Automatic modeling method and system for gas turbine silo type diffusion combustor

Abstract

The invention relates to the technical field of gas turbines, and discloses an automatic modeling method and system for a gas turbine silo type diffusion combustor. According to the preset performance requirement and the preset size limitation of a target combustor and the overall input parameters of the combustor under the full-load working condition, the target combustor is automatically modeled; setting structural parameters of parts at different positions on the silo type diffusion burner; according to the structure parameters and a preset static pressure value, target gas flows at different outlets are calculated, and target static pressure parameters, matched with the target gas flows, at the outlets are determined; and a target combustor is constructed based on the structure parameters and the target static pressure parameters of all the outlets. By accurately calculating and setting the structural parameters of the parts at different positions of the silo-type diffusion burner, and combining the preset static pressure value, the target gas flow and the physical and chemical mechanisms of use instead of empirical data, the problem that a traditional burner is prone to mismatching when facing gas fuel is solved, and the overall performance of a gas turbine is improved to some extent.

Description

Technical Field

[0001] The present invention relates to the technical field of gas turbines, and in particular to an automated modeling method and system for a silo-type diffusion burner of a gas turbine. Background Art

[0002] Gas turbines are used in aviation, petroleum, shipping and other fields due to their high power density and high thermal efficiency. Gas turbines that use gas fuel are often found in factories such as booster stations and regional power generation. Gas turbines convert chemical energy into kinetic energy through fuel combustion to drive the turbine to do work. At the same time, the turbine drives the compressor to increase the pressure in the combustion chamber, thereby achieving efficient combustion.

[0003] For small gas turbines, the combustion chamber does not produce excessive nitrogen oxide emissions due to its small power, and usually adopts a diffusion combustion chamber. According to the different structural forms, the combustion chamber can be divided into two types: silo burner and full annular flame tube.

[0004] Among them, full annular flame tubes are mostly used in gas turbines modified from aircraft engines. Most of the existing gas turbine design experience and formulas are based on the development of aircraft engines, which usually use liquid fuels. The formulas and experience of aircraft engine combustion chamber design may not be completely applicable to gas fuel combustion chambers. That is to say, when these designs are directly applied to gas fuel combustion chambers, there may be a mismatch between the gas fuel combustion chamber head and the flame shape and the main combustion hole position. Due to the different combustion speed, flame temperature and mixture formation characteristics of gas fuel, the overall performance of the designed gas turbine is reduced. Summary of the invention

[0005] In view of this, the present invention provides a method and system for automatically modeling a silo-type diffusion burner of a gas turbine to solve the problem of how to improve the overall performance of the designed gas turbine.

[0006] In a first aspect, the present invention provides a method for automatic modeling of a gas turbine silo type diffusion burner, the method comprising:

[0007] Obtaining preset performance requirements, preset size restrictions, and overall input parameters of the target burner under full load conditions, wherein the preset performance requirements represent physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions represent preset constraints on the geometric shape and size of the burner, and the overall input parameters represent physical parameters of the gas at different inlet positions in the burner under full load;

[0008] Setting structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions;

[0009] Calculate the target gas flow rates at different outlets of the burner according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets of the burner, wherein the target gas flow rate represents the total flow rate of the gas at the outlet;

[0010] Determining a target static pressure parameter at an outlet that matches the target gas flow rate according to the target gas flow rate;

[0011] After the target static pressure parameters at all outlets are obtained, the target burner is constructed using an automated modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets.

[0012] The embodiment of the present invention obtains the preset performance requirements, preset size restrictions, and overall input parameters of the target burner under full load conditions, wherein the preset performance requirements characterize the physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions characterize the preset constraints on the geometric shape and size of the burner, and the overall input parameters characterize the physical parameters of the gas at different inlet positions in the burner under full load; by obtaining the preset performance requirements and size restrictions of the burner, chemical mechanisms and physical and chemical mechanisms are introduced into the design of the burner head, rather than relying entirely on empirical data, which can more accurately predict the flame combustion behavior in the combustion chamber. Based on the preset performance requirements, preset size restrictions, and the overall input parameters of the burner under full load conditions, the structural parameters of the components at different positions on the silo-type diffusion burner are set, and modeling and design are performed according to the overall input parameters under full load conditions, and the characteristics of gas fuel flame combustion are combined to ensure that the modeling and design of the burner are more in line with actual application requirements. According to the structural parameters of components at different positions and the preset static pressure values ​​of different outlets on the burner, the target gas flow at different outlets in the burner is calculated, where the target gas flow represents the total flow of gas at the outlet; the target static pressure parameters at the outlet that match the target gas flow are determined according to the target gas flow; after the target static pressure parameters at all outlets are obtained, the target burner is constructed using an automated modeling tool based on the structural parameters of components at different positions and the target static pressure parameters at all outlets. By accurately calculating and setting the structural parameters of components at different positions of the silo-type diffusion burner, combined with the preset static pressure value and the target gas flow, the burner is made more stable in actual work, which solves the mismatch problem that traditional burners are prone to when facing gas fuel, and improves the overall performance of the gas turbine.

