A method for constructing and simplifying a diesel / polyoxymethylene dimethyl ether alternative fuel reaction mechanism model

Abstract

The application discloses a method for constructing and simplifying a diesel / polyoxymethylene dimethyl ether alternative fuel reaction mechanism model, which comprises the following steps: step 1, constructing a detailed initial mechanism based on a TRF-PAH diesel alternative mechanism and a PODEn chemical kinetics mechanism; step 2, comparing and analyzing the results obtained by using multiple DRG mechanism simplification methods respectively, screening an optimal simplification method, simplifying the initial mechanism obtained in step 1 by using the optimal simplification method, and obtaining a first-stage simplified mechanism; step 3, further reducing the mechanism scale based on the first-stage simplified mechanism, and obtaining a second-stage simplified mechanism; step 4, optimizing the simulation target parameters with large errors in the second-stage simplified mechanism, and obtaining an optimized mechanism; and step 5, supplementing the error source species and related reactions deleted from the optimized mechanism, and obtaining a final simplified mechanism. The scheme can improve the prediction ability for multiple combustion characteristics.

Description

Technical Field

[0001] This invention belongs to the field of computer simulation technology for engine combustion processes, specifically relating to a method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels. Background Technology

[0002] Combustion is one of the most important energy utilization methods today, playing a vital role in transportation, industrial production, power supply, and national defense. Currently, over 80% of global energy is still obtained through combustion. However, the combustion of traditional fossil fuels produces pollutants such as nitrogen oxides, particulate matter, and unburned products, which adversely affect the environment and human health. Therefore, improving combustion efficiency and reducing pollutant emissions has become an important research direction in the field of combustion.

[0003] With increasingly stringent emission regulations and ever-increasing demands for energy efficiency, the development of efficient and clean new fuels has gradually become a research hotspot. Polyoxymethylene dimethyl ether (PODE) possesses characteristics such as high cetane number, high oxygen content, and low carbon emissions, and is considered a promising diesel alternative fuel or diesel additive. Blending PODE with traditional diesel fuel can improve the combustion process and reduce pollutant emissions. While there are numerous experimental studies on PODE blending with traditional fuels, research on the kinetic mechanisms related to the combustion of PODE-blended diesel fuel is relatively limited. Therefore, developing a reliable kinetic model is of great significance.

[0004] Fuel combustion is essentially a complex system composed of numerous chemical reactions. To reveal combustion mechanisms and predict combustion characteristics, researchers typically establish fuel combustion chemical kinetic mechanisms and utilize numerical simulations to study the combustion process. Since real diesel fuel consists of hundreds or even thousands of hydrocarbon compounds, directly establishing the chemical kinetic mechanism of real diesel is extremely difficult; therefore, alternative fuel methods are often used to describe the diesel combustion process. The development of diesel fuel substitutes has progressed from single-component substitutes like n-heptane and isooctane, to two-component substitutes, and then to three-component or more-component substitutes. With the increasing demands for combustion efficiency and pollution emission research, constructing multi-component alternative fuel mechanisms that can simultaneously characterize the features of traditional diesel and clean oxygenated fuels is of great significance.

[0005] To accurately describe the fuel combustion process, detailed chemical kinetic mechanisms typically involve a large number of species and reaction steps, often reaching hundreds or even thousands of species and thousands of reactions. While detailed mechanisms can achieve high simulation accuracy, directly applying them to multidimensional computational fluid dynamics (CFD) simulations results in enormous computational costs and leads to significant rigidity issues due to the large reaction timescales. Therefore, it is necessary to simplify detailed mechanisms, effectively reducing their scale while maintaining simulation accuracy, thereby improving numerical simulation efficiency and meeting the needs of engineering applications.

[0006] Currently, various simplification methods have been developed in the field of mechanism simplification, such as the direct relationship diagram method and sensitivity analysis. Different simplification methods employ different importance evaluation criteria, resulting in differences in the identification of key species and reaction pathways. Therefore, the simplification results obtained by different methods have certain limitations and are dependent on target parameters and operating conditions. Existing mechanism simplification studies mostly use ignition delay time as the main evaluation index, which has relatively limited synergistic constraints on multiple combustion characteristics and may lead to problems in simultaneously addressing different research objectives.

