experimental results.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 is a block diagram of an example computing device 100 arranged to implement a compressor stability boundary prediction method of intake air distortion conditions in accordance with the present invention. In a basic configuration 102, computing device 100 typically includes system memory 106 and one or more processors 104. A memory bus 108 may be used for communication between the processor 104 and the system memory 106.
Depending on the desired configuration, the processor 104 may be any type of processing, including but not limited to: a microprocessor (μ P), a microcontroller (μ C), a Digital Signal Processor (DSP), or any combination thereof. The processor 104 may include one or more levels of cache, such as a level one cache 110 and a level two cache 112, a processor core 114, and registers 116. The example processor core 114 may include an Arithmetic Logic Unit (ALU), a Floating Point Unit (FPU), a digital signal processing core (DSP core), or any combination thereof. The example memory controller 118 may be used with the processor 104, or in some implementations the memory controller 118 may be an internal part of the processor 104.
Depending on the desired configuration, system memory 106 may be any type of memory, including but not limited to: volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.), or any combination thereof. System memory 106 may include an operating system 120, one or more programs 122, and program data 124. In some implementations, the program 122 can be configured to execute instructions on an operating system by one or more processors 104 using program data 124.
Computing device 100 may also include an interface bus 140 that facilitates communication from various interface devices (e.g., output devices 142, peripheral interfaces 144, and communication devices 146) to the basic configuration 102 via the bus/interface controller 130. The example output device 142 includes a graphics processing unit 148 and an audio processing unit 150. They may be configured to facilitate communication with various external devices, such as a display terminal or speakers, via one or more a/V ports 152. Example peripheral interfaces 144 may include a serial interface controller 154 and a parallel interface controller 156, which may be configured to facilitate communication with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device) or other peripherals (e.g., printer, scanner, etc.) via one or more I/O ports 158. An example communication device 146 may include a network controller 160, which may be arranged to facilitate communications with one or more other computing devices 162 over a network communication link via one or more communication ports 164.
A network communication link may be one example of a communication medium. Communication media may typically be embodied by computer readable instructions, data structures, program modules, and may include any information delivery media, such as carrier waves or other transport mechanisms, in a modulated data signal. A "modulated data signal" may be a signal that has one or more of its data set or its changes made in such a manner as to encode information in the signal. By way of non-limiting example, communication media may include wired media such as a wired network or private-wired network, and various wireless media such as acoustic, Radio Frequency (RF), microwave, Infrared (IR), or other wireless media. The term computer readable media as used herein may include both storage media and communication media.
Computing device 100 may be implemented as part of a small-form factor portable (or mobile) electronic device such as a cellular telephone, a Personal Digital Assistant (PDA), a personal media player device, a wireless web-watch device, a personal headset device, an application specific device, or a hybrid device that include any of the above functions. Computing device 100 may also be implemented as a personal computer including both desktop and notebook computer configurations.
Among other things, one or more programs 122 of the computing device 100 include instructions for performing a compressor stable boundary prediction method of intake air distortion conditions in accordance with the present invention.
Fig. 2 illustrates a flowchart of a compressor stability boundary prediction method for intake air distortion conditions according to an embodiment of the present invention, which starts at step S1. Fig. 3 is a detailed flow chart of the method of fig. 2.
S1: and under the condition that the air compressor uniformly admits air, calculating by adopting a constant Reynolds average method to obtain the flow field parameters of the air compressor.
Specifically, the compressor rotor parameters comprise local radius of the blade, a blade circumferential angle coordinate, blade surface pressure, a projection speed of the local speed of the airflow along a meridian plane, the local tangential speed of the blade, the local tangential speed of the airflow, a local static temperature, local airflow density, airflow speed under a local relative coordinate system, an entropy gradient along a flow direction, and a mach number corresponding to the local flow direction speed.
