A flame surface database construction method, device, equipment and storage medium

Abstract

The present application discloses a flame surface database construction method, device, equipment and storage medium, which relates to the technical field of database management, including: based on a preset data segmentation method, respectively performing data partition processing on the discrete post-mixing fraction space and scalar dissipation rate in the target thermal system to obtain a data base point composed of the post-partitioning mixing fraction and the post-partitioning scalar dissipation rate; determining the constraint value set corresponding to the data base point according to the constraint flame surface equation corresponding to each constraint in the target thermal system; solving the constraint potential energy form equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value, and determining the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct the target flame surface database based on the temperature distribution and mass fraction distribution corresponding to the data base point. In this way, by reducing the dimension of the control equation describing the system from the number of components to the number of constraints, the dimension of the equation group to be solved is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of database management, and in particular to a flame surface database construction method, device, equipment and storage medium. Background Art

[0002] In engineering, combustion generally occurs in turbulent flow, and there will be strong interactions between turbulence and combustion. However, until now, the study of the interaction mechanism between turbulence and combustion has not formed a scientific and clear understanding in theory. Since the early 1970s, when computational fluid dynamics was introduced to solve combustion problems, numerical simulation has gradually become an important method for studying turbulent combustion problems because it can provide more refined and comprehensive flow field parameter distribution. At present, among the turbulent combustion models commonly used in engineering, the mixed fraction model and the eddy dissipation model have small calculation amounts, but it is difficult to accurately simulate the non-steady-state combustion phenomena such as ignition, blowout, and reburning. Although the probability density transport model and the eddy dissipation conceptual model can consider the non-steady-state combustion phenomena at a small scale in detail, the huge amount of calculation is difficult to meet the actual needs of engineering. Since the flame surface model can be independent of the flow field calculation, even if the detailed chemical reaction kinetics are considered, it will not increase the amount of calculation, so it is widely used in engineering calculations and scientific research.

[0003] The flame surface model decouples turbulent combustion from fluid solution and converts the component equations into the mixture fraction space for solution and table building. However, for complex hydrocarbon fuels, the chemical reaction mechanism can contain hundreds of components, which means that hundreds of partial differential equations need to be solved simultaneously, which is still very computationally intensive. Therefore, how to simplify the dimensions of the flame surface equations to reduce the consumption of computational resources is a problem that needs to be solved. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a flame surface database construction method, device, equipment and storage medium, which can reduce the dimension of the control equation describing the system from the number of components to the number of constraints, thereby reducing the dimension of the equation group to be solved. The specific scheme is as follows:

[0005] In a first aspect, the present application discloses a flame surface database construction method, comprising:

[0006] Based on the preset data segmentation method, the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system are respectively partitioned to obtain data base points composed of the partitioned post-mixing fraction and the partitioned post-scalar dissipation rate;

[0007] Determining a set of constraint values ​​corresponding to the data base point according to constraint flame surface equations corresponding to the constraints in the target thermal system;

[0008] Solve the constraint potential energy form equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value, and determine the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution.

[0009] Optionally, the data partitioning process is performed on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system based on a preset data partitioning method to obtain data base points composed of the post-partitioning mixing fraction and the post-partitioning scalar dissipation rate, including:

[0010] Discretizing the mixture fraction space in the target thermodynamic system to obtain a discrete mixture fraction space, and partitioning the discrete mixture fraction space based on the distribution law of each component in the discrete mixture fraction space to obtain a partitioned mixture fraction;

[0011] Performing equal partitioning processing on the scalar dissipation rate in the target thermal system within a preset value range to obtain a partitioned scalar dissipation rate;

[0012] The combination of the post-partition mixing fraction and the post-partition scalar dissipation rate is determined as the data base point of the target flame surface database.

