A method for constructing a hydrogen turbulent combustion thickened flame surface model

Abstract

This application provides a method for constructing a thickened flame surface model for hydrogen turbulent combustion, belonging to the field of hydrogen fuel cell engine technology. Specifically, it includes: constructing a hydrogen fuel turbulent flame velocity scaling rate under wide operating conditions to model the diffusion enhancement effect and flame surface wrinkling effect caused by multi-scale turbulence, thus more accurately describing the hydrogen fuel combustion process. Furthermore, based on a thin reaction zone combustion mode, key physical quantities are extracted, the combustion efficiency function is optimized, and multi-scale turbulence and differential diffusion effects are considered to further improve the thickened flame surface model. The development of this method will provide strong technical support for realizing forward design of hydrogen fuel cell engines based on numerical simulation, promote the engineering application of hydrogen fuel cell engines, and help them play a greater role in the efficient, clean, and safe energy transition.

Description

Technical Field

[0001] This application relates to the field of hydrogen fuel cell engines, and in particular to a method for constructing a hydrogen turbulent combustion thickened flame surface model. Background Technology

[0002] With the increasing global demand for clean energy, hydrogen fuel cell engines have attracted widespread attention due to their efficient and clean combustion characteristics. However, the development of hydrogen fuel cell engines faces numerous challenges. Backfire and thermoacoustic oscillations are prone to occur during hydrogen combustion, affecting engine performance. Backfire refers to the reverse propagation of the flame into the fuel supply system, while thermoacoustic oscillations are instabilities caused by the interaction between the combustion process and the acoustic characteristics of the combustion chamber. Furthermore, hydrogen fuel has a low ignition energy, making it prone to detonation, which poses a threat to the safe operation of the equipment. Numerical simulation is of great significance for the design of hydrogen fuel cell engines. Traditional engine design typically relies on extensive experimental trial and error, a method that is not only costly but also time-consuming and labor-intensive. Numerical simulation, based on physical models and numerical methods, can simulate and predict the internal combustion process of the engine, providing a scientific basis for engine design optimization. Through numerical simulation, engineers can evaluate different combustion organization schemes during the design phase, predict engine performance and emission characteristics, identify and resolve potential problems in advance, reduce experimental costs and risks, and shorten the development cycle. However, hydrogen combustion numerical simulation also faces a series of challenges. The unstable combustion of hydrogen fuel is highly transient, which places high demands on the accuracy of combustion models and the stability of numerical methods. Under actual engine operating conditions, the combustion process involves complex interactions between turbulent flow and chemical reactions. Conventional large eddy simulation grids are insufficient to accurately resolve the fine structure of the hydrogen flame, limiting the accuracy of simulation results and consequently restricting their guiding significance for engine development. Summary of the Invention

[0003] In view of this, this application provides a method for constructing a hydrogen turbulent combustion thickened flame surface model, which solves the problems in the prior art and accurately simulates the combustion process in a hydrogen fuel engine.

[0004] The method for constructing a hydrogen turbulent combustion thickened flame surface model provided in this application adopts the following technical solution:

[0005] A method for constructing a hydrogen turbulent combustion thickened flame surface model, comprising:

[0006] Step 1: Construct a multi-source dataset of hydrogen turbulent flame propagation velocity under wide operating conditions, and determine the main control parameters of hydrogen turbulent flame propagation velocity based on the multi-source dataset. Then, model the diffusion enhancement effect and flame surface wrinkling effect corresponding to multi-scale turbulence respectively, and construct a scaling rate of hydrogen turbulent flame propagation velocity over a wide operating range.

[0007] Step 2: The hydrogen turbulent combustion process in the thin reaction zone is simulated using numerical simulation methods. Physical quantities in the combustion field are extracted, and the optimal expression of the hydrogen turbulent combustion efficiency function is determined based on the extracted physical quantities.

[0008] Step 3: To address the combustion characteristic deviation caused by the unresolved flame folds in the thickened flame surface model, a physical model of the flame folds is modeled, and a compensation method for reducing the thickness of the flame folds is designed.

