Simplified modeling method, apparatus and computer program product for complex mixed fuel combustion reaction kinetics modeling

Abstract

The application provides a simplified modeling method, device and computer program product of a complex mixed fuel combustion reaction kinetics model. The simplified modeling method comprises the following steps: model coupling, one-time simplification of the model by using an error transmission-based directed relationship diagram method and a species sensitivity analysis method, optimization of the one-time simplified model by taking the optimal pre-exponential factor, temperature index and activation energy of the three-parameter modified Arrhenius equation as optimization objects, and re-simplification of the optimized model. The application adopts a method for directly simplifying a complex model, does not need to artificially disassemble and construct the model, does not need to perform in-depth reaction path analysis, does not need to perform program writing, is suitable for combustion simulation engineering practitioners without a combustion reaction kinetics research foundation, is used to quickly produce a fuel mechanism model, and is reasonably verified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of reaction kinetics modeling, in particular to a complex mixed fuel combustion reaction kinetics model simplification modeling method, device and computer program product. BACKGROUND

[0002] Currently, the combustion chamber design process cannot be separated from three-dimensional CFD (Computational Fluid Dynamics) numerical simulation, and the combustion model in numerical simulation needs the participation of reaction kinetics mechanism model. In the model with direct solving of reaction rate as the core calculation method, the calculation efficiency is negatively correlated with the number of components and the number of elementary reactions of the mechanism model used. If a chemical reaction kinetics model with a large number of elementary reaction steps is used, it will cause the problem of too long calculation time, and even insufficient computing resources. Therefore, when performing simulation calculation, the number of elementary reactions of the reaction kinetics model used by the technical personnel is generally below 100 steps. However, when performing combustion simulation calculation of new type of component fuel, the existing traditional fuel mechanism model cannot be directly used for simulation calculation, which requires researchers to use a substitute component mechanism model of new type of fuel or splice other admixture mechanism model to the traditional fuel mechanism model to achieve the purpose of making a new type of fuel mechanism model. Since a detailed mechanism model is generally used for splicing when making a new fuel mechanism model, in order to reduce the complexity of simulation calculation, it is necessary to simplify the chemical reaction kinetics model.

[0003] The conventional simplification method generally uses sensitivity analysis, path analysis, decoupling method, isomer lumping method and the like in combination, for example, Chinese invention patent applications with publication numbers CN 117524330 A, CN 118335212 A and CN 116978473 A. These methods generally require researchers to have relatively deep chemical kinetics professional knowledge to perform dynamics calculation or switch to use multiple software and methods for programming modeling, and it is extremely difficult for general engineering technical personnel to use traditional methods to construct and simplify the proxy model in a short time when performing simulation calculation. SUMMARY

[0004] Since the prior art has the above-mentioned defects, the present application provides a complex mixed fuel combustion reaction kinetics model simplification modeling method, device and computer program product, which adopts a method of directly simplifying a complex model, without the need for artificial disassembly and construction of the model; without the need for in-depth reaction path analysis, without the need for programming, and can be automatically realized by means of ANSYS software, suitable for combustion simulation engineering practitioners without a foundation in combustion reaction kinetics research, to quickly make a fuel mechanism model and perform reasonable verification.

[0005] To achieve the above object, in a first aspect, the application provides a simplified modeling method of complex mixed fuel combustion reaction kinetics model, comprising the following steps:

[0006] Step S1, model coupling: selecting a model according to the mechanism of complex mixed fuel combustion reaction to obtain a detailed fuel combustion reaction kinetics model; removing repeated components and repeated elementary reactions to obtain a detailed fuel combustion reaction kinetics model to be simplified;

[0007] Step S2, simplifying the model obtained in S1: removing redundant components and elementary reactions by using the directed relation graph method based on error propagation and species sensitivity analysis; the target components are selected as the substitute components of fuel, oxidizer, main combustion products and main intermediate products;

[0008] Step S3, optimizing the model obtained in S2: identifying the elementary reactions to be optimized by reaction rate and sensitivity analysis; calculating and optimizing the pre-exponential factor A, temperature index N and activation energy E of the three-parameter modified Arrhenius equation of each elementary reaction to be optimized by using genetic algorithm a ; substituting the optimal pre-exponential factor A, temperature index N and activation energy E a into the rate constant equation corresponding to the elementary reaction to be optimized to obtain the optimized elementary reaction;

[0009] Step S4, simplifying the model obtained in S3: performing chemical reaction path rationality analysis; performing sensitivity analysis on the optimized model with reasonable reaction path to find the key components of the model; adding the key components to the target component set of model simplification; and simplifying the model again by using the directed relation graph method based on error propagation and species sensitivity analysis;

[0010] Step S5, verifying the model obtained in S4: when the verification fails, returning to steps S2 to S4.