S2: according to the flow field parameters and the blade parameters of the gas compressor, a distributed force source volume force model is constructed, and the distributed force source volume force is output
. Tangential volumetric force of fluid including vanes
Volume force along isoflow direction coordinate plane
And volume force along equal blade height
And comprises the following steps:
obtaining the tangential volumetric force
The formula is as follows:
wherein, Fθ，invIs the local tangential volumetric force of the blade to the airflow; r is the local radius of the blade; theta is a circumferential angle coordinate; p is the pressure.
By passingThe volume force F of the height surface of the edge equal blade is obtained by calculating the mechanical energy conservation equations，inv；
The formula is as follows: fs，inv·Vs+Fη，inv·Vη+Fθ，inv·Vθ＝Fθ，inv·U
Obtaining the viscous force of the blade to the airflow through calculation of a loss equation
The formula is as follows:
wherein,
is the viscous force of the blade to the airflow, and the direction of the viscous force is opposite to the direction of the airflow speed under the local relative coordinate system; vsIs the projection of the local velocity of the gas flow along the meridian plane; t is the local static temperature, ρ is the local density;
is the air flow velocity in the local relative coordinate system;
is the entropy gradient along the direction of the grid flow obtained by extraction from the first flow field.
Extracting the tangential volumetric force F for a plurality of the first flow fieldsθ，invAnd the entropy gradient
And the local pneumatic parameters
Correlation was performed to construct a volumetric matrix.
S3: and carrying out full-cycle numerical simulation of the gas compressor based on a volume force model of the distributed force source under the condition of intake distortion. The calculation domain is divided into a blade domain and a non-blade domain, and the interface between the two is determined by ZR coordinates of the leading edge and the trailing edge of the blade. The non-blade area includes all parts from the inlet to the rotor blade area, between the blade areas and after the last blade area to the outlet, i.e. all areas except the blade area. The computational domain grid is a hexahedral structured grid and is generated by scanning a meridian plane grid around a rotating shaft, as shown in fig. 4, a region with a darker color at a position A in the graph is a blade domain, the rest regions are non-blade domains, and the grids of the blade domain and the non-blade domains are completely matched at an interface, so that the problem of interface data transmission errors does not exist. In the calculation process, a distributed force source volume force model is adopted in a blade domain, and a Reynolds average method is adopted in a non-blade domain to perform non-steady calculation. The inlet boundary conditions are given with total temperature, total pressure distribution (given based on test measurement results) and speed direction (axial air intake), the outlet boundary conditions are given with average static pressure conditions, the simulation of the throttling process of the air compressor is realized by reducing the outlet static pressure, and in addition, the solid wall boundary including the casing and the hub are non-slip boundary conditions.
S4: the distribution condition of the compressor load under the condition of intake distortion is obtained through the calculation result, the total pressure ratio is selected as a characteristic parameter of the blade load in the example, and the intake distortion condition is given as radial distortion in the example and is uniformly distributed in the circumferential direction, so that the radial distribution of the pressure ratio is only required to be obtained. Two points need to be explained here: 1. the total pressure ratio is only one blade load characterization parameter selected in the example, in addition, a factor D, a pressure rise coefficient and the like can also be used as load characterization quantities, appropriate parameters are selected for different research objects, and the factor D is a diffusion factor and characterizes the relative diffusion degree of gas flowing through a blade cascade; 2. for the case where there is circumferential distortion, it is not possible to obtain only the radial distribution of the load, but it is necessary to obtain the spatial distribution of the load in the radial direction as well as in the circumferential direction to carry out the next work. Judging according to the spatial distribution of the compressor load, and returning to S3 if the load of the whole compressor or any local area does not reach the local critical load; and if the load of the whole or local area of the compressor reaches the local critical load, the compressor is unstable and outputs the last stable point. The local critical load is the local load when the compressor is locally unstable.
S5: obtaining a last stable point and a first unstable point, and when the throttling step length between the last stable point and the first unstable point is small enough, taking the last stable point as a prediction stable boundary of the compressor under the condition of intake distortion; otherwise, returning to S3, the exit average static pressure is adjusted between the last stable point and the first unstable point during calculation.
The invention also provides a system of the compressor stable boundary prediction method for the intake air distortion condition and a readable storage medium, wherein the system comprises executable instructions which can be executed to cause a computer to execute the operations of the compressor stable boundary prediction method for the intake air distortion condition.