[0009] Step 4: Integrate the combustion efficiency function determined in Step 2, the flame folding physical model and compensation method in Step 3, and the wide operating range hydrogen turbulent flame propagation velocity scaling rate in Step 1 into the thickened flame surface initial model under the large eddy simulation framework. By dynamically calculating the effective diffusion coefficient in the energy equation and composition equation, a hydrogen turbulent combustion thickened flame surface model considering multi-scale turbulence and differential diffusion effects is formed.

[0010] Optionally, in step 1, the construction of a multi-source dataset of hydrogen turbulent flame propagation velocity under wide operating conditions includes hydrogen fuel turbulent flame propagation velocity data under different pressures, temperatures, fuel equivalence ratios, and turbulence intensities.

[0011] Optionally, in step 1, the specific steps for determining the master control parameters of hydrogen turbulent flame propagation speed based on the multi-source dataset include: using the active subspace method to reduce the dimensionality of the operating parameters in the multi-source dataset, and extracting the turbulent pulsation velocity, laminar flame velocity, laminar flame thickness, and turbulent integral scale as master control parameters by analyzing the correlation between each operating parameter and the hydrogen turbulent flame propagation speed.

[0012] Optionally, in step 1, the expression for the scaling factor of the hydrogen turbulent flame propagation velocity over a wide operating range is:

[0013] ;

[0014] ;

[0015] ;

[0016] in, The propagation speed of turbulent flame; Laminar flame velocity; The area of ​​the flame after folding; The flame area before the folds; The additional diffusion coefficient caused by turbulence; The molecular diffusion coefficient; For turbulent fluctuation velocity; Laminar flame velocity; The thickness of the laminar flame; The integral scale is for turbulence. It is a Karlovy Vu number.

[0017] Optionally, in step 2, the physical quantities extracted from the combustion field include turbulent fluctuation velocity. Flame elongation, laminar flame velocity Laminar flame thickness and grid feature scale .

[0018] Optionally, in step 2, the optimal expression for the hydrogen turbulent combustion efficiency function is:

[0019] ;

[0020] in, Let it be the efficiency function; These are the parameters of the first model; For turbulent fluctuation velocity; Laminar flame velocity; The grid feature scale; The thickness of the laminar flame; This is a thickening factor.

[0021] Optionally, in step 3, the method for designing a compensation method to reduce flame wrinkles specifically includes:

[0022] A correction term is introduced into the thickened flame surface model. The correction term is related to the morphological characteristics and scale of the flame folds. The correction term compensates for the deviations in combustion efficiency and flame propagation speed caused by the lack of resolution of flame folds.

[0023] Optionally, in step 4, the formula for dynamically calculating the effective diffusion coefficient in the energy equation and composition equation is:

[0024] ;

[0025] in, ;

[0026] The effective diffusion coefficient; The molecular diffusion coefficient; The turbulent diffusion coefficient; Let it be the efficiency function; For thickening factor; This is a flame detection function; These are the parameters for the second model; This represents the absolute value of the reaction rate.

[0027] In summary, this application includes the following beneficial technical effects:

[0028] The thickened flame surface model in this application, which considers multi-scale turbulence and differential diffusion effects, enables the simulation of unsteady combustion of hydrogen fuel to accurately simulate the combustion process in a hydrogen fuel engine over a wide range of operating conditions. This provides strong technical support for the forward design of the engine, helps to improve engine performance and safety, and reduces R&D costs and time.

[0029] By incorporating a thickened flame surface model that considers multi-scale turbulence and differential diffusion effects, the requirements for grid resolution can be reduced while ensuring simulation accuracy, thereby improving the computational efficiency of numerical simulation and making it more suitable for practical engineering applications. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating the method for constructing a hydrogen turbulent combustion thickened flame surface model according to an embodiment of this application. Detailed Implementation

[0032] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0033] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0034] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0035] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0036] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0037] This application provides a method for constructing a hydrogen turbulent combustion thickened flame surface model.