[0011] By using the above technical solution, the directed relation graph method based on error propagation and species sensitivity analysis is used in step S2 to simplify the model, which can effectively avoid the problems of large calculation amount and calculation divergence caused by global sensitivity analysis and reaction path analysis, ensure the accuracy of model simplification and significantly reduce the calculation amount of simplification.

[0012] In general optimization methods, direct optimization of rate constants is often used to match simplified models under target operating conditions with detailed models. In chemical kinetics, the reaction rate constant K is a function of temperature T. Therefore, directly modifying the rate constant can distort the simulation results of the optimized model under a wide range of operating conditions and is ineffective when simulating diffusion flames with a large temperature range. The optimization process in step S3 optimizes the optimal pre-exponential factor, temperature exponent, and activation energy of the three-parameter modified Arrhenius equation, avoiding the problem of model distortion over a wide temperature range caused by direct optimization of the rate constant.

[0013] Furthermore, step S2 includes the following sub-steps:

[0014] Step S2-1, importing the model obtained in step S1 into simulation software, and performing subsequent simulation calculations using a closed homogeneous reactor model;

[0015] Step S2-2: using a directed relationship graph method based on error propagation and a species sensitivity analysis method to remove redundant components and elementary reactions; during the simplification process, the target components are selected as alternative components of the fuel, oxidant, main combustion products, and main intermediates;

[0016] Step S2-3: Set a simplified initial operating condition based on the typical operating condition of the engineering calculation being performed, and then select a fault tolerance threshold to obtain a fuel skeleton mechanism model that is as small as possible. This fault tolerance threshold is selected to be a large value to obtain a fuel skeleton mechanism model that is as small as possible.

[0017] Furthermore, step S3 includes the following sub-steps:

[0018] Step S3-1, setting boundary conditions and selecting the target parameter as ignition delay time;

[0019] Step S3-2, identifying elementary reactions that need to be optimized through reaction rate and sensitivity analysis;

[0020] Step S3-3: Using a genetic algorithm, calculate and optimize the pre-exponential factor A, temperature index N, activation energy E of the three-parameter modified Arrhenius equation for each elementary reaction to be optimized identified in step S3-2. a ;

[0021] Step S3-4: Substitute the optimal pre-exponential factor, temperature index, and activation energy parameters obtained in S3-3 into the rate constant equation corresponding to the elementary reaction to be optimized, thereby obtaining the optimized elementary reaction; and replace the corresponding elementary reaction in the simplified model with the optimized elementary reaction to obtain the optimized model.

[0022] Furthermore, step S4 includes the following sub-steps:

[0023] Step S4-1, using a closed homogeneous reactor model, the model obtained in S3 is analyzed for chemical reaction path to verify the rationality of the reaction path; if the reaction path is not reasonable, it needs to return to step S2 again;

[0024] Step S4-2, according to the typical working condition of the engineering calculation, the boundary conditions are set, and the sensitivity analysis is carried out on the optimized model with reasonable reaction path to find the key components of the model;

[0025] Step S4-3, the key components determined in S4-2 are added to the target component set of mechanism simplification;

[0026] Step S4-4, the directed relation graph method based on error propagation and species sensitivity analysis method are used to simplify the model again, and a simplified complex mixed fuel combustion reaction dynamics model is obtained.

[0027] Further, the verification in step S5 includes but is not limited to zero-dimensional flame verification and one-dimensional flame verification.

[0028] Still further, the step S5 includes the following sub-steps:

[0029] Step S5-1, the model obtained in S4 is verified by zero-dimensional flame;

[0030] Step S5-2, according to the target working condition of the engineering calculation, the boundary conditions of the combustion are parameterized;

[0031] Step S5-3, ignition delay time calculation is carried out, and the simulation value of ignition delay time is compared with the simulation value of ignition delay time of the detailed reaction dynamics model of fuel combustion and the experimental value of ignition delay time; if the calculation result of ignition delay of the simplified mechanism model is within the allowable range of the detailed value and the experimental value, it is determined that the simplified mechanism model passes the zero-dimensional flame verification, otherwise, it returns to step S2;

[0032] Step S5-4, on the basis of the verification in S5-3, one-dimensional flame verification is carried out: laminar flame propagation speed is calculated, and the simulation value of laminar flame propagation speed of the simplified mechanism model and the detailed mechanism model is compared with the experimental measured value of laminar flame propagation speed of the fuel; if the calculation result of laminar flame propagation speed of the simplified mechanism model is within the allowable range of the detailed value and the experimental value, it is determined that the simplified mechanism model passes the one-dimensional flame verification, otherwise, it returns to step S2.