[0013] In an optional embodiment, the overall input parameters include gas flow, gas calorific value, total temperature at the burner inlet, and total pressure at the burner inlet; the preset size restrictions include head size restrictions; the preset performance requirements include resistance coefficient, outlet temperature distribution coefficient, combustion efficiency, combustion temperature, internal and external pressure difference, and flame tube head dynamic pressure;

[0014] The setting of structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions specifically includes:

[0015] Design the burner head size based on the overall input parameters and head size constraints;

[0016] Calculating the total pressure loss based on the burner head size and the total pressure at the burner inlet;

[0017] Determine the radius parameter of the flame tube outer cover according to the overall input parameters and the burner head size;

[0018] Determine the flame tube radius parameter according to the gas flow rate, gas calorific value, total temperature of the burner inlet, total pressure of the burner inlet, resistance coefficient and total pressure loss;

[0019] Determine the flame tube length parameter according to the total pressure loss, the flame tube radius parameter, the flame tube head dynamic pressure and the outlet temperature distribution coefficient;

[0020] Determine the number of flame tube nozzles according to the combustion efficiency; wherein the flame tube outer cover radius parameter, the flame tube radius parameter, the flame tube length parameter, and the number of flame tube nozzles together constitute the initial flame tube structure parameter;

[0021] Determining the initial swirler structural parameters according to the gas flow rate, gas calorific value, total burner inlet temperature, total burner inlet pressure, and initial flame tube structural parameters;

[0022] According to the initial cyclone structural parameters, a flame combustion simulation is performed using a simulation software to obtain a flame combustion simulation result;

[0023] Determining initial combustion hole parameters based on the simulation results, gas flow rate, gas calorific value, total burner inlet temperature, total burner inlet pressure, and initial flame tube structural parameters;

[0024] Determining the wall adiabatic temperature according to the initial combustion hole parameters, gas flow rate, gas calorific value, total burner inlet temperature, total burner inlet pressure, initial flame tube structural parameters, and combustion temperature;

[0025] According to the wall adiabatic temperature or the internal and external pressure difference, heat transfer analysis is performed according to the arrangement and combination of different types of preset cooling structures to determine the target cooling structure combination and the corresponding initial cooling structure parameters.

[0026] The embodiment of the present invention gradually determines the parameters of the key components of the burner (burner head, flame tube, swirler, combustion hole, cooling structure) by combining the overall input parameters such as gas flow, calorific value, inlet temperature, inlet total pressure, and head size restrictions. Among them, by accurately calculating the total pressure loss of the burner head, the energy loss in the combustion process can be effectively controlled. The introduction of parameters such as combustion temperature, outlet temperature distribution coefficient and combustion efficiency improves the stability and combustion efficiency of the combustion process. In the subsequent steps, flame combustion simulation is performed to flexibly adjust the position and size of the combustion hole. The optimal cooling structure is selected through heat transfer analysis, which can effectively reduce the wall temperature and prevent material overheating. The steps are interrelated, and repeated iterations are performed through empirical formulas and simulations to ensure that the parameters of all components are highly matched in the overall burner. Finally, a burner that is more adaptable to physical and chemical mechanisms and has accurate adaptability to adiabatic flame temperature, etc. is modeled.

[0027] In an optional embodiment, the method further includes:

[0028] Dividing the burner into a plurality of cross sections according to the gas flow direction in the burner based on the initial combustion hole parameters and the initial cooling component structure parameters;

[0029] The isentropic calculation is performed on each divided cross section to obtain the parameters of each cross section.

[0030] The embodiment of the present invention can accurately determine the changes in the airflow inside the burner through the fine division and isentropic calculation of multiple cross-sections of the burner, and based on the detailed cross-sectional analysis, make the calculated shape and size of each cross-section of the burner more consistent with the actual thermodynamic changes, thereby further improving the accuracy of burner modeling.