[0038] like Figure 1 As shown, a method for constructing a hydrogen turbulent combustion thickened flame surface model includes:

[0039] Step 1: Construct a multi-source dataset of hydrogen turbulent flame propagation velocity under wide operating conditions, and determine the main control parameters of hydrogen turbulent flame propagation velocity based on the multi-source dataset. Then, model the diffusion enhancement effect and flame surface wrinkling effect corresponding to multi-scale turbulence respectively. The diffusion enhancement effect model is for small-scale turbulence, considering the promoting effect of small-scale turbulence on the mixing of hydrogen fuel and oxidizer, and the enhancement effect of this effect on the hydrogen turbulent flame propagation velocity. The enhancement effect is quantified by the ratio of the additional diffusion coefficient caused by turbulence to the molecular diffusion coefficient. The flame surface wrinkling effect model is for large-scale turbulence, describing the stretching, folding and fragmentation phenomena of hydrogen flame surface caused by large-scale turbulence. The influence of flame surface wrinkling on hydrogen turbulent flame propagation velocity is quantified by the ratio of the flame area after wrinkling to the flame area before wrinkling, thereby developing a wide-range hydrogen turbulent flame propagation velocity scaling rate.

[0040] Step 2: The hydrogen turbulent combustion process in the thin reaction zone is simulated using a high-fidelity numerical simulation method. Key physical quantities in the combustion field are extracted, and the optimal expression of the hydrogen turbulent combustion efficiency function is determined based on the extracted key physical quantities.

[0041] Step 3: To address the combustion characteristic deviation caused by the unresolved flame folds in the thickened flame surface model, a physical model of the flame folds is modeled, and a compensation method for reducing the thickness of the flame folds is designed.

[0042] Step 4: Integrate the combustion efficiency function determined in Step 2, the flame folding physical model and compensation method in Step 3, and the wide operating range hydrogen turbulent flame propagation velocity scaling rate in Step 1 into the thickened flame surface initial model under the large eddy simulation framework. By dynamically calculating the effective diffusion coefficient in the energy equation and composition equation, a hydrogen turbulent combustion thickened flame surface model considering multi-scale turbulence and differential diffusion effects is formed.

[0043] This application aims to develop a simulation method for unsteady combustion of hydrogen fuel based on a thickened flame surface model to address the challenges faced in hydrogen combustion simulation. The thickened flame surface model, by artificially thickening the flame surface, reduces the mesh resolution requirement while ensuring accurate flame propagation velocity, effectively alleviating the mismatch between mesh analytical scale and flame thickness in combustion chamber simulation. By constructing a hydrogen fuel turbulent flame velocity scaling rate under wide operating conditions, and modeling the diffusion enhancement effect and flame surface wrinkling effect caused by multi-scale turbulence, the hydrogen fuel combustion process can be described more accurately. Furthermore, based on a thin reaction zone combustion mode, key physical quantities are extracted, the combustion efficiency function is optimized, and multi-scale turbulence and differential diffusion effects are considered to further improve the thickened flame surface model. The development of this method will provide strong technical support for realizing forward design of hydrogen fuel engines based on numerical simulation, promote the engineering application of hydrogen fuel engines, and help them play a greater role in the efficient, clean, and safe energy transition.

[0044] In step 1, a multi-source dataset of hydrogen turbulent flame propagation velocity under wide operating conditions is constructed, including hydrogen fuel turbulent flame propagation velocity data under different pressures, temperatures, fuel equivalence ratios, and turbulence intensities to ensure the dataset's broad applicability and representativeness. Specifically, the pressure range is 0.1-1 MPa, the temperature range is 300-800 K, the fuel equivalence ratio range is 0.3-3.0, and the turbulent fluctuation velocity range is 0.1-10 m / s.

[0045] In step 1, the specific steps for determining the master control parameters of hydrogen turbulent flame propagation velocity based on multi-source datasets include: using the active subspace method to reduce the dimensionality of the operating parameters in the multi-source datasets; and extracting the turbulent fluctuation velocity, laminar flame velocity, laminar flame thickness, and turbulent integral scale as master control parameters by analyzing the correlation between each operating parameter and the hydrogen turbulent flame propagation velocity. By analyzing the correlation between the operating parameters and the flame propagation velocity, the main sensitive parameters, i.e., the master control parameters of hydrogen turbulent flame propagation velocity, are determined, providing a foundation for developing the scaling rate of hydrogen turbulent flame propagation velocity.