[0007] Current mechanistic simplification methods typically correct errors in predictions under certain operating conditions by readjusting simplification conditions, modifying simplification thresholds, or optimizing reaction rate parameters. However, these optimization processes usually require analyzing error sources based on prediction results under different operating conditions and adjusting relevant parameters multiple times. This process is highly empirically dependent and struggles to improve the efficiency of mechanism correction. Therefore, establishing a universally applicable and empirically independent mechanism construction and simplification process is of great significance. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels. This method aims to effectively reduce the scale of the mechanism while maintaining the accuracy of the simulation, and improves the predictive ability of the simplified mechanism for various combustion characteristics through an error optimization approach, thereby increasing the efficiency of numerical simulation calculations.

[0009] One objective of this invention is to provide a method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels. Includes the following steps: Step 1: Mechanism of TRF-PAH diesel substitute and PODE n Based on chemical kinetics, a detailed initial mechanism was constructed. Step 2: Using various DRG-type mechanism simplification methods, multiple sets of fuels are set to simplify the initial mechanism. The ignition delay time prediction error and mechanism scale are used as evaluation indicators to compare and analyze the results obtained by different simplification methods, select the optimal simplification method, and use the optimal simplification method to simplify the initial mechanism obtained in Step 1 to obtain a simplified mechanism. The ignition characteristic prediction capability is verified by ignition delay time under single-component, multi-component, and multi-operating-condition conditions. Step 3: Based on the simplified mechanism obtained in Step 2, the mechanism is further simplified under multiple fuels by using sensitivity analysis. By deleting low-sensitivity species and related reactions, the scale of the mechanism is reduced again, resulting in a secondary simplified mechanism. Step 4: Optimize the simulated target parameters that have large errors in the secondary simplification mechanism obtained in Step 3 to obtain the optimized mechanism. The optimization method is as follows: First, construct an important species candidate set by deleting the species in the sensitivity analysis method; Second, use the dichotomy method to gradually restore the species and related responses in the candidate species set to the secondary simplification mechanism, reconstruct the mechanism and verify the target parameters, and screen out the important species that have a greater impact on the target parameters. Step 5: Fully verify the optimization mechanism obtained in Step 4. Using the same optimization method as in Step 4, optimize the simulation error of laminar flame velocity. Through the process of identification, replenishment and verification, accurately identify the deleted error source species, replenish the deleted error source species and related reactions to optimize the mechanism, and obtain the final simplified mechanism.

[0010] As a preferred embodiment, in step 1, the three sub-mechanisms of n-heptane, isooctane, and toluene in the TRF-PAH diesel substitute mechanism are screened out; then the screened three sub-mechanisms are compared with PODE. n Mechanism coupling was performed, and duplicate species and reactions were removed to obtain the initial mechanism.

[0011] As a preferred embodiment, in step 2, the ignition delay time is verified using experimental data. The verification objects include single-component, two-component, and three-component systems. The single-component system is one of n-heptane, isooctane, toluene, or PODE3. The two-component system is one of n-heptane plus isooctane or n-heptane plus toluene. The three-component system is n-heptane, isooctane, and toluene.

[0012] As a preferred embodiment, in step 3, low-sensitivity species and reactions in the mechanism are removed by sensitivity analysis, and the obtained mechanism is used for simulation; then the simulation data is compared with the experimental data to verify the consistency between the simplified mechanism simulation by sensitivity analysis and the experimental data. The simulation data includes ignition delay time, laminar flame velocity and concentration of important component species.