[0031] In an optional embodiment, the preset cooling structure includes a ribbed enhanced cooling structure, an impingement cooling structure, a convection cooling structure, an air film cooling structure, and a seepage cooling structure;

[0032] The heat transfer analysis is performed according to the wall adiabatic temperature or the internal and external pressure difference according to the arrangement and combination of different types of preset cooling structures to determine the target cooling structure combination and the corresponding initial cooling structure parameters, specifically including:

[0033] Calculate the heat transfer coefficient of the lower burner with different cooling structures based on a preset empirical formula;

[0034] Calculating the actual wall temperature according to the heat transfer coefficient and the wall adiabatic temperature, performing temperature distribution analysis based on the actual wall temperature, and selecting a target cooling structure combination and corresponding initial cooling structure parameters from permutations and combinations of different types of preset cooling structures according to the temperature distribution analysis results;

[0035] Alternatively, the pressure ratio is calculated according to the heat transfer coefficient and the internal and external pressure difference, and a cold air flow analysis is performed based on the pressure ratio. According to the cold air flow analysis results, a target cooling structure combination and corresponding initial cooling structure parameters are selected from permutations and combinations of different types of preset cooling structures.

[0036] The embodiment of the present invention calculates the heat transfer coefficients for the five cooling structures respectively, and can more accurately determine the heat exchange efficiency of the burner under different cooling structures, thereby maximizing the cooling efficiency, reducing the operating temperature of the burner, and thus extending the service life of the modeled burner.

[0037] In an optional embodiment, the temperature distribution analysis is performed based on the actual wall temperature, and a target cooling structure combination and corresponding initial cooling structure parameters are selected from permutations and combinations of different types of preset cooling structures according to the temperature distribution analysis result, specifically including:

[0038] The preset cooling structure is arranged at different positions of the burner to obtain different arrangement combinations at different positions, wherein each arrangement combination includes multiple cooling structures at different positions;

[0039] Calculate the overall actual wall temperature corresponding to each arrangement and combination according to the actual wall temperature of different cooling structures;

[0040] A target overall actual wall temperature is determined from a plurality of overall actual wall temperatures, and a target cooling structure combination corresponding to the target overall actual wall temperature and corresponding initial cooling structure parameters are determined, wherein the target overall actual wall temperature represents the lowest temperature among all temperatures.

[0041] The embodiment of the present invention sets preset cooling structures at different positions of the burner and arranges and combines them. By calculating and comparing the actual overall wall temperature of each arrangement and combination, the most suitable cooling structure combination can be found, and the wall temperature distribution of the burner is more uniform, thereby further extending the service life of the modeled target burner.

[0042] In an optional embodiment, the cold air flow analysis is performed based on the pressure ratio, and a target cooling structure combination and corresponding initial cooling structure parameters are selected from permutations and combinations of different types of preset cooling structures according to the cold air flow analysis results, specifically including:

[0043] The preset cooling structure is arranged at different positions of the burner to obtain different arrangement combinations at different positions, wherein each arrangement combination includes multiple cooling structures at different positions;

[0044] Calculate the cold air flow rate corresponding to each arrangement and combination according to the pressure ratio and the preset gas flow rate;

[0045] A target cold air flow rate higher than a preset cold air flow rate is selected from a plurality of cold air flow rates, and a target cooling structure combination corresponding to the target cold air flow rate and a corresponding initial cooling structure parameter are determined.

[0046] The embodiment of the present invention analyzes the cooling structures of different arrangements and combinations and calculates the cold air flow rate under each combination, so as to better match the actual cooling requirements, thereby optimizing the cooling effect of the final target burner, avoiding overcooling or insufficient cooling, and making the modeling of the target burner more accurate and in line with actual needs.

[0047] In an optional implementation manner, determining a target static pressure parameter at an outlet that matches the target gas flow rate specifically includes:

[0048] When it is calculated that the target gas flow at the current outlet is within the preset flow range, the preset static pressure value is used as the target static pressure parameter of the current burner outlet;

[0049] When it is calculated that the target gas flow at the current outlet exceeds the preset flow range, the preset static pressure value is reset and the target gas flow at the current outlet is calculated again until the target gas flow at the current outlet is within the preset flow range. The corresponding preset static pressure value is used as the target static pressure parameter of the current outlet of the burner.

[0050] The embodiment of the present invention ensures that the gas flow rate at the burner outlet is always maintained within a preset range by real-time calculation and adjustment of the target static pressure parameters. During the modeling process, the actual operating conditions can be better matched with the theoretical parameters, thereby reducing the burner modeling error caused by the mismatch between static pressure and flow rate.