[0013] Optionally, partitioning the discrete post-mixing fraction space based on the distribution law of each of the components in the discrete post-mixing fraction space to obtain the partitioned mixing fraction includes:

[0014] The corresponding partitioning step is determined based on the distribution law of each component in the discrete post-mixing fraction space, and the discrete post-mixing fraction space is partitioned based on the partitioning step to obtain the partitioned mixing fraction.

[0015] Optionally, determining the set of constraint values ​​corresponding to the data base point according to the constraint flame surface equations corresponding to the constraints in the target thermal system includes:

[0016] Obtaining constraints in the target thermal system, and constructing constraint flame surface equations corresponding to the constraints according to the partitioned scalar dissipation rate in the data base point and the data values ​​of the constraints in the target thermal system;

[0017] Solve each of the constraint flame surface equations to obtain a constraint value set corresponding to the data base point.

[0018] Optionally, solving the constraint potential energy formal equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value includes:

[0019] Based on the component chemical potential of each constraint in the constraint value set, a constraint potential energy formal equation of each constraint is constructed, and based on the Lagrangian operator method, the equation group consisting of the constraint data value and the constraint potential energy formal equation is solved to obtain the corresponding constraint potential energy value.

[0020] Optionally, determining the mass fraction distribution of each component corresponding to the data base point in the target thermodynamic system based on the constrained potential energy value includes:

[0021] The concentration value of each component corresponding to the data base point in the target thermal system is determined based on the constrained potential energy value, and the concentration value is converted into a mass fraction to determine the mass fraction distribution of each component.

[0022] Optionally, solving the constraint potential energy form equation of each constraint in the constraint value set to obtain a corresponding constraint potential energy value, and determining the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution, includes:

[0023] Selecting a set of data base points from all data base points as target base points, and obtaining a set of target constraint values ​​corresponding to the target base points;

[0024] Solving the constraint potential energy form equation of each constraint in the target constraint value set to obtain a corresponding constraint potential energy value, and determining the mass fraction distribution of each component corresponding to the target base point in the target thermodynamic system based on the constraint potential energy value;

[0025] A group of unselected data base points are selected from all the data base points as new target base points, and the process jumps to the step of obtaining a set of target constraint values ​​corresponding to the target base points until there are no unselected data base points among all the data base points, so as to construct a target flame surface database based on the mass fraction distribution and temperature distribution corresponding to each of the target base points.

[0026] In a second aspect, the present application discloses a flame surface database construction device, comprising:

[0027] A data base point determination module is used to perform data partition processing on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system based on a preset data segmentation method to obtain a data base point composed of the post-partition mixing fraction and the post-partition scalar dissipation rate;

[0028] A constraint value set module, used to determine the constraint value set corresponding to the data base point according to the constraint flame surface equation corresponding to each constraint in the target thermal system;

[0029] A database construction module is used to solve the constraint potential energy form equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value, and determine the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution.

[0030] In a third aspect, the present application discloses an electronic device, comprising:

[0031] Memory, used to store computer programs;

[0032] A processor is used to execute the computer program to implement the flame surface database construction method mentioned above.

[0033] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program, wherein the computer program implements the aforementioned flame surface database construction method when executed by a processor.

[0034] It can be seen that in the present application, based on the preset data segmentation method, the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system are respectively partitioned to obtain the data base points composed of the partitioned post-mixing fraction and the partitioned post-scalar dissipation rate; the constraint value set corresponding to the data base point is determined according to the constraint flame surface equation corresponding to each constraint in the target thermal system; the constraint potential energy form equation of each constraint in the constraint value set is solved to obtain the corresponding constraint potential energy value, and the mass fraction distribution of each component corresponding to the data base point in the target thermal system is determined based on the constraint potential energy value, so as to construct the target flame surface database based on the temperature distribution and the mass fraction distribution corresponding to the data base point. In this way, by solving the constraint control equation, the distribution of various components in the mixture fraction space is obtained, and the flame surface database is established in combination with the probability density function. That is, by determining the constraint potential energy form equation of each constraint in the constraint value set, the mass fraction distribution of each component corresponding to the data base point in the target thermal system is determined, so as to reduce the dimension of the control equation of the thermal system from the number of components to the number of constraints, which can greatly reduce the dimension of the solution of the equation group. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0036] Figure 1 A flow chart of a flame surface database construction method disclosed in this application;