[0046] In step 1, the expression for the scaling factor of the hydrogen turbulent flame propagation velocity over a wide operating range is:

[0047] ;

[0048] ;

[0049] ;

[0050] in, The propagation speed of turbulent flame; Laminar flame velocity; The area of ​​the flame after folding; The flame area before the folds; The additional diffusion coefficient caused by turbulence; The molecular diffusion coefficient; For turbulent fluctuation velocity; Laminar flame velocity; The thickness of the laminar flame; The integral scale is for turbulence. It is a Karlovy Vu number.

[0051] The scaling factor for hydrogen turbulent flame propagation velocity over a wide operating range can reflect the quantitative relationship between flame propagation velocity and operating parameters, providing a foundation for subsequent combustion model development.

[0052] In step 2, the key physical quantities extracted from the combustion field include turbulent fluctuation velocity. Flame elongation, laminar flame velocity Laminar flame thickness and grid feature scale These physical quantities reflect important information such as turbulence characteristics, flame structure, and combustion reaction rate during the combustion process.

[0053] In step 2, the optimal expression of the hydrogen turbulent combustion efficiency function is:

[0054] ;

[0055] in, Let it be the efficiency function; These are the parameters for the first model, with values ​​ranging from 0.1 to 10. For turbulent fluctuation velocity; Laminar flame velocity; The grid feature scale; The thickness of the laminar flame; The thickening factor has a value range of 5-50.

[0056] The optimal expression of the hydrogen turbulent combustion efficiency function should be able to more accurately describe the relationship between combustion efficiency and key physical quantities, thereby improving the prediction accuracy of the combustion model.

[0057] In step 3, the specific compensation method for reducing the thickness of flame folds includes: introducing a correction term into the thickened flame surface model. The correction term is related to the morphological characteristics and scale of the flame folds. The correction term compensates for the deviation in combustion efficiency and flame propagation speed caused by the lack of resolution of flame folds.

[0058] In step 4, the formula for dynamically calculating the effective diffusion coefficient in the energy equation and composition equation is as follows:

[0059] ;

[0060] in, ;

[0061] The effective diffusion coefficient; The molecular diffusion coefficient; The turbulent diffusion coefficient; Let it be the efficiency function; For thickening factor; This is a flame detection function; These are the parameters for the second model, with values ​​ranging from 3 to 10. This represents the absolute value of the reaction rate.

[0062] Step 4: Specifically, using the large eddy simulation framework as the numerical calculation vehicle, the hydrogen turbulent combustion efficiency function determined in Step 2, the flame wrinkling physical model constructed in Step 3, and the thickened flame wrinkling reduction compensation method are initially embedded into the basic thickened flame surface model to form an initial model of hydrogen turbulent combustion thickened flame surface considering multi-scale turbulence and differential diffusion effects. Then, the wide-range hydrogen turbulent flame propagation velocity scaling rate model constructed in Step 1 is used as the accuracy verification benchmark model, and the parameters of the current simulation condition are substituted: including turbulent fluctuation velocity. Laminar flame velocity Laminar flame thickness Turbulent integral scale The theoretical turbulent flame propagation velocity is calculated. The aforementioned initial model for hydrogen turbulent combustion with a thickened flame surface is run, and the turbulent flame propagation velocity output by the initial model is extracted from the calculation results of the large eddy simulation framework. The deviation between the theoretical turbulent flame propagation velocity and the turbulent flame propagation velocity output by the initial model for hydrogen turbulent combustion with a thickened flame surface is compared. If the deviation exceeds a preset accuracy threshold, the parameters of the initial model for hydrogen turbulent combustion with a thickened flame surface are adjusted, such as the parameters of the first model. Flame detection function The second model parameter Thickening factor The above process is repeated until the deviation between the theoretical turbulent flame propagation speed and the turbulent flame propagation speed output by the initial model of hydrogen turbulent combustion thickened flame surface meets the accuracy requirements, and finally the hydrogen turbulent combustion thickened flame surface model considering multi-scale turbulence and differential diffusion effects is obtained.