[0051] In a second aspect, the present invention provides an automatic modeling system for a gas turbine silo type diffusion burner, the device comprising:

[0052] A burner initial condition acquisition module, used to acquire preset performance requirements, preset size restrictions, and overall input parameters of the burner under full load conditions of the target burner, wherein the preset performance requirements represent physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions represent preset constraints on the geometric shape and size of the burner, and the overall input parameters represent physical parameters of the gas at different inlet positions in the burner under full load;

[0053] A burner structural parameter setting module, used to set structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions;

[0054] A target gas flow calculation module is used to calculate the target gas flow at different outlets in the burner according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets on the burner, wherein the target gas flow represents the total flow of the gas at the outlet;

[0055] A target static pressure parameter determination module, used to determine a target static pressure parameter at an outlet that matches the target gas flow rate;

[0056] The burner automatic modeling module is used to construct a target burner using an automatic modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets after obtaining the target static pressure parameters at all outlets.

[0057] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the automatic modeling method for a gas turbine silo-type diffusion burner according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0058] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the automated modeling method for a gas turbine silo-type diffusion burner of the first aspect or any corresponding embodiment thereof.

[0059] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for automated modeling of a gas turbine silo-type diffusion burner according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 is a flow chart of an automatic modeling method for a gas turbine silo type diffusion burner according to an embodiment of the present invention;

[0062] Figure 2 is a flow chart of another method for automatic modeling of a gas turbine silo type diffusion burner according to an embodiment of the present invention;

[0063] Figure 31 is a schematic diagram of a heat transfer coefficient calculation method according to an automatic modeling method for a gas turbine silo type diffusion burner according to an embodiment of the present invention;

[0064] Figure 4 2 is a schematic diagram showing the principle of a second heat transfer coefficient calculation method of another automatic modeling method for a gas turbine silo type diffusion burner according to an embodiment of the present invention;

[0065] Figure 5 is a schematic diagram of the third principle of heat transfer coefficient calculation method of another gas turbine silo type diffusion burner automatic modeling method according to an embodiment of the present invention;

[0066] Figure 6 is a schematic diagram of a fifth principle of heat transfer coefficient calculation method of another gas turbine silo type diffusion burner automatic modeling method according to an embodiment of the present invention;

[0067] Figure 7 is a structural block diagram of a gas turbine silo type diffusion burner automatic modeling system according to an embodiment of the present invention;

[0068] Figure 8 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0070] Gas turbines have the characteristics of high power density and high thermal efficiency. They are used in aviation, petroleum, ships and other fields. Gas turbines convert chemical energy into kinetic energy by burning fuel, drive the turbine to output power, and drive the compressor to increase the pressure of the combustion chamber, thereby achieving high-efficiency combustion. Gas turbines need to operate for a long time in a variety of environments, and have high requirements for their efficiency, power and reliability. Therefore, many specific requirements and parameters are put forward for their performance. The existing technology started late in the research of gas turbines. In the early days, it was mainly through the purchase of Western products, and improvements and designs were made on this basis, especially aero-derivative gas turbines based on modified aircraft engines. However, there are few studies on the design of gas turbines directly using gas fuel on the ground, and the public information is mostly scattered information and not systematic.

[0071] The burners of small gas turbines mostly use diffusion burners due to their low power and low nitrogen oxide emissions. Their structural forms are mainly divided into two categories: A. Silo burners are mostly used for the direct design of ground-based gas turbines. The process and test are relatively simple, and the opening of the flame tube can reduce the pressure fluctuations in the burner. B. Full-annular burners are mostly used in the design of aero-derivative gas turbines. Among them, when aero-derivative gas turbines are in use, due to the need to make more modifications to the gas fuel pipelines, it may lead to mismatches in the burner design, or even mismatches between the compressor and the turbine. In addition, there are certain requirements for the calorific value of the fuel. When upgrading or repairing, most of them use silo burners, which are simpler.

[0072] Therefore, in actual application, aircraft engines usually use liquid fuels, and the design formulas and experience of their combustion chambers are not fully applicable to gas fuels. When the above-mentioned aircraft engine design is directly applied to the combustion chamber of gas fuel, problems such as mismatch of the combustion chamber head and mismatch between the flame shape and the main combustion hole position may occur. The combustion speed, flame temperature and mixture formation characteristics of gas fuel are significantly different from those of liquid fuel, which leads to a decrease in the overall performance of the gas turbine.

[0073] An embodiment of the present invention provides an automated modeling method for a silo-type diffusion burner of a gas turbine. The research and development process of the method starts with a design process, an algorithm is created through the design process, and finally implemented in Python. The structural parameters of components at different positions of the silo-type diffusion burner are set by precise calculation, combined with a preset static pressure value and a target gas flow rate, so that the burner has higher stability in actual work, solves the mismatch problem that is easy to occur in traditional burners when facing gas fuel, and improves the overall performance of the gas turbine.

[0074] An embodiment of the present invention provides an automated modeling method for a gas turbine silo-type diffusion burner, which is applied to modeling scenarios of small gas turbine silo-type diffusion burners, such as scenarios where the gas turbine needs to be modified, upgraded, or redesigned.