The invention also provides a computing device comprising one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors to perform operations included in a method of compressor stability boundary prediction of an intake distortion condition.
The engineer can also make the above method as executable instructions stored in a readable storage medium, which when executed, cause a computer to perform the operations involved in the above compressor stability margin prediction method of intake air distortion case. Or one or more programs stored in the memory and configured to be executed by the one or more processors to perform operations included in the above-described method for compressor stability boundary prediction of intake air distortion conditions. The memory and the processor are included in a computing device.
Description of specific embodiments: a transonic single-stage compressor is taken as a research object, and the stable boundary prediction is carried out on 88% of the designed rotating speed of the intake distortion condition constructed by using an inlet annular distortion screen.
The method aims at single-channel steady Reynolds average numerical simulation under the condition of uniform air intake of the compressor rotor, and extracts a distributed volume force source term
And constructing a matrix comprising tangential volumetric forces
Volume force along isoflow direction coordinate plane
And volume force along equal blade height
The above S1-S3 steps are performed. The inlet boundary conditions give the total temperature, total pressure distribution (as shown in fig. 5) and velocity direction (axial inlet), and the outlet boundary conditions give the average static pressure conditions.
And judging whether the pressure ratio of the whole or local area of the compressor reaches the local critical pressure ratio or not according to the load space distribution. For the compressor, earlier experimental research shows that the compressor respectively generates two destabilization processes starting from a blade tip and a blade root under the conditions of 88% of designed rotating speed and different load distribution, the critical pressure ratio when the blade tip is destabilized is 1.49, and the critical pressure ratio when the blade root is destabilized is 1.42. The radial distribution of the pressure ratios at a plurality of flow points obtained by calculation is given here as shown in fig. 6. It can be seen from the figure that when the flow rate is 9.43kg/s, the pressure ratio of the blade tip and the blade root does not reach the local critical value, and the compressor is in a stable state; when the flow is further throttled to 8.90kg/s, the tip pressure ratio exceeds 1.49, the compressor is judged to be unstable, and the initial unstable position is a tip area; and obtaining the working point when the tip pressure ratio is closest to the critical value by adjusting the back pressure in the flow range, wherein the flow is 9.04kg/s, and taking the working point as a prediction stable boundary of the compressor under the intake distortion condition, wherein the distortion condition comprises non-uniform inlet total pressure and velocity distribution.
The prediction of the stable boundary of the compressor under the intake distortion condition is completed in the steps, in order to verify the accuracy of the result, a characteristic line of the compressor obtained by the test is given and shown in fig. 7, and the prediction boundary is marked by an asterisk, so that the prediction boundary (9.04kg/s) is close to the test result (8.92kg/s), the error is within 2 percent and the prediction boundary is conservative estimation, which shows that the prediction method has reasonable result and the prediction accuracy can meet the requirement. Meanwhile, under the condition that a volume force source item of the compressor is obtained, the time required by the process is within 5 hours, and compared with an unsteady RANS numerical simulation method, the prediction efficiency is improved by more than 10 times.
It should be understood that the various techniques described herein may be implemented in connection with hardware or software or, alternatively, with a combination of both. Thus, the methods and apparatus of the present invention, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium, wherein, when the program is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the invention.
In the case of program code execution on programmable computers, the computing device will generally include a processor, a storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. Wherein the memory is configured to store program code; the processor is configured to perform the various methods of the present invention according to instructions in the program code stored in the memory.
By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer-readable media includes both computer storage media and communication media. Computer storage media store information such as computer readable instructions, data structures, program modules or other data. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. Combinations of any of the above are also included within the scope of computer readable media.