[0033] Still further, for the flame axial combustion emission concentration verification, two-dimensional flame verification is carried out; the step S5 further includes:

[0034] Step S5-5, on the basis of the verification in S5-4, using open source code or coaxial jet flame model in simulation software, two-dimensional flame verification is carried out: according to the engineering calculation target parameter, the boundary condition is set, the flame height, temperature field, soot concentration field, OH free radical concentration field calculation is carried out, and the test results of coaxial jet flame are compared and verified; if the error is within the allowable range, it can be determined that the model passes the two-dimensional flame verification, and it can be used for simulation calculation of engine pollutant emission.

[0035] In a second aspect, the present application provides an electronic device, comprising:

[0036] at least one processor; and

[0037] a memory connected with the at least one processor; wherein,

[0038] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the simplified modeling method of the complex mixed fuel combustion reaction kinetics model as described above.

[0039] In a last aspect, the present application provides a computer program product, when the computer program product runs on a computer, so that the computer executes the simplified modeling method of the complex mixed fuel combustion reaction kinetics model as described above.

[0040] Compared with the prior art, the present application has the following advantages or beneficial effects:

[0041] (1) The present application automatically simplifies the modeling with a complete detailed reaction model as the simplified object, without reaction class splitting and isomer lumping, which can effectively avoid the problem of human error caused by the lack of chemical reaction kinetics research by engineering and technical personnel; it is particularly suitable for quickly simplifying a complex chemical reaction kinetics model containing 5000 to 20000 elementary reactions to 300 steps or less;

[0042] (2) The present application uses the directed relationship graph method based on error propagation and the species sensitivity analysis method to simplify the model, which can effectively avoid the problems of large calculation amount and non-convergent calculation caused by global sensitivity analysis and reaction path analysis, ensure the model simplification precision and significantly reduce the simplification calculation amount;

[0043] (3) The mechanism optimization process of the present application takes the optimal pre-exponential factor, temperature index and activation energy of the three-parameter modified Arrhenius equation as the optimization object, which avoids the problem of model distortion in a wide temperature range caused by directly optimizing the rate constant. BRIEF DESCRIPTION OF DRAWINGS

[0044] The present application, its features and advantages will become more apparent upon reading the following detailed description of non-limiting embodiments thereof, with reference to the annexed drawings. In all the drawings, the same references refer to the same parts. The drawings are not to scale, the emphasis being on illustrating the principles of the present application.

[0045] Figure 1 Flow chart of the simplified modeling method of the complex mixed fuel combustion reaction kinetics model in an embodiment of the present application;

[0046] Figure 2 Main reaction path diagram of the complex mixed fuel combustion reaction kinetics model in an embodiment of the present application;

[0047] Figure 3 Shock tube ignition delay time verification result of the complex mixed fuel combustion reaction kinetics model in an embodiment of the present application. DETAILED DESCRIPTION

[0048] Exemplary embodiments of the present disclosure will be described in detail with reference to the drawings. It should be understood that all the described exemplary embodiments are only partial embodiments and examples of the present application, rather than all. Instead, these exemplary embodiments are provided so that those skilled in the art can have a more thorough understanding of the present disclosure and can more completely convey the technical content of the present disclosure to those skilled in the art.

[0049] In the following detailed description, many specific details are set forth in order to provide a more thorough understanding of the present application. However, it will be apparent to one skilled in the art that well-known algorithms or models (such as genetic algorithms, directed relation graphs, species sensitivity analysis, etc.) do not show detailed processes in order to avoid obscuring the main idea of the present application.

[0050] Embodiment 1

[0051] Reference Figure 1 The present embodiment provides a simplified modeling method of a complex mixed fuel combustion reaction kinetics model, comprising the following steps:

[0052] S1 Coupling of the model

[0053] S1-1, according to the different simulation calculation objects faced by the mechanism model, select the appropriate model coupling object. If the original model can simulate the characteristics of the calculation object, there is no need to couple other models.