[0075] According to an embodiment of the present invention, an embodiment of a method for automated modeling of a gas turbine silo-type diffusion burner is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0076] In this embodiment, a method for automatically modeling a gas turbine silo type diffusion burner is provided, which can be used for the above-mentioned computer. Figure 1 is a flow chart of an automatic modeling method for a gas turbine silo type diffusion burner according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0077] Step S101, obtaining the preset performance requirements, preset size restrictions, and overall input parameters of the target burner under full load conditions, wherein the preset performance requirements represent the physical and / or chemical performance indicators to be met by the burner during operation, and the above indicators are decomposed using the library cantera and chemical mechanism GRI3.11 in Python to obtain a series of combustion parameters for gas fuels such as flame propagation speed, flame temperature, and ignition time. The preset size restrictions represent the preset constraints of the geometric shape and size of the burner, and the overall input parameters represent the physical parameters of the gas at different inlet positions in the burner under full load.

[0078] It should be noted that the preset performance requirements are target indicators that need to be achieved before designing the burner, such as the radial distribution coefficient of the total temperature of the turbine inlet section, carbon monoxide (CO) emission requirements, nitrogen oxide (NOx) emission requirements, total pressure loss, combustion efficiency, etc. The preset size restrictions are boundary conditions that cannot be separated from the restrictions during the design process. For example, the area, inner and outer diameters of the burner outer cover, the installation angle, area and volume of the flame tube, etc. The overall input parameters are the basic data for the design calculation, such as the total temperature and total pressure at the burner inlet.

[0079] It is understandable that in the early stages of burner design, the objectives and constraints of the designed burner must be clearly defined to ensure that the designed burner meets the requirements. Specifically, when determining and recording the performance objectives and design constraints of the burner, it is necessary to obtain reference information according to engineering standards, user requirements, etc., and define the preset performance indicators and dimensions based on the reference information and combined with the experimental data or empirical data of the burner.

[0080] Step S102, setting structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions.

[0081] It should be noted that the structural parameters of the burner components are designed based on the preset performance requirements, size restrictions and input parameters in the previous step, which determine the airflow distribution and combustion characteristics of the final designed burner. For example, the length, diameter, opening position of the flame tube, the position and angle of the igniter and fuel nozzle, and the geometric shape and size of the combustion head.

[0082] Specifically, fluid dynamics simulation can be used to simulate the effects of different structural parameters on the flow field and combustion efficiency, thereby determining different structural parameters, or a fluid dynamics optimization algorithm can be used to determine the optimal combination of structural parameters.

[0083] Step S103, calculating the target gas flow at different outlets in the burner according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets on the burner, wherein the target gas flow represents the total flow of the gas at the outlet.

[0084] It should be noted that the target gas flow rate refers to the total flow rate that needs to be achieved at each outlet of the burner, which determines the working efficiency and performance of the burner.

[0085] Specifically, the fluid mechanics equation is combined with CFD simulation to calculate the gas flow rate of different outlets. During the simulation iterative calculation process, the preset static pressure value is input in real time, and the input parameters during the simulation iterative calculation process cannot exceed the preset size limit.

[0086] Step S104, determining a target static pressure parameter at the outlet that matches the target gas flow rate.

[0087] Specifically, based on the relationship between flow and pressure (for example, preset relationships such as flow and pressure characteristic curves and pressure loss models), the outlet static pressure value is adjusted, and the optimal outlet static pressure parameters are found through iterative simulation and optimization.

[0088] Step S105, after the target static pressure parameters at all outlets are obtained, a target burner is constructed using an automated modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets.

[0089] It should be noted that the automated modeling tool refers to the computer-aided design (CAD) software used to build the burner structure. This tool can generate a three-dimensional model of the burner based on the input structural parameters and static pressure parameters. The target static pressure parameter refers to the static pressure value required at each outlet to match the target gas flow rate, which is a key parameter that needs to be calculated.

[0090] Specifically, the burner model is generated by using the input structural parameters and static pressure parameters through CAD software modeling, and after generation, simulation tests can be performed again to measure the performance of the burner under full load conditions.