[0013] As a preferred embodiment, the optimization method in step 4 is as follows: First, the source of error is determined by the error feedback of the target parameter, and an important species set is constructed by identifying and deleting species that are redundant in the simplification process from the first simplification mechanism to the second simplification mechanism. Secondly, a stepwise recovery, verification, and screening method was adopted. The species and related reactions in the candidate important species set were restored to the secondary simplified mechanism in batches using the dichotomy method. The mechanism was reconstructed and verified. By comparing the predicted results of the mechanism after supplementing the species and related reactions on ignition delay time and laminar flame velocity, key species and related reactions with important influence on the research target were identified, and error optimization was completed to obtain the optimized mechanism.

[0014] As a preferred embodiment, in step 3, the mechanism simplification program ReaxRed is used to further simplify the first-simplified mechanism to obtain the second-simplified mechanism.

[0015] The second objective of this invention is to provide a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels, which is obtained by using the reaction mechanism model construction and simplification method described in any of the above-mentioned methods.

[0016] As a preferred embodiment, the reaction mechanism model includes 121 species and 548 reactions.

[0017] Compared with the prior art, the present invention has at least the following beneficial effects: Firstly, this application utilizes the relatively mature mechanisms of traditional fuel substitutes and the PODE mechanism to construct and simplify a new, compact chemical kinetic model that can be directly used for CFD simulations, providing a reliable kinetic model foundation for the development of clean fuels incorporating traditional fuels. During the simplification process, extensive verification using multi-component, multi-condition, and multi-objective parameters enhances the wide applicability of the simplified mechanism across various operating conditions. The simplification process goes beyond conventional methods; instead, it proposes an error optimization approach based on the identification and compensation of key species and related reactions, improving the simulation accuracy while maintaining a low mechanism size. The chemical kinetic model constructed and simplified in this application has a small size while ensuring simulation accuracy, making it directly applicable to CFD numerical simulations. Unlike the commonly used simplification program CHEMKIN PRO, which can only simplify one group of fuels at a time, this simplification process relies on the ReaxRed mechanism simplification program, which can simplify multiple groups of fuels simultaneously, significantly saving simplification time and improving simplification efficiency.

[0018] Secondly, the simplification method proposed in this application includes an error optimization approach for key species screening and replenishment, which can significantly reduce simulation errors while barely affecting the scale of the simplified mechanism. The complete simplification process of this application differs from conventional simplification methods, and the incorporated optimization approach is universally applicable. This error optimization approach establishes a closed-loop process of error feedback, accurate identification of error sources, replenishment of species, and optimization of related reactions, which can assist conventional simplification methods. Adding this optimization measure to the simplification method enables rapid analysis of error sources and effective reduction of errors. The error feedback-oriented optimization and verification approach in this method is universally applicable, independent of the studied fuel system and the researcher's experience, and applicable to the post-processing optimization steps of various simplification methods such as DRG and PFA. After determining the target parameters to be optimized, a key species set is constructed across different simplification methods, and then the above optimization is performed. The optimization method for identifying error sources and reducing errors in this application is completely independent of experience. It only requires establishing a species set for species identified as redundant by the simplification method, screening important species in this set, and replenishing these important species and related reactions into the simplified mechanism, then verifying the simulation performance of the replenished mechanism. (Existing conventional simplification methods, such as DRG, can improve the accuracy of simplified mechanism simulations by adjusting thresholds, simulation conditions, and reaction rate parameters during the simplification process. However, some methods rely on the researchers' experience.) Third, the key species identified by this method can lay the foundation for further in-depth research on the interactions between different target parameters. For example, when C5H is added... 10 While the ignition delay time of n-heptane and toluene was improved by (1-pentene) and NC3H7CO (n-butyryl radical), it affected the laminar flame velocity of isooctane. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the reaction mechanism model construction and simplification method of the present invention; Figure 2 A comparison of ignition delay time of n-heptane and toluene binary components simulated by mechanism 118 with experimental data: under the conditions of temperature 800-1300K, equivalence ratio of 0.3, and pressure of 50 atm; Figure 3A comparison of ignition delay time of n-heptane and toluene binary components under the 120 mechanism simulation with experimental data: temperature 800-1300K, equivalence ratio 0.3, and pressure 50 atm. Figure 4 Comparison of isooctane laminar flame velocity simulated by mechanism 120 with experimental data: temperature 298K, pressure 1atm; Figure 5 Comparison of isooctane laminar flame velocity simulated by mechanism 121 with experimental data: temperature 298K, pressure 1atm; Figure 6 Comparison of ignition delay time of PODE3 simulated for mechanism 121 with experimental data: under the conditions of temperature 600-1200K, pressure 10atm, and equivalence ratio of 1.5; Figure 7 A comparison of ignition delay time of n-heptane simulated by mechanism 121 with experimental data: under the conditions of temperature 700-1500K, pressure 40bar, and equivalence ratio of 1.0; Figure 8 A comparison of ignition delay time and experimental data for PRF90 (0.1 molar fraction of n-heptane and 0.9 molar fraction of isooctane) simulated by mechanism 121: under the conditions of temperature 700-1500K, pressure 40bar, and equivalence ratio of 1.0; Figure 9 Comparison of ignition delay time of toluene simulated by mechanism 121 with experimental data: under the conditions of temperature 1000-1400K, pressure 50atm, and equivalence ratio of 0.25; Figure 10 A comparison of ignition delay time of isooctane simulated by mechanism 121 with experimental data: under the conditions of temperature 700-1500K, pressure 40bar, and equivalence ratio of 1.0; Figure 11 Comparison of laminar flame velocity in PODE3 simulated by mechanism 121 with experimental data: under the conditions of pressure 1 atm and temperature 408 K; Figure 12 Comparison of laminar flame velocity of n-heptane simulated by mechanism 121 with experimental data: under the conditions of pressure 1 atm and temperature 298 K; Figure 13 Comparison of laminar flame velocity of toluene simulated by mechanism 121 with experimental data: under the conditions of pressure 1 atm and temperature 298 K. Detailed Implementation