[0054] S1-2, remove the repeated components and repeated elementary reactions of the fuel detailed reaction kinetics model obtained by S1-1 to obtain a simplified fuel detailed reaction kinetics model.

[0055] S2 Simplification of the model

[0056] S2-1, the fuel detailed reaction kinetics model obtained in S1 is imported into an extended module Reaction Workbench model simplification work area of Chemkin Pro software (part of ANSYS software package), and subsequent simulation calculation is carried out by adopting a closed homogeneous reactor model.

[0057] S2-2, a directed relationship graph method and a species sensitivity analysis method based on error transmission are adopted to remove redundant components and elementary reactions.

[0058] S2-3, in the simplification process, the target components are selected as substitute components of the fuel, oxidants, main combustion products and main intermediate products. The initial working condition of the simplification is set according to the typical working condition of the engineering calculation, and then a larger value is selected for the fault tolerance threshold, so as to obtain a fuel skeleton mechanism model as small as possible.

[0059] S3 Optimization of the model

[0060] The skeleton mechanism model obtained in S2 is imported into the Reaction Workbench model optimization work area, and subsequent simulation calculation is carried out by adopting a closed homogeneous reactor model.

[0061] S3-1, boundary conditions are set, and the target parameter is selected as the ignition delay time.

[0062] S3-2, on the basis of S3-1, the elementary reactions that need to be optimized are identified through reaction rate and sensitivity analysis.

[0063] S3-3, on the basis of S3-2, based on a genetic algorithm, the pre-exponential factor A, temperature index N and activation energy E of the three-parameter modified Arrhenius equation (equation 1) of each elementary reaction to be optimized are automatically calculated and optimized by the software a .

[0064] (1)

[0065] In equation 1, k is the chemical reaction rate constant, A is the frequency factor, also known as the pre-exponential factor, which is a constant independent of temperature, representing the maximum possible rate constant of the reaction if there is no activation energy barrier; T is the thermodynamic temperature, and R is the gas constant.

[0066] S3-4, the optimal pre-exponential factor, temperature index and activation energy parameters obtained in S3-3 are substituted into the rate constant equation of the elementary reaction to be optimized, that is, the optimized elementary reaction is obtained; the corresponding elementary reaction in the simplified model is replaced by the optimized elementary reaction, and the optimized model is obtained.

[0067] In chemical reaction kinetics, the rate constant of a elementary reaction is determined by the Arrhenius equation, which indicates the pre-exponential factor A, temperature exponent N and activation energy E a Commonly control the trend of reaction rate with temperature. By optimizing these three parameters through algorithm, the experimental data and theoretical model can be accurately matched, and the kinetic behavior of elementary reactions in complex mechanism (such as product generation path, energy barrier) is closer to the actual system, so as to improve the prediction accuracy and reliability of the overall reaction mechanism model. Replace the corresponding elementary reactions in the simplified model with the optimized elementary reactions to obtain the optimized skeletal mechanism model.

[0068] S4 Secondary simplification of model

[0069] S4-1, in Chemkin Pro software, using closed homogeneous reactor model, the optimized skeletal mechanism model obtained by S3 is analyzed by chemical reaction path, and the rationality of the reaction path is verified. If the reaction path is not reasonable, it needs to return to S2.

[0070] S4-2, according to the typical working condition of the engineering calculation, set the boundary condition, the optimized skeletal mechanism model with reasonable reaction path is analyzed by sensitivity analysis, and the key components of the optimized skeletal mechanism model are found.

[0071] S4-3, add the key components determined by S4-2 to the target component set of mechanism simplification.

[0072] S4-4, use the error transmission based directed relation graph method and species sensitivity analysis method to simplify the mechanism model again, and get the simplified mechanism model.

[0073] S5 verification of model

[0074] S5-1, the fuel simplified mechanism model obtained by S4 is verified by zero-dimensional flame, and the closed homogeneous reactor model in Chemkin Pro software is used to simulate the calculation of zero-dimensional flame.

[0075] S5-2, according to the target working condition of the engineering calculation, parameterize the boundary condition of combustion.

[0076] S5-3, ignition delay time calculation is carried out, and the simulation value of ignition delay time is compared with the simulation value of ignition delay time of detailed reaction kinetics model and the experimental value of ignition delay time. If the calculation result of ignition delay time of simplified mechanism model is within the allowable range compared with the detailed value and experimental value, it can be determined that the simplified mechanism model passes the zero-dimensional flame verification, otherwise, the model simplification needs to be carried out again.