[0037] Figure 2 A flowchart of a specific flame surface database construction method disclosed in this application;

[0038] Figure 3 This is a schematic diagram of the structure of a flame surface database construction device disclosed in this application;

[0039] Figure 4 A structural diagram of an electronic device disclosed in this application;

[0040] Numbers in the figure: 11, data base point determination module; 12, constraint value set module; 13, database construction module; 20, electronic device; 21, processor; 22, memory; 23, power supply; 24, communication interface; 25, input and output interface; 26, communication bus; 221, operating system; 222, computer program. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] The rate-controlled constrained-equilibrium method (RCCE) is a chemical reaction dimensionality reduction method based on the second law of thermodynamics. The RCCE method believes that the elementary reactions in the chemical reaction system can be divided into fast reactions and slow reactions. The slow reaction, as the bottleneck of the evolution of the entire system, controls the advancement speed of the entire system. The time scale of the fast reaction is very small. Within the reaction time scale, the slow reaction can be considered to be in a "frozen" state, which will constrain the reaction system, while the slow reaction will develop the system into an equilibrium state under the constraint, which is called a constrained equilibrium state. It can be seen from the second law of thermodynamics that for a given thermodynamic system, under the same constraint, there is only one equilibrium state, at which the entropy of the system reaches its maximum value. Therefore, the constrained equilibrium state corresponds to the constraint one by one. It is only necessary to know how the constraints of the system change over time to know how the entire system (i.e., each component) advances over time. Therefore, based on this idea, this application will introduce a flame surface database construction method in which the dimension of the control equation is reduced from the number of components to the number of constraints.

[0043] See also Figure 1 As shown, the embodiment of the present application discloses a method for constructing a flame surface database, comprising:

[0044] Step S11: Based on a preset data segmentation method, data partitioning is performed on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system to obtain data base points composed of the post-partition mixing fraction and the post-partition scalar dissipation rate.

[0045] In this embodiment, the data partitioning process is performed on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system based on the preset data segmentation method to obtain the data base point composed of the partitioned post-mixing fraction and the partitioned post-scalar dissipation rate, including: discretizing the mixed fraction space in the target thermal system to obtain the discrete post-mixing fraction space, and partitioning the discrete post-mixing fraction space based on the distribution law of each component in the discrete post-mixing fraction space to obtain the partitioned post-mixing fraction; performing equal partitioning process on the scalar dissipation rate in the target thermal system within the preset value range to obtain the partitioned post-scalar dissipation rate; and determining the value combination of the partitioned post-mixing fraction and the partitioned post-scalar dissipation rate as the data base point of the target flame surface database. That is, the corresponding partitioning step is determined based on the distribution law of each component in the discrete post-mixing fraction space, and the discrete post-mixing fraction space is partitioned based on the partitioning step to obtain the partitioned post-mixing fraction. That is, firstly, the mixture fraction space z in the target thermal system is discretized, and then z is finely divided in the [0,0.3] region according to the spatial distribution law of each physical quantity in the mixture fraction space, and the partition step size is gradually increased in the [0.3,1] region. z. It should be noted that the physical quantities include the components plus temperature data. The segmentation step is dz=a×i b Calculate, where a is 10 -4 , b=1.5. Then, the scalar dissipation rate χ is evenly partitioned in the value range [0,0.25], and the region is evenly divided into 15 parts. Finally, each set of z and χ value combinations is used as a set of data base points of the flame surface database to construct the flame surface database.

[0046] Step S12: determining a set of constraint values ​​corresponding to the data base point according to constraint flame surface equations corresponding to the constraints in the target thermal system.