[0091] The embodiment of the present invention obtains the preset performance requirements, preset size restrictions, and overall input parameters of the target burner under full load conditions, wherein the preset performance requirements characterize the physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions characterize the preset constraints on the geometric shape and size of the burner, and the overall input parameters characterize the physical parameters of the gas at different inlet positions in the burner under full load; by obtaining the preset performance requirements and size restrictions of the burner, chemical mechanisms and physical and chemical mechanisms are introduced into the design of the burner head, rather than relying entirely on empirical data, which can more accurately predict the flame combustion behavior in the combustion chamber. Based on the preset performance requirements, preset size restrictions, and the overall input parameters of the burner under full load conditions, the structural parameters of the components at different positions on the silo-type diffusion burner are set, and modeling and design are performed according to the overall input parameters under full load conditions, and the characteristics of gas fuel flame combustion are combined to ensure that the modeling and design of the burner are more in line with actual application requirements. According to the structural parameters of components at different positions and the preset static pressure values ​​of different outlets on the burner, the target gas flow at different outlets in the burner is calculated, where the target gas flow represents the total flow of gas at the outlet; the target static pressure parameters at the outlet that match the target gas flow are determined according to the target gas flow; after the target static pressure parameters at all outlets are obtained, the target burner is constructed using an automated modeling tool based on the structural parameters of components at different positions and the target static pressure parameters at all outlets. By accurately calculating and setting the structural parameters of components at different positions of the silo-type diffusion burner, combined with the preset static pressure value and the target gas flow, the burner is made more stable in actual work, solving the mismatch problem that traditional burners are prone to when facing gas fuels, and improving the overall performance of the gas turbine.

[0092] In this embodiment, a method for automatic modeling of a gas turbine silo type diffusion burner is provided, which can be used for the above-mentioned computer. The process includes the following steps:

[0093] Step S201, obtaining the preset performance requirements, preset size restrictions, and overall input parameters of the target burner under full load conditions, wherein the preset performance requirements represent the physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions represent the preset constraints on the geometric shape and size of the burner, and the overall input parameters represent the physical parameters of the gas at different inlet positions in the burner under full load. For details, please refer to Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0094] Step S202, setting structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions.

[0095] In an optional embodiment, the overall input parameters include gas flow rate, gas calorific value, total temperature at the burner inlet, and total pressure at the burner inlet; the preset size restrictions include head size restrictions; the preset performance requirements include resistance coefficient, outlet temperature distribution coefficient, combustion efficiency, combustion temperature, internal and external pressure difference, and flame tube head dynamic pressure.

[0096] For details, please refer to Figure 2 , step S202 includes:

[0097] Step S2021, designing the burner head size according to the overall input parameters and the head size limit.

[0098] Step S2022, calculating the total pressure loss based on the burner head size and the total pressure at the burner inlet.

[0099] Step S2023, determining the radius parameters of the flame tube outer cover according to the overall input parameters and the burner head size.

[0100] Step S2024, determining the flame tube radius parameter according to the gas flow rate, gas calorific value, total temperature at the burner inlet, total pressure at the burner inlet, resistance coefficient and total pressure loss.

[0101] Step S2025, determining the flame tube length parameter according to the total pressure loss, the flame tube radius parameter, the flame tube head dynamic pressure and the outlet temperature distribution coefficient.

[0102] Step S2026, determining the number of flame tube nozzles according to the combustion efficiency; wherein the flame tube outer cover radius parameter, the flame tube radius parameter, the flame tube length parameter, and the number of flame tube nozzles together constitute the initial flame tube structural parameters.

[0103] Step S2027, determining the initial swirler structural parameters according to the gas flow rate, gas calorific value, burner inlet total temperature, burner inlet total pressure, and initial flame tube structural parameters.

[0104] Step S2028, performing flame combustion simulation using simulation software according to the initial swirler structural parameters to obtain flame combustion simulation results.

[0105] Step S2029, determining the initial combustion hole parameters based on the simulation results, gas flow rate, gas calorific value, burner inlet total temperature, burner inlet total pressure, and initial flame tube structural parameters.

[0106] Step S20210, determining the wall adiabatic temperature according to the initial combustion hole parameters, gas flow rate, gas calorific value, total temperature at the burner inlet, total pressure at the burner inlet, initial flame tube structural parameters, and combustion temperature.

[0107] Step S20211, performing heat transfer analysis according to the wall adiabatic temperature or the internal and external pressure difference according to the arrangement and combination of different types of preset cooling structures, and determining the target cooling structure combination and the corresponding initial cooling structure parameters.

[0108] It should be noted that in the above steps S2021 to S20210, empirical formulas can be used to calculate the structural parameters of relevant components, and the relevant component structures at least include: burner head, flame tube, swirler, combustion hole, cooling structure. The empirical formula is a design formula verified by historical experimental data and can be directly substituted into the parameters.