[0077] S5-4, on the basis of the verification in S5-3, one-dimensional flame verification is carried out, and a counterflow flame model is selected in the Chemkin Pro software for simulation calculation. The laminar flame propagation speed is calculated, and the simulation values of the laminar flame propagation speed of the simplified mechanism model and the detailed mechanism model are compared with the measured values of the laminar flame propagation speed of the fuel. If the calculation result of the laminar flame propagation speed of the simplified mechanism model is within the allowable range of the detailed value and the test value, it is determined that the simplified mechanism model passes the one-dimensional flame verification, otherwise, the mechanism simplification needs to be re-performed.

[0078] S5-5, if flame axial combustion emission concentration verification is required, two-dimensional flame verification is required, otherwise it is skipped. On the basis of S5-4, the same coaxial jet flame model in the open source code or simulation software is used for two-dimensional flame verification. According to the target parameters of engineering calculation, the boundary conditions are set, the flame height, temperature field, soot concentration field and OH radical concentration field are calculated, and compared with the test results of the coaxial jet flame. If the error is within the allowable range, it is determined that the simplified mechanism model passes the two-dimensional flame verification, and it can be used for simulation calculation of engine pollutant emission.

[0079] The following takes aviation kerosene RP-3 as an example to explain the above-mentioned simplified modeling method in detail, so that those skilled in the art can understand the technical solutions and technical effects of the present application.

[0080] S1 Coupling of the model

[0081] S1-1, according to the different simulation calculation objects of the mechanism model, the appropriate coupling object of the model is selected.

[0082] The target chemical reaction kinetics simplified model of the present example needs to be used for simulation calculation of the soot particle characteristics of the jet flame, so the RP-3 combustion reaction kinetics model that has been effectively verified is coupled with the model containing polycyclic aromatic hydrocarbon growth. The present example selects a four-component substituted RP-3 detailed reaction kinetics model, and the substituted components of the model are composed of 27.44% (mole fraction) n-dodecane, 28.81% isododecane, 26.12% decalin, and 17.63% butylbenzene. The model contains 3056 components and 11898 elementary reactions.

[0083] S1-2, the RP-3 detailed reaction kinetics model obtained by coupling S1-1 is removed from repeated components and repeated elementary reactions to obtain the RP-3 detailed reaction kinetics model containing polycyclic aromatic hydrocarbon growth. The model contains 3017 components and 12168 elementary reactions.

[0084] S2 Simplification of the model

[0085] S2-1, the fuel detailed kinetic model obtained in S1 is imported into the Reaction Workbench model simplification field of Chemkin Pro software, and subsequent simulation calculation is carried out by adopting a closed homogeneous reactor model.

[0086] S2-2, the directed relationship graph method and species sensitivity analysis method based on error transmission are adopted to remove redundant components and elementary reactions.

[0087] S2-3, in the simplification process, the target components are selected as fuel substitute components NC12H26 (n-dodecane), PMH (isododecane), DECALIN (decalin), C6H5C4H9 (butylbenzene), oxidants N2 and O2, main combustion products CO2, CO, H2O, main intermediate products C2H2, C2H4, CH4, HO2, OH and polycyclic aromatic hydrocarbon precursor components BAPYR, BAPYR*S and BGHIF.

[0088] According to the engineering calculation target working condition, a simplified initial working condition is set. In this example, the initial working condition is selected as shown in Table 1. A RP-3 fuel skeleton mechanism model is obtained by taking a fault tolerance threshold of 20%, and the model contains 439 components and 2206 reactions.

[0089] Table 1 Initial working condition table for mechanism model simplification calculation

[0090]

[0091] S3 Optimization of the model

[0092] S3-1, the RP-3 skeleton mechanism model obtained in S2 is imported into the mechanism optimization field of Reaction Workbench, and subsequent simulation calculation is carried out by adopting a closed homogeneous reactor model.

[0093] S3-2, on the basis of S3-1, boundary conditions are set, and the target parameter is selected as the ignition delay time.

[0094] S3-3, on the basis of S3-2, the elementary reactions that need to be optimized are identified through rate and sensitivity analysis.

[0095] S3-4, on the basis of S3-3, based on a genetic algorithm, the software automatically calculates the optimal pre-exponential factor, temperature index and activation energy of the three-parameter modified Arrhenius equation of each elementary reaction to be optimized.

[0096] S3-5, the elementary reactions optimized in S3-3 are replaced by the corresponding elementary reactions in the simplified model to obtain an optimized skeleton mechanism model, and the tolerance between the model and the original model is 0.5%.