[0021] The present invention will now be described in detail through exemplary embodiments. However, it should be understood that, without further description, elements, structures, and features in one embodiment may be advantageously incorporated into other embodiments.

[0022] It should be noted that, unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "a," "an," or "the," and similar words used in the specification and claims of this patent application do not express a limitation of quantity, but rather indicate the presence of at least one. Terms such as "comprising" or "including" indicate that the elements or objects preceding "comprising" encompass the elements or objects listed following "comprising" or "including" and their equivalents, but do not exclude other elements or objects having the same function.

[0023] This invention provides a simplified method for modeling the mechanism of PODE (polyoxymethylene dimethyl ether) blended diesel alternative fuel, the method comprising the following steps: Step 1: Detailed Mechanism Construction. The detailed mechanism of PODE and the mechanism of diesel substitutes are coupled to obtain the detailed mechanism of PODE blended with diesel substitute fuel.

[0024] The detailed mechanisms of PODE and diesel substitutes were screened and coupled, and the resulting detailed mechanisms were verified. The PODE mechanism developed by He et al. was selected. nThe mechanism comprises 225 species and 1082 reactions, covering the essential medium- and low-temperature range for combustion simulation. The diesel substitute mechanism selected is the TRF-PAH mechanism developed by Wang et al., a relatively mature and widely accepted mechanism for diesel / gasoline substitutes. This mechanism comprises 109 species and 543 reactions, and is composed of n-heptane, isooctane, toluene, and PAH mechanisms. This invention will use the n-heptane, isooctane, and toluene mechanisms as some of the fundamental mechanisms for constructing the detailed mechanism of this invention. Since the core mechanisms of the PODE and TRF-PAH mechanisms are derived from the AramcoMech mechanism, the coupling process can effectively reduce the impact of differences in core mechanisms (the AramcoMech mechanism is a series of detailed chemical kinetic mechanisms developed by the Combustion Chemistry Centre of the National University of Ireland for Saudi Aramco, mainly used to accurately describe the combustion characteristics of C1-C4 basic hydrocarbons and oxygenated fuels). The coupling process is as follows: First, drawing on the decoupling method, the n-heptane, isooctane, and toluene mechanisms in the TRF-PAH mechanism are screened out; then, the obtained three sub-mechanisms are coupled with the PODE mechanism, and duplicate species and reactions are removed to obtain the initial detailed mechanism. The initial detailed mechanism contains 289 species and 1259 reactions.