[0109] Exemplarily, in step S2021, the burner head size is designed according to the overall input parameters and the head size limit. First, the required combustion chamber cross-sectional area is calculated according to the gas flow rate and the gas calorific value. The burner head diameter D is calculated according to the head cross-sectional area using an empirical formula. In step S2022, based on the burner head diameter D, the total pressure P0 at the burner inlet is combined with the resistance coefficient and the total temperature T0 at the burner inlet, and the total pressure loss P is calculated according to the empirical formula using the density and velocity of the gas itself. In step S2023, according to the burner head diameter D and the designed combustion chamber length L0, the flame tube outer cover radius R0 is designed, and the empirical formula includes the installation clearance of the flame tube outer cover and the flame tube itself. In step S2024, the reference cross-sectional area of ​​the flame tube is calculated using the energy balance equation and the resistance coefficient according to the gas flow rate, gas calorific value, total temperature at the burner inlet, total pressure at the burner inlet, resistance coefficient and total pressure loss, and the flame tube radius length R1 is obtained. In step S2025, the flame tube length parameter L1 is determined according to the total pressure loss, flame tube radius parameter, flame tube head dynamic pressure and outlet temperature distribution coefficient using the same empirical formula. In step S2026, the number of nozzles N is designed using the empirical formula according to the combustion efficiency and the required gas flow rate. In step S2027, the swirl number S and blade angle F of the swirler are calculated using the empirical formula according to the gas flow rate and the initial flame tube structural parameters. In step S2028, the computational fluid dynamics (CFD) simulation software is used to input the initial swirler structural parameters, perform flame combustion simulation, and analyze the simulation results, including the flame temperature field, flow field distribution, etc., from which the axial positions of the flame recirculation zone and the flame high temperature zone are obtained. Step S2029, based on the simulation results and the burner inlet parameters, use empirical formulas to design the size and position of the initial combustion holes, where the combustion holes include: main combustion holes, supplementary combustion holes, and mixing holes. Specifically, (1) the position and flow of the main combustion holes are calculated through the axial position of the recirculation zone and the flame high temperature zone; (2) if the flow of the main combustion hole cannot reach the preset flow target, continue to design the supplementary combustion; (3) the mixing hole is calculated based on the position and flow of the mixing hole. Step S20210, use empirical formulas to calculate the maximum temperature of the flame tube wall, and compare it with the allowable temperature of the material to determine whether it is a suitable cooling structure. Step S20211, use heat transfer analysis methods to calculate the effects of different cooling structures and select the optimal cooling structure.

[0110] In the embodiment of the present invention, the flame tube radius parameter calculated in step S2024 can be calculated by the empirical formula 1 of the aircraft engine burner, as shown below:

[0111]

[0112] Among them, Aref represents the reference cross-sectional area of ​​the flame tube, q represents the burner flow rate, t represents the total temperature at the burner inlet, p represents the total pressure at the burner inlet, a represents the resistance coefficient, and p' represents the total pressure loss. Once the reference cross-sectional area of ​​the flame tube is calculated, the radius length R1 of the circular rocket launcher section can be directly determined.

[0113] Similarly, the flame tube length parameter calculated in step S2025 can be calculated by the empirical formula 2 of the aircraft engine burner, as shown below:

[0114]

[0115] Among them, L1 represents the flame tube length parameter, R1 represents the radius length of the rocket tube section, p' represents the total pressure loss, RefVHead represents the dynamic pressure of the flame tube head, and OTDF represents the outlet temperature distribution coefficient.

[0116] In actual application, the empirical formulas that can be used in other steps can be directly preset and will not be repeated here.

[0117] Step S203, according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets on the burner, the target gas flow rate at different outlets in the burner is calculated, wherein the target gas flow rate represents the total flow rate of the gas at the outlet. Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.

[0118] Step S204, determining the target static pressure parameter at the outlet that matches the target gas flow rate. Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0119] Step S205: After obtaining the target static pressure parameters at all outlets, the target burner is constructed using an automated modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets. Figure 1 Step S105 of the illustrated embodiment will not be described in detail here.

[0120] The embodiment of the present invention gradually determines the parameters of the key components of the burner (burner head, flame tube, swirler, combustion hole, cooling structure) by combining the overall input parameters such as gas flow, calorific value, inlet temperature, inlet total pressure, and head size restrictions. Among them, by accurately calculating the total pressure loss of the burner head, the energy loss in the combustion process can be effectively controlled. The introduction of parameters such as combustion temperature, outlet temperature distribution coefficient and combustion efficiency improves the stability and combustion efficiency of the combustion process. In the subsequent steps, flame combustion simulation is performed to flexibly adjust the position and size of the combustion hole. The optimal cooling structure is selected through heat transfer analysis, which can effectively reduce the wall temperature and prevent material overheating. The steps are interrelated, and repeated iterations are performed through empirical formulas and simulations to ensure that the parameters of all components are highly matched in the overall burner. Finally, a burner that is more adaptable to physical and chemical mechanisms and has accurate adaptability to adiabatic flame temperature, etc. is modeled.