[0097] S4 Secondary simplification of the model

[0098] S4-1, the optimized skeleton mechanism model obtained in S3 is subjected to chemical reaction path analysis to verify the rationality of the reaction path. The reaction path of the present example is shown in Figure 2

[0099] S4-2, boundary conditions are set according to the target working condition of engineering calculation, and the optimized skeleton mechanism model with a reasonable reaction path is subjected to temperature sensitivity analysis in Chemkin Pro to find the key components of the optimized skeleton mechanism model.

[0100] S4-3, the key components determined in S4-2 are added to the target component set of mechanism simplification.

[0101] S4-4, the mechanism model is simplified again by using the error propagation-based directed relationship graph method and species sensitivity analysis method to obtain a simplified mechanism model. In the present example, the final simplified mechanism obtained by the above simplification method contains 288 components and 1619 elementary reactions.

[0102] S5 Verification of the model

[0103] S5-1, the RP-3 simplified mechanism model obtained in S4 is subjected to zero-dimensional flame verification. The closed homogeneous reactor model is used in Chemkin Pro to perform simulation calculation of zero-dimensional flame.

[0104] S5-2, the boundary conditions of combustion are parameterized according to the target working condition of engineering calculation.

[0105] S5-3, ignition delay time calculation is performed, and the simulation value of ignition delay time is compared with the simulation value and experimental value of ignition delay time of the detailed reaction kinetics model. If the calculation result of ignition delay time of the simplified mechanism model is within the allowable range of the detailed value and experimental value, it is determined that the simplified mechanism model has passed the zero-dimensional flame verification, otherwise, the model simplification needs to be performed again.

[0106] ​In this example, the ignition delay time of RP-3 and 21% oxygen concentration air mixture was calculated under the condition of T = 1100-1600 K, P = 1 atm, and under the condition of lean oil (Φ = 0.5), stoichiometric ratio (Φ = 1.0) and rich oil (Φ = 1.5) in turn, and compared with the ignition delay time data obtained by the shock tube test published in the papers of Chen et al. (Chen, B. H.; Liu, J. Z.; Yao, F.; He, Y.; Yang, W. J., Ignition delay characteristics of RP-3 under ultra-low pressure (0.01-0.1 MPa). Combustion and Flame 2019, 210, 126-133.) and Liu et al. (Liu, J.; Hu, E.; Yin, G.; Huang, Z.; Zeng, W., An experimental and kinetic modeling study on the low-temperature oxidation, ignition delay time, and laminar flame speed of a surrogate fuel for RP-3 kerosene. Combustion and Flame 2022, 237.), and the results are shown in Figure 3 The results show that the synthesized detailed mechanism can reflect the dependence of the ignition delay of RP-3 and 21% oxygen concentration air mixture on the equivalence ratio, which is consistent with the experimental trend; the ignition delay time obtained by the numerical calculation model of the simplified mechanism can predict the experimentally measured ignition delay time.

[0107] S5-4, on the basis of the verification of S5-3, one-dimensional flame verification is carried out. The counterflow flame model is selected in Chemkin Pro for simulation calculation. The laminar flame propagation speed is calculated, and the simulation values of the laminar flame propagation speed of the simplified mechanism model and the detailed mechanism model are compared with the experimentally measured values of the laminar flame propagation speed of the fuel. If the calculation results of the laminar flame propagation speed of the simplified mechanism model are within the allowable range of the detailed values and the experimental values, it is determined that the simplified mechanism model has passed the one-dimensional flame verification, otherwise, the mechanism simplification needs to be re-performed.

[0108] S5-5, on the basis of S5-4, two-dimensional flame verification is performed. In the present example, the calculation model is selected as an open-source two-dimensional coaxial jet flame calculation model. According to the test parameters, the boundary conditions are set as follows: fuel pipe inner diameter 5 mm, fuel outlet velocity 10.49 cm / s, air outlet velocity 21.62 cm / s, fuel temperature 540 K, air temperature 540 K, and oxygen volume fraction 23.5%, 21%, 20%, 19%, and 18.5% in sequence. Flame height, temperature field, soot concentration field, and OH radical concentration field are calculated, and compared with the test results of the coaxial jet flame. If the error is within the allowable range, it is determined that the simplified mechanism model has passed the two-dimensional flame verification, and can be used for simulation calculation of engine pollutant emission.