[0047] In this embodiment, the constraint value set corresponding to the data base point is determined according to the constraint flame surface equation corresponding to each constraint in the target thermal system, including: obtaining the constraints in the target thermal system, and constructing the constraint flame surface equation corresponding to each constraint according to the partitioned scalar dissipation rate in the data base point and the data value of the constraint in the target thermal system; solving the constraint flame surface equation to obtain the constraint value set corresponding to the data base point. That is, according to different values ​​of the scalar dissipation rate, the control equation of each constraint is constructed. Specifically, first, according to the partition step size z, discretize the constraint flame surface equation. Assume that the total number of constraints in the system is n c , the control equations can be written as follows for each constraint:

[0048] ;

[0049] Where χ is the value of the scalar dissipation rate at the base point, C i is the value of the ith constraint, is the reaction rate of the jth component, n s is the number of chemical components in the system, and ρ is the density. c ij is the coefficient of the jth component in the constraint matrix corresponding to the i-th constraint, and its value satisfies the following formula:

[0050] . (1)

[0051] Then, combined with the flame surface form of the energy equation, we can solve n c+1 By solving an ordinary differential equation, we can get the set of constraint values ​​corresponding to each set of z and χ, which will be used as the input value for the next step. c+1 An ordinary differential equation is given by n c The flame surface equation of the constraint + the flame surface equation of the temperature. The selection of constraints is based on chemical reaction kinetics. Common constraints include the number of carbon, hydrogen and oxygen elements, the number of moles, the number of fuels, the number of free radicals, etc. Each element in the constraint matrix represents the number of constraints contained in the substance. Taking the number of carbon elements as an example, if the jth component is C3H8, the corresponding coefficient a ij =3, if the jth component is H2O, then the corresponding coefficient a ij =0.

[0052] Step S13: Solve the constraint potential energy formal equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value, and determine the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution.

[0053] In this embodiment, based on the component chemical potential of each constraint in the constraint value set, the constraint potential energy formal equation of each constraint is constructed, and the equation group consisting of the data value of the constraint and the constraint potential energy formal equation is solved based on the Lagrangian operator method to obtain the corresponding constraint potential energy value. Based on the constraint potential energy value, the concentration value of each component corresponding to the data base point in the target thermal system is determined, and the concentration value is converted into a mass fraction to determine the mass fraction distribution of each component. Specifically, the constraint potential energy formal equations of all constraints are constructed as follows:

[0054] ;

[0055] Among them, is the chemical potential energy of the jth component, R is the gas constant, and T is the temperature. For each substance in the system, the constraint potential energy equation can be listed, and the Lagrangian operator method and equation (1) are used to solve the equation system to obtain each constraint potential energy The value of Solve to obtain the concentration of each component, where N j is the molar amount of the gas. Then the concentration value of each component is converted into a mass fraction distribution as the data corresponding to a data base point (z, χ) in the flame surface database.

[0056] For the entire database, there will be multiple data base points. Specifically, Figure 2 As shown, the step of solving the constraint potential energy form equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value, and determining the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution and the mass fraction distribution corresponding to the data base point, includes: selecting a group of data base points from all data base points as target base points, and obtaining a target constraint value set corresponding to the target base points; solving the constraint potential energy form equation of each constraint in the target constraint value set to obtain the corresponding constraint potential energy value, and determining the mass fraction distribution of each component corresponding to the target base point in the target thermal system based on the constraint potential energy value; selecting a group of data base points that have not been selected from all data base points as new target base points, and jumping to the step of obtaining the target constraint value set corresponding to the target base point, until there are no data base points that have not been selected among all data base points, so as to construct a target flame surface database based on the mass fraction distribution and temperature distribution corresponding to each of the target base points. That is, select a set of (z, χ) combinations and obtain the corresponding constraint value set {c1, c2, …, c nc}. As the benchmark constraint for solving the thermodynamic system. Construct the constraint potential energy form equations of all constraints and solve the Lagrangian operator (constraint potential energy) value { , ,…, }, as the next step input; according to the given constraint potential energy value, solve the concentration value of each component, convert the concentration value of each component into a mass fraction distribution, and use it as the data corresponding to a data base point (z, χ) in the flame surface database. Select the next set of base points until the concentration values ​​of each component corresponding to all data base points are converted into mass fraction distributions. Finally, according to the corresponding component distributions at different base points, combined with the temperature distribution of the point, the flame surface database is established.