[0025] Finally, it is necessary to verify the important dynamic simulation parameters of the initial detailed mechanism through experimental data. The verification parameters include: ignition delay time.

[0026] Step 2: PFA simplification. The detailed mechanism obtained from the coupling was initially simplified using a direct relationship graph approach. After comparing various simplification methods and results, PFA simplification was determined, and the resulting mechanism contained 158 species and 798 reactions.

[0027] The mechanism simplification program ReaxRed, developed using the kinetic platform of Sichuan University, was used to simplify the initial detailed mechanism using six DRG-based framework simplification methods. Unlike the CHEMKIN PRO simplification program, ReaxRed can simplify multiple fuel groups during simplification, greatly improving simplification efficiency. Two fuel groups were selected: one group consisted of 100% PODE3, and the other group used a mixture of n-heptane, isooctane, and toluene. Three equivalence ratios were used for simplification: 0.5, 1.0, and 2.0. Initial pressures were set to 10, 20, and 50 atm, for a total of three groups. Temperatures ranged from 800 to 1400 K. The simplification results obtained using the six DRG-based simplification methods were compared and analyzed. Finally, the initial simplified mechanism obtained by PFA (path flux analysis) (the first simplified mechanism) was selected as the basis for subsequent simplifications. This initial simplified mechanism contains 158 species and 798 reactions (hereinafter referred to as the 158 mechanism).

[0028] Finally, based on experimental data, the ignition delay time was verified for single-component n-heptane, isooctane, toluene, and PODE3; two-component n-heptane and isooctane, n-heptane and toluene; and three-component n-heptane, isooctane, and toluene.

[0029] Step 3: Sensitivity Analysis (SA) Simplification. The initial simplified mechanism obtained and validated using the PFA simplification method is simplified by sensitivity analysis to obtain the secondary simplified mechanism, which contains 118 species and 525 reactions (hereinafter referred to as the 118 mechanism).

[0030] The initial simplified mechanism was further simplified using the ReaxRed mechanism simplification program developed by the Sichuan University kinetic platform through sensitivity analysis. The simplification conditions were set as follows: three equivalence ratios of 0.5, 1.0, and 2.0; four fuels of n-heptane, isooctane, toluene, and PODE3; pressures of 10, 20, and 50 atm; a temperature range of 800-2400 K; and a threshold of 0.28. The secondary simplified mechanism obtained using this condition through sensitivity analysis contained 118 species and 525 reactions (118 mechanisms).

[0031] Finally, the kinetic simulation data related to the simplified secondary mechanism were analyzed using experimental data on ignition delay time, laminar flame velocity, and concentrations of key component species. The results show that the simulation data for the ignition delay time of the 118 mechanism for the n-heptane and toluene binary components differs significantly from the experimental data. Figure 2 As shown in the figure, for the 118 mechanism, at temperatures between 800-900K, as the temperature decreases, the error between the simulated and experimental data of the ignition delay time of the binary component gradually increases, and it can no longer accurately describe the ignition delay time characteristics of the binary component.

[0032] Step 4: Optimize the ignition delay time simulation performance of mechanism 118 by using a key species screening and replenishment approach. Establish a key species set, consisting of the 40 species removed during the simplification process from mechanism 158 to mechanism 118. Use a bisection method to divide the species in the set in half each time, and then replenish the two groups of species separately into mechanism 118. Then, perform important kinetic parameter simulations to verify the mechanism 118 containing the replenished species. After analyzing the simulation results, eliminate half of the species. By continuously narrowing down the range of target species, identify the key species affecting the ignition delay time of the n-heptane and toluene binary components. Using this approach, screen out C5H, which was identified as a redundant species by SA. 10Regarding NC3H7CO, it is worth noting that this approach utilizes the ReaxRed simplified program developed by the Sichuan University kinetic platform, which can perform supplementation for individual species and related reactions. The mechanisms obtained through this optimization process include 120 species and 532 reactions (hereinafter referred to as the 120 mechanisms, or optimized mechanisms). The 120 mechanisms were thoroughly validated, with a significant improvement in the simulation results for the ignition delay time of the n-heptane and toluene binary components, which is of particular interest. The simulation results are as follows: Figure 3 As shown, after restoring the two key species, mechanism 120 significantly optimized the ignition delay time of the n-heptane and toluene binary components at temperatures of 800-900 K compared to mechanism 118, and it is closer to the experimental data, showing a strong agreement with the experimental results. This mechanism can accurately describe the fuel combustion characteristics, indicating that the optimization approach is effective.