It should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various disclosed aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, disclosed aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules or units or components of the devices in the examples disclosed herein may be arranged in a device as described in this embodiment or alternatively may be located in one or more devices different from the devices in this example. The modules in the foregoing examples may be combined into one module or may be further divided into multiple sub-modules.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
Furthermore, some of the described embodiments are described herein as a method or combination of method elements that can be performed by a processor of a computer system or by other means of performing the described functions. A processor having the necessary instructions for carrying out the method or method elements thus forms a means for carrying out the method or method elements. Further, the elements of the apparatus embodiments described herein are examples of the following apparatus: the apparatus is used to implement the functions performed by the elements for the purposes of this disclosure.
As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.
Claims (10)
1. A compressor stable boundary prediction method for intake distortion conditions is characterized by comprising the following steps:
s1, under the condition that the air compressor uniformly admits air, the constant Reynolds average method is adopted to calculate and obtain the flow field parameters of the air compressor
S2, constructing a distributed force source volume force model according to the compressor flow field parameters and the blade parameters, and outputting the distributed force source volume force;
s3, calculating a blade domain by adopting the volume force model of the distributed force source, calculating a non-blade domain by adopting a Reynolds average method, and giving a distortion condition required by a target condition to an inlet boundary condition so as to obtain the spatial distribution of the load of the compressor;
s4, judging according to the space distribution of the compressor load, if the load of the whole compressor or any local area does not reach the local critical load, returning to S3 and increasing the average static pressure of the outlet for recalculation; and if the load of the whole or local area of the compressor reaches the local critical load, the compressor is unstable and outputs the last stable point.
2. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: the compressor flow field parameters and the blade parameters comprise local radius of the blade, circumferential angle coordinates of the blade, surface pressure of the blade, projection speed of local speed of airflow along a meridian plane, local tangential speed of the blade, local tangential speed of the airflow, local static temperature, local airflow density, airflow speed under a local relative coordinate system, entropy gradient along the flow direction, and Mach number corresponding to the local flow direction speed.
3. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: the non-blade area comprises all areas from the inlet of the compressor to the front edge of the first row of blade areas, between the adjacent blade areas and from the tail edge of the last row of blade areas to the outlet of the compressor.
4. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: the local critical load is the local load when the compressor is locally unstable.
5. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: also comprises the following steps of (1) preparing,
s5, obtaining the last stable point and the first unstable point, and taking the last stable point as the prediction stable boundary of the compressor under the intake distortion condition when the throttling step length between the two points is small enough; otherwise, return to S3.
6. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: the distributed force source volume force comprises tangential volume force of the blade to the fluid, volume force along an equidirectional coordinate plane and volume force along an equivane height plane.
7. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: the interface between the blade area and the non-blade area is a curved surface formed after the projection of the front edge and the rear edge of the blade on the meridian plane rotates for one circle along the circumferential direction.
8. The compressor stability boundary prediction method for intake air distortion conditions as claimed in claim 1, wherein: the inlet boundary condition gives total temperature, total pressure distribution and speed direction, the outlet boundary condition gives average static pressure condition, and the simulation of the throttling process of the compressor is realized by reducing the outlet static pressure, and the solid wall boundary including the casing and the hub is the non-slip boundary condition.
9. A readable storage medium having executable instructions thereon that, when executed, cause a computer to perform the operations included in any one of claims 1-8.
10. A computing device, comprising:
one or more processors;
a memory; and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors to perform operations as recited in any of claims 1-8.
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| CN109815624A (en) * | 2019-02-21 | 2019-05-28 | 南京航空航天大学 | A kind of compressor stability boundaris judgment method for considering inlet total pressure distortion and influencing |
| CN111859567A (en) * | 2020-07-20 | 2020-10-30 | 北京航空航天大学 | Volume force construction method, computing device and readable storage medium |
| CN113609623A (en) * | 2021-08-26 | 2021-11-05 | 北京航空航天大学 | Processing casing design evaluation method based on fixed-time effect quantitative description |
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| CN109815624A (en) * | 2019-02-21 | 2019-05-28 | 南京航空航天大学 | A kind of compressor stability boundaris judgment method for considering inlet total pressure distortion and influencing |
| CN111859567A (en) * | 2020-07-20 | 2020-10-30 | 北京航空航天大学 | Volume force construction method, computing device and readable storage medium |
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