[0057] It can be seen that in this embodiment, based on the preset data segmentation method, the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system are respectively partitioned to obtain data base points composed of the partitioned post-mixing fraction and the partitioned post-scalar dissipation rate; the constraint value set corresponding to the data base point is determined according to the constraint flame surface equation corresponding to each constraint in the target thermal system; the constraint potential energy form equation of each constraint in the constraint value set is solved to obtain the corresponding constraint potential energy value, and the mass fraction distribution of each component corresponding to the data base point in the target thermal system is determined based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution and the mass fraction distribution corresponding to the data base point. In this way, by solving the constraint control equation, the distribution of various components in the mixture fraction space is obtained, and the flame surface database is established in combination with the probability density function. That is, by determining the constraint potential energy form equation of each constraint in the constraint value set, the mass fraction distribution of each component corresponding to the data base point in the target thermal system is determined, so as to reduce the dimension of the control equation of the thermal system from the number of components to the number of constraints, which can greatly reduce the dimension of the solution of the equation group.

[0058] refer to Figure 3 The embodiment of the present application also discloses a flame surface database construction device, including:

[0059] A data base point determination module 11 is used to perform data partitioning processing on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system based on a preset data segmentation method to obtain a data base point composed of the post-partition mixing fraction and the post-partition scalar dissipation rate;

[0060] A constraint value set module 12, used to determine the constraint value set corresponding to the data base point according to the constraint flame surface equation corresponding to each constraint in the target thermal system;

[0061] The database construction module 13 is used to solve the constraint potential energy form equation of each constraint in the constraint value set to obtain the corresponding constraint potential energy value, and determine the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value, so as to construct a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution.

[0062] It can be seen that in this embodiment, by solving the constraint control equation, the distribution of various components in the mixture fraction space is obtained, and the flame surface database is established in combination with the probability density function. That is, by determining the constraint potential energy form equation of each constraint in the constraint value set, the mass fraction distribution of each component corresponding to the data base point in the target thermal system is determined, thereby reducing the dimension of the control equation of the thermal system from the number of components to the number of constraints, which can greatly reduce the dimension of the solution of the equation group.

[0063] In some specific embodiments, the data base point determination module 11 may specifically include:

[0064] A space partition processing submodule is used to discretize the mixture fraction space in the target thermodynamic system to obtain a discrete mixture fraction space, and partition the discrete mixture fraction space based on the distribution law of each component in the discrete mixture fraction space to obtain a partitioned mixture fraction;

[0065] A scalar dissipation rate partition processing unit, used for performing partition processing on the scalar dissipation rate in the target thermal system within a preset value range to obtain a partitioned scalar dissipation rate;

[0066] The data base point determination unit is used to determine the value combination of the post-partition mixing fraction and the post-partition scalar dissipation rate as the data base point of the target flame surface database.

[0067] In some specific embodiments, the space partition processing submodule can be specifically used to determine the corresponding partition step based on the distribution law of each component in the discrete post-mixing fraction space, and partition the discrete post-mixing fraction space based on the partition step to obtain the partitioned mixing fraction.

[0068] In some specific embodiments, the constraint value set module 12 may specifically include:

[0069] a flame surface equation construction unit, used for obtaining the constraints in the target thermal system, and respectively constructing the constraint flame surface equations corresponding to the constraints according to the partitioned scalar dissipation rate in the data base point and the data values ​​of the constraints in the target thermal system;

[0070] The equation solving unit is used to solve the constraint flame surface equations to obtain the constraint value set corresponding to the data base point.