[0033] However, during the verification of the laminar flame velocity using the 120 mechanism, it was found that the laminar flame velocity of isooctane, which performed well in the original 118 mechanism, showed a significant deviation. Figure 4 It is evident that the laminar flame velocity of isooctane has shown a very large error, and the basic trend is completely inconsistent with the experimental data.

[0034] Step 5: Utilize the key species screening and replenishment optimization approach from Step 4 again to optimize the simulation performance of isooctane laminar flame velocity using mechanism 120. With isooctane laminar flame velocity as the target, repeat the identification and replenishment approach from Step 4, removing all species except C5H that were removed during the simplification process from mechanism 158 to mechanism 118. 10 A key species set was established from 38 species other than (1-pentene) and NC3H7CO (n-butyryl radical). Species from this set were gradually added back into the 120 mechanism. Then, important kinetic parameters were simulated and verified for the 120 mechanism containing the added species. The key species HCOH (hydroxymethylene) was screened out, and after adding this species back into the 120 mechanism, a mechanism containing 121 species and 548 reactions was obtained (the 121 mechanism, the final simplified mechanism).

[0035] The key target parameters within the research conditions were comprehensively validated. The remaining target parameters performed well, with significant optimization effects observed in the isooctane laminar flame velocity, which was the focus of the study. The results are as follows: Figure 5 As shown. After the key species were reinstated, the simulation results of the 121 mechanism were in excellent agreement with the experimental data.

[0036] The final 121 mechanism was fully verified, except... Figure 3 , Figure 5 In addition, the simulation results for the other target parameters are as follows: Figures 6 to 13 As shown, the results indicate that the simulation results of this mechanism are in good agreement with the experimental data under a wide range of simulation conditions.

[0037] All the verification objectives and related conditions mentioned above are as follows: (1) Ignition delay time of n-heptane (condition: NC7H) 16 / Air P=40bar, φ=0.5, 1.0) and laminar flame velocity (condition: NC7H) 16 / Air P=1atm, T=298K, φ=0.6-1.6); (2) Ignition delay time of isooctane (condition: IC8H) 18 / Air P=40bar, φ=1.0) and laminar flame velocity (condition: IC8H) 18 / Air P=1bar, T=298K, φ=0.6-1.6); (3) Toluene ignition delay time (conditions: C7H8 / Air P=50atm, φ=0.25, 0.5, 1.0) and laminar flame velocity (conditions: C7H8 / Air P=1atm, T=298K, φ=0.7-1.5); (4) Ignition delay time of PODE3 (conditions: PODE3 / Air P=10, 15atm, φ=1.5) and laminar flame velocity (conditions: PODE3 / Air P=1atm, T=408K, φ=0.6-1.6); (5) Ignition delay time of toluene + n-heptane (condition: C7H) 18 / NC7H 16 / Air P=10, 30, 50atm, φ=0.3) (6) Ignition delay time of n-heptane + isooctane (PRF90 / Air (n-heptane mole fraction is 0.1, isooctane mole fraction is 0.9), PRF80 / Air, PRF60 / Air, P=40bar, φ=1.0). (7) Ignition delay time of n-heptane + isooctane + toluene (condition: NC7H) 16 / IC8H 18 / C7H8 / Air P=30, 50atm, φ=1.0).