[0109] The present example designs a mechanism coupling method suitable for complex fuel containing benzene from the perspective of soot emission, and verifies the generation mechanism of the model with respect to soot precursors.

[0110] Embodiment 2

[0111] The present embodiment provides an electronic device, comprising:

[0112] at least one processor; and

[0113] a memory connected with the at least one processor in communication; wherein

[0114] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the simplified modeling method of the complex mixed fuel combustion reaction kinetics model as described in Embodiment 1.

[0115] In addition, each of the functional units in the embodiments of the present application can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0116] Optionally, the memory includes but is not limited to a high-speed random access memory, a nonvolatile memory. For example, one or more disk storage devices, flash memory devices or other nonvolatile solid-state storage devices; the processor includes but is not limited to a central processing unit (CPU), a network processor (NP), a graphics processing unit (GPU) and the like; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component.

[0117] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium. When the computer program product runs on a computer, it makes the computer execute the simplified modeling method of the complex mixed fuel combustion reaction kinetics model as described in Embodiment 1. The computer readable storage medium can include, but is not limited to, a floppy disk, an optical disk, a CD-ROM (compact disk read-only memory), a magneto-optical disk, a ROM (read-only memory), a RAM (random access memory), an EPROM (erasable programmable read-only memory), an EEPROM (electrically erasable programmable read-only memory), a magnetic card or an optical card, a flash memory, or other types of media / machine readable media suitable for storing machine executable instructions. The computer readable storage medium can be a product not connected to a computer device, or a component connected to a computer device.

[0118] In summary, the present application provides a simplified modeling method, device and computer program product of a complex mixed fuel combustion reaction kinetics model. The simplified modeling method includes model coupling, one-time simplification of the model using an error transmission-based directed relationship diagram method and species sensitivity analysis method, optimization of the one-time simplified model taking the optimal pre-exponential factor, temperature index and activation energy of the three-parameter modified Arrhenius equation as optimization objects, and re-simplification of the optimized model. The present application uses a method of directly simplifying a complex model, without the need for artificial disassembly and construction of the model; without the need for in-depth reaction path analysis, without the need for program writing, and is suitable for combustion simulation engineering practitioners without a foundation in combustion reaction kinetics research, to quickly produce a fuel mechanism model and perform reasonable verification.

[0119] The above describes the preferred embodiments of the present application. It should be understood that the present application is not limited to the specific embodiments described above, wherein the devices and structures not described in detail should be understood as being implemented in the ordinary way in the art; any person skilled in the art can make many possible changes and modifications to the technical solutions of the present application, or modify equivalent embodiments with equivalent changes, without departing from the scope of the technical solutions of the present application, which does not affect the essential content of the present application. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application, without departing from the content of the technical solutions of the present application, still belongs to the scope of protection of the technical solutions of the present application.

Claims

1. A simplified modeling method for a complex mixed fuel combustion reaction kinetic model, characterized in that: The following steps are involved: Step S1, model coupling: selecting a model according to the mechanism of the complex mixed fuel combustion reaction and coupling it to obtain a detailed reaction kinetics model of the fuel combustion; eliminating repeated components and repeated elementary reactions to obtain a detailed reaction kinetics model of the fuel combustion to be simplified; Step S2: simplify the model obtained in step S1: remove redundant components and elementary reactions using a directed relationship graph method based on error propagation and a species sensitivity analysis method; target components are selected as alternative components of the fuel, oxidant, main combustion products, and main intermediates; Step S3, optimize the model obtained in S2: identify the elementary reactions that need to be optimized through reaction rate and sensitivity analysis; use genetic algorithm to calculate and optimize the pre-exponential factor A, temperature index N, activation energy E of the three-parameter modified Arrhenius equation for each elementary reaction to be optimized a ; The optimal pre-exponential factor A, temperature index N, activation energy E a Substitute the rate constant equation corresponding to the elementary reaction to be optimized to obtain the optimized elementary reaction; Step S4, performing secondary simplification on the model obtained in S3: performing a rationality analysis on the chemical reaction path; performing a sensitivity analysis on the optimized model with a reasonable reaction path to find the key components of the model; adding the key components to the target component set for model simplification; and further simplifying the model using a directed relationship graph method based on error propagation and a species sensitivity analysis method; Step S5, verifying the model obtained in S4: if the verification fails, returning to steps S2 to S4; The step S3 includes the following sub-steps: Step S3-1, setting boundary conditions and selecting the target parameter as ignition delay time; Step S3-2, identifying elementary reactions that need to be optimized through reaction rate and sensitivity analysis; Step S3-3, using a genetic algorithm to calculate and optimize the pre-exponential factor A, temperature index N, and activation energy Ea of the three-parameter modified Arrhenius equation for each elementary reaction to be optimized identified in step S3-2; Step S3-4, substituting the optimal pre-exponential factor, temperature index, and activation energy parameters obtained in S3-3 into the rate constant equation corresponding to the elementary reaction to be optimized, thereby obtaining the optimized elementary reaction; replacing the elementary reaction corresponding to the simplified model with the optimized elementary reaction to obtain the optimized model; The step S4 includes the following sub-steps: Step S4-1: Use the closed homogeneous reactor model to perform chemical reaction path analysis on the model obtained in S3 to verify the rationality of the reaction path; if the reaction path is unreasonable, it is necessary to return to step S2; Step S4-2: setting boundary conditions according to typical working conditions of the engineering calculation being performed, performing sensitivity analysis on the optimized model with reasonable reaction paths, and finding the key components of the model; Step S4-3, adding the key components determined in S4-2 to the target component set of mechanism simplification; Step S4-4: using a directed relationship graph method based on error propagation and a species sensitivity analysis method to simplify the model again, and obtain a simplified complex mixed fuel combustion reaction kinetics model.