[0071] In some specific embodiments, the database construction module 13 may specifically include:

[0072] A constraint potential energy value construction unit is used to construct a constraint potential energy formal equation for each constraint based on the component chemical potential energy of each constraint in the constraint value set, and solve the equation group consisting of the data value of the constraint and the constraint potential energy formal equation based on the Lagrangian operator method to obtain the corresponding constraint potential energy value.

[0073] In some specific embodiments, the database construction module 13 may specifically include:

[0074] The mass fraction solving unit is used to determine the concentration value of each component corresponding to the data base point in the target thermal system based on the constrained potential energy value, and convert the concentration value into a mass fraction to determine the mass fraction distribution of each component.

[0075] In some specific embodiments, the database construction module 13 may specifically include:

[0076] A target base point selection unit, used to select a group of data base points from all data base points as target base points, and obtain a target constraint value set corresponding to the target base points;

[0077] a mass fraction distribution determining unit, configured to solve a constraint potential energy form equation of each constraint in the target constraint value set to obtain a corresponding constraint potential energy value, and determine a mass fraction distribution of each component corresponding to the target base point in the target thermal system based on the constraint potential energy value;

[0078] A step jump unit is used to select a group of unselected data base points from all the data base points as new target base points, and jump to the step of obtaining a set of target constraint values ​​corresponding to the target base points until there are no unselected data base points among all the data base points, so as to construct a target flame surface database based on the mass fraction distribution and temperature distribution corresponding to each of the target base points.

[0079] Furthermore, the present application also discloses an electronic device. Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0080] Figure 4The present invention provides a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the flame surface database construction method disclosed in any of the above embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0081] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0082] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0083] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the flame surface database construction method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks.

[0084] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the flame surface database construction method disclosed above is implemented. For the specific steps of the method, reference may be made to the corresponding contents disclosed in the above embodiments, and no further description will be given here.

[0085] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0086] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0087] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0088] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0089] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A flame surface database construction method, characterized in that: include: Based on the preset data segmentation method, data partitioning is performed on the discrete mixed fraction space and the scalar dissipation rate in the target thermal system to obtain data base points composed of the partitioned mixed fraction and the partitioned scalar dissipation rate; the discrete mixed fraction space is the discrete mixed fraction space corresponding to the hydrocarbon fuel; the scalar dissipation rate is the scalar dissipation rate corresponding to the hydrocarbon fuel; Determine a constraint value set corresponding to the data base point, and determine a constraint potential energy value corresponding to each constraint in the constraint value set; the constraint potential energy value is a potential energy value determined based on a constraint potential energy form equation of each constraint in the constraint value set; Wherein, the determining of the constraint value set corresponding to the data base point includes: obtaining the constraints in the target thermal system, and constructing the constraint flame surface equations corresponding to each of the constraints according to the partitioned scalar dissipation rate in the data base point and the data value of the constraints in the target thermal system; solving the constraint flame surface equations to obtain the constraint value set corresponding to the data base point; The determining of the constraint potential energy value corresponding to each constraint in the constraint value set includes: Constructing a constraint potential energy form equation for each constraint based on the component chemical potential energy of each constraint in the constraint value set, and solving the equation system consisting of the data value of the constraint and the constraint potential energy form equation based on the Lagrangian operator method to obtain the corresponding constraint potential energy value; Determining the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constrained potential energy value; A target flame surface database is constructed based on the temperature distribution corresponding to the data base points and the mass fraction distribution.