[0063] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for constructing a hydrogen turbulent combustion thickened flame surface model, characterized in that... ,include: Step 1: Construct a multi-source dataset of hydrogen turbulent flame propagation velocity under wide operating conditions, and determine the main control parameters of hydrogen turbulent flame propagation velocity based on the multi-source dataset. Then, model the diffusion enhancement effect and flame surface wrinkling effect corresponding to multi-scale turbulence respectively, and construct a scaling rate of hydrogen turbulent flame propagation velocity over a wide operating range. Step 2: The hydrogen turbulent combustion process in the thin reaction zone is simulated using numerical simulation methods. Physical quantities in the combustion field are extracted, and the optimal expression of the hydrogen turbulent combustion efficiency function is determined based on the extracted physical quantities. Step 3: To address the combustion characteristic deviation caused by the unresolved flame folds in the thickened flame surface model, a physical model of the flame folds is modeled, and a compensation method for reducing the thickness of the flame folds is designed. Step 4: Integrate the combustion efficiency function determined in Step 2, the flame wrinkling physical model and compensation method in Step 3, and the wide operating range hydrogen turbulent flame propagation speed scaling rate in Step 1 into the thickened flame surface initial model under the large eddy simulation framework. By dynamically calculating the effective diffusion coefficient in the energy equation and composition equation, a hydrogen turbulent combustion thickened flame surface model considering multi-scale turbulence and differential diffusion effects is formed. In step 1, the expression for the scaling factor of the hydrogen turbulent flame propagation velocity over a wide operating range is: ； ； ； in, The propagation speed of turbulent flame; Laminar flame velocity; The area of ​​the flame after folding; The flame area before the folds; The additional diffusion coefficient caused by turbulence; The molecular diffusion coefficient; For turbulent fluctuation velocity; Laminar flame velocity; The thickness of the laminar flame; The integral scale is for turbulence. For Karlowitz numbers; In step 2, the physical quantities extracted from the combustion field include turbulent pulsation velocity. Flame elongation, laminar flame velocity Laminar flame thickness and grid feature scale ; In step 2, the optimal expression of the hydrogen turbulent combustion efficiency function is: ； in, Let it be the efficiency function; These are the parameters of the first model; For turbulent fluctuation velocity; Laminar flame velocity; The grid feature scale; The thickness of the laminar flame; This is a thickening factor.

2. The method for constructing a hydrogen turbulent combustion thickened flame surface model according to claim 1, characterized in that, In step 1, a multi-source dataset of hydrogen turbulent flame propagation velocity under wide operating conditions is constructed, including hydrogen fuel turbulent flame propagation velocity data under different pressures, temperatures, fuel equivalence ratios, and turbulence intensities.

3. The method for constructing the hydrogen turbulent combustion thickened flame surface model according to claim 1, characterized in that, In step 1, the specific steps for determining the master control parameters of hydrogen turbulent flame propagation speed based on multi-source datasets include: using the active subspace method to reduce the dimensionality of the operating parameters in the multi-source datasets, and extracting the turbulent pulsation velocity, laminar flame velocity, laminar flame thickness, and turbulent integral scale as master control parameters by analyzing the correlation between each operating parameter and hydrogen turbulent flame propagation speed.

4. The method for constructing the hydrogen turbulent combustion thickened flame surface model according to claim 1, characterized in that, In step 3, the specific compensation method for reducing the thickness of flame wrinkles includes: A correction term is introduced into the thickened flame surface model. The correction term is related to the morphological characteristics and scale of the flame folds. The correction term compensates for the deviations in combustion efficiency and flame propagation speed caused by the lack of resolution of flame folds.

5. The method for constructing a hydrogen turbulent combustion thickened flame surface model according to claim 1, characterized in that, In step 4, the formula for dynamically calculating the effective diffusion coefficient in the energy equation and composition equation is as follows: ； in, ; The effective diffusion coefficient; The molecular diffusion coefficient; The turbulent diffusion coefficient; Let it be the efficiency function; For thickening factor; This is a flame detection function; These are the parameters for the second model; This represents the absolute value of the reaction rate.

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