[0038] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels, characterized in that: Includes the following steps: Step 1: Mechanism of TRF-PAH diesel substitute and PODE n Based on chemical kinetics, a detailed initial mechanism was constructed. Step 2: Using various DRG-type mechanism simplification methods, multiple sets of fuels are set to simplify the initial mechanism. The ignition delay time prediction error and mechanism scale are used as evaluation indicators to compare and analyze the results obtained by different simplification methods, select the optimal simplification method, and use the optimal simplification method to simplify the initial mechanism obtained in Step 1 to obtain a simplified mechanism. The ignition characteristic prediction capability is verified by ignition delay time under single-component, multi-component, and multi-operating-condition conditions. Step 3: Based on the simplified mechanism obtained in Step 2, the mechanism is further simplified under multiple fuels by using sensitivity analysis. By deleting low-sensitivity species and related reactions, the scale of the mechanism is reduced again, resulting in a secondary simplified mechanism. Step 4: Optimize the simulated target parameters that have large errors in the secondary simplification mechanism obtained in Step 3 to obtain the optimized mechanism. The optimization method is as follows: First, construct an important species candidate set by deleting the species in the sensitivity analysis method; Second, use the dichotomy method to gradually restore the species and related responses in the candidate species set to the secondary simplification mechanism, reconstruct the mechanism and verify the target parameters, and screen out the important species that have a greater impact on the target parameters. Step 5: Fully verify the optimization mechanism obtained in Step 4. Using the same optimization method as in Step 4, optimize the simulation error of laminar flame velocity. Through the process of identification, replenishment and verification, accurately identify the deleted error source species, replenish the deleted error source species and related reactions to optimize the mechanism, and obtain the final simplified mechanism.

2. The method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels according to claim 1, characterized in that: In step 1, the three sub-mechanisms of n-heptane, isooctane, and toluene in the TRF-PAH diesel substitute mechanism are screened out; then the screened three sub-mechanisms are compared with PODE. n Mechanism coupling was performed, and duplicate species and reactions were removed to obtain the initial mechanism.

3. The method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels according to claim 1, characterized in that: In step 2, the ignition delay time is verified using experimental data. The verification objects include single-component, two-component, and three-component systems. The single-component system is one of n-heptane, isooctane, toluene, or PODE3. The two-component system is one of n-heptane plus isooctane or n-heptane plus toluene. The three-component system is n-heptane, isooctane, and toluene.

4. The method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels according to claim 1, characterized in that: In step 3, low-sensitivity species and reactions in the mechanism are removed by sensitivity analysis, and the obtained mechanism is used for simulation. Then, the simulation data is compared with the experimental data to verify the consistency between the simplified mechanism simulation by sensitivity analysis and the experimental data. The simulation data includes ignition delay time, laminar flame velocity and concentration of important component species.

5. The method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels according to claim 1, characterized in that: In step 4, the optimization method is as follows: First, the source of error is determined by the error feedback of the target parameter, and an important species set is constructed by identifying and deleting species that are redundant in the simplification process from the first simplification mechanism to the second simplification mechanism. Secondly, a stepwise recovery, verification, and screening method was adopted. The species and related reactions in the candidate important species set were restored to the secondary simplified mechanism in batches using the dichotomy method. The mechanism was reconstructed and verified. By comparing the predicted results of the mechanism after supplementing the species and related reactions on ignition delay time and laminar flame velocity, key species and related reactions with important influence on the research target were identified, and error optimization was completed to obtain the optimized mechanism.

6. The method for constructing and simplifying a reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels according to claim 1, characterized in that: In step 3, the mechanism simplification program ReaxRed is used to further simplify the first-simplified mechanism to obtain the second-simplified mechanism.

7. A reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuels, characterized in that: The reaction mechanism model was obtained using the construction and simplification methods described in any one of items 1-6.

8. The reaction mechanism model for diesel / polyoxymethylene dimethyl ether alternative fuel according to claim 7, characterized in that: The reaction mechanism model includes 121 species and 548 reactions.

Images