2. The simplified modeling method for a complex mixed fuel combustion reaction kinetic model according to claim 1, characterized in that: The step S2 includes the following sub-steps: Step S2-1, importing the model obtained in step S1 into simulation software, and performing subsequent simulation calculations using a closed homogeneous reactor model; Step S2-2: using a directed relationship graph method based on error propagation and a species sensitivity analysis method to remove redundant components and elementary reactions; during the simplification process, the target components are selected as alternative components of the fuel, oxidant, main combustion products, and main intermediates; Step S2-3: Set simplified initial operating conditions according to typical operating conditions of the engineering calculation being performed, and then select a fault tolerance threshold to obtain a fuel skeleton mechanism model that is as small as possible.

3. The simplified modeling method for a complex mixed fuel combustion reaction kinetic model according to claim 1, characterized in that: The verification in step S5 includes zero-dimensional flame verification and one-dimensional flame verification.

4. The simplified modeling method for a complex mixed fuel combustion reaction kinetic model according to claim 3, characterized in that: The step S5 includes the following sub-steps: Step S5-1, performing zero-dimensional flame verification on the model obtained in S4; Step S5-2: parameterize the combustion boundary conditions according to the target operating conditions of the engineering calculation; Step S5-3: Calculate the ignition delay time and compare the simulated value of the ignition delay time with the simulated value of the ignition delay time of the detailed fuel combustion reaction kinetics model and the experimental value of the ignition delay time; if the difference between the calculated ignition delay result of the simplified mechanism model and the detailed value and the experimental value is within the allowable range, it can be determined that the simplified mechanism model has passed the zero-dimensional flame verification; otherwise, return to step S2; Step S5-4: Based on the verification in S5-3, perform one-dimensional flame verification: calculate the laminar flame propagation velocity, and compare the laminar flame propagation velocity simulation values ​​of the simplified mechanism model and the detailed mechanism model with the laminar flame propagation velocity experimental measurement value of the fuel; If the difference between the calculated laminar flame propagation velocity result of the simplified mechanism model and the detailed value and the test value is within the allowable range, it can be determined that the simplified mechanism model has passed the one-dimensional flame verification; otherwise, the process returns to step S2.

5. The simplified modeling method for a complex mixed fuel combustion reaction kinetic model according to claim 4, characterized in that: For verification of the concentration of axial combustion emissions from the flame, two-dimensional flame verification is performed; the step S5 further includes: Step S5-5: Based on the verification in S5-4, use the coaxial jet flame model in the open source code or simulation software to perform two-dimensional flame verification: set boundary conditions according to the engineering calculation target parameters, calculate the flame height, temperature field, soot concentration field, and OH radical concentration field, and compare and verify with the test results of the coaxial jet flame; if the error is within the allowable range, it can be determined that the model has passed the two-dimensional flame verification and can be used for simulation calculations of engine pollutant emissions.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the simplified modeling method of the complex mixed fuel combustion reaction kinetic model according to any one of claims 1 to 5.

7. A computer program product, characterized in that When the computer program product is run on a computer, the computer is enabled to execute the simplified modeling method of the complex mixed fuel combustion reaction kinetics model according to any one of claims 1 to 5.

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