2. The flame surface database construction method according to claim 1, characterized in that: The method of performing data partitioning on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system based on the preset data segmentation method to obtain data base points composed of the post-partitioning mixing fraction and the post-partitioning scalar dissipation rate includes: Discretizing the mixture fraction space in the target thermodynamic system to obtain a discrete mixture fraction space, and partitioning the discrete mixture fraction space based on the distribution law of each component in the discrete mixture fraction space to obtain a partitioned mixture fraction; Performing equal partitioning processing on the scalar dissipation rate in the target thermal system within a preset value range to obtain a partitioned scalar dissipation rate; The combination of the post-partition mixing fraction and the post-partition scalar dissipation rate is determined as the data base point of the target flame surface database.

3. The flame surface database construction method according to claim 2, characterized in that: The partitioning of the discrete post-mixing fraction space based on the distribution law of each component in the discrete post-mixing fraction space to obtain the partitioned mixing fraction includes: The corresponding partitioning step is determined based on the distribution law of each component in the discrete post-mixing fraction space, and the discrete post-mixing fraction space is partitioned based on the partitioning step to obtain the partitioned mixing fraction.

4. The flame surface database construction method according to claim 1, characterized in that: The determining, based on the constrained potential energy value, the mass fraction distribution of each component corresponding to the data base point in the target thermal system comprises: The concentration value of each component corresponding to the data base point in the target thermal system is determined based on the constrained potential energy value, and the concentration value is converted into a mass fraction to determine the mass fraction distribution of each component.

5. The flame surface database construction method according to any one of claims 1 to 4, characterized in that: Determine a constraint potential energy value corresponding to each constraint in the constraint value set; determine a mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constraint potential energy value; Constructing a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution, including: Selecting a set of data base points from all data base points as target base points, and obtaining a set of target constraint values ​​corresponding to the target base points; Solving the constraint potential energy form equation of each constraint in the target constraint value set to obtain a corresponding constraint potential energy value, and determining the mass fraction distribution of each component corresponding to the target base point in the target thermodynamic system based on the constraint potential energy value; A group of unselected data base points are selected from all the data base points as new target base points, and the process jumps to the step of obtaining a set of target constraint values ​​corresponding to the target base points until there are no unselected data base points among all the data base points, so as to construct a target flame surface database based on the mass fraction distribution and temperature distribution corresponding to each of the target base points.

6. A flame surface database construction device, characterized in that: include: A data base point determination module is used to perform data partition processing on the discrete post-mixing fraction space and the scalar dissipation rate in the target thermal system based on a preset data segmentation method, so as to obtain a data base point composed of the partitioned mixing fraction and the partitioned scalar dissipation rate; the discrete post-mixing fraction space is the discrete post-mixing fraction space corresponding to the hydrocarbon fuel; the scalar dissipation rate is the scalar dissipation rate corresponding to the hydrocarbon fuel; A constraint value set module, used to determine a constraint value set corresponding to the data base point, and determine a constraint potential energy value corresponding to each constraint in the constraint value set; The constraint potential energy value is a potential energy value determined based on a constraint potential energy formal equation of each constraint in the constraint value set; Wherein, the determining of the constraint value set corresponding to the data base point includes: obtaining the constraints in the target thermal system, and constructing the constraint flame surface equations corresponding to each of the constraints according to the partitioned scalar dissipation rate in the data base point and the data value of the constraints in the target thermal system; solving the constraint flame surface equations to obtain the constraint value set corresponding to the data base point; The determining of the constraint potential energy value corresponding to each constraint in the constraint value set includes: Constructing a constraint potential energy form equation for each constraint based on the component chemical potential energy of each constraint in the constraint value set, and solving the equation system consisting of the data value of the constraint and the constraint potential energy form equation based on the Lagrangian operator method to obtain the corresponding constraint potential energy value; A mass fraction determination module, used to determine the mass fraction distribution of each component corresponding to the data base point in the target thermal system based on the constrained potential energy value; A database construction module is used to construct a target flame surface database based on the temperature distribution corresponding to the data base point and the mass fraction distribution.

7. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the flame surface database construction method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the flame surface database construction method according to any one of claims 1 to 5.

Images