[0121] In an optional embodiment, an automated modeling method for a gas turbine silo-type diffusion burner provided in this embodiment further includes: dividing the burner into a plurality of cross-sections according to the gas flow direction in the burner based on the initial combustion hole parameters and the initial cooling component structure parameters; performing isentropic calculation on each divided cross-section to obtain parameters of each cross-section.

[0122] In a specific embodiment, the burner is divided into multiple sections according to the gas flow direction in the burner based on the initial combustion hole parameters and the initial cooling component structural parameters, including: (1) firstly selecting points with important structural changes or functional changes in the burner as the basic positions for dividing the sections, such as: the inlet position of the combustion hole, the outlet position of the swirler, the outer cover at different positions of the flame tube, etc.; (2) secondly, along the path of the gas flow inside the burner, the burner is divided into multiple sections to ensure that each section has consistent airflow direction and structural characteristics; (3) then according to the size, shape, position of the initial combustion hole and the arrangement of the cooling components, the position of the section is accurately divided, and the local flow characteristics and heat transfer characteristics can be analyzed on each section, wherein the number and spacing of the sections should be determined based on the cooling requirements of the gas flow in the burner. If the structure of a certain section changes dramatically or the temperature gradient is large, the spacing of the sections should be reduced.

[0123] In another specific embodiment, isentropic calculation is performed on each divided cross section to obtain the parameters of each cross section, including: (1) for each cross section, a thermodynamic model of isentropic flow is established, and the pressure, temperature, density and other parameters on each cross section are calculated using the isentropic relationship; (2) during the isentropic calculation process, the combustion hole parameters and the cooling structure parameters are combined to adjust the local temperature and pressure changes in the calculation, and for each divided cross section, isentropic calculation is performed in sequence from the burner inlet to the outlet to obtain the thermodynamic parameters of each cross section, and the thermodynamic parameters are gradually corrected in the cyclic iteration.

[0124] The embodiment of the present invention can accurately determine the changes in the airflow inside the burner through the fine division and isentropic calculation of multiple cross-sections of the burner, and based on the detailed cross-sectional analysis, make the calculated shape and size of each cross-section of the burner more consistent with the actual thermodynamic changes, thereby further improving the accuracy of burner modeling.

[0125] In an optional embodiment, the preset cooling structure includes a ribbed enhanced cooling structure, an impingement cooling structure, a convection cooling structure, an air film cooling structure, and a seepage cooling structure; Figure 3 , step S20211, specifically includes:

[0126] Step A1, calculating the heat transfer coefficient of the lower burner with different cooling structures based on a preset empirical formula.

[0127] Step A2, calculating the actual wall temperature according to the heat transfer coefficient and the wall adiabatic temperature, and performing temperature distribution analysis based on the actual wall temperature, and selecting a target cooling structure combination and corresponding initial cooling structure parameters from permutations and combinations of different types of preset cooling structures according to the temperature distribution analysis results.

[0128] Step A3, alternatively, calculate the pressure ratio according to the heat transfer coefficient and the internal and external pressure difference, and perform cold air flow analysis based on the pressure ratio, and select the target cooling structure combination and the corresponding initial cooling structure parameters from the permutations and combinations of different types of preset cooling structures according to the cold air flow analysis results.

[0129] Exemplarily, the five cooling structures in the above step A1 (ribbed enhanced cooling structure, impingement cooling structure, convection cooling structure, air film cooling structure, and seepage cooling structure) have their own corresponding calculation methods for heat transfer coefficients.

[0130] Method 1: Calculate the heat transfer coefficient of the burner with ribbed enhanced cooling structure. For details, refer to Figure 3, set the empirical formula as a computer program, and the input parameters include: rib geometric parameters (including arrangement angle (alfa), rib height (e), rib pitch (p)), cooling air velocity and its physical and chemical properties, pipeline hydraulic diameter (that is, channel height D). The final output is the heat transfer coefficient (h), which will be used in the overall program to judge the cooling effect and the corresponding parameters (flow rate, static pressure), so as to judge whether the cooling structure is suitable. The specific calculation process includes, the following statement uses python3.11:

[0131] (1) Calculation of Reynolds number (Re), the empirical formula is:

[0132] Re=Rou*u*D / Vis;

[0133] Where Rou is the fluid density, u is the fluid velocity, and Vis is the dynamic viscosity.

[0134] (2) Calculation of the initial coefficient (a0), if alfa>45°, then n=0, otherwise n=0.17. The empirical formula is:

[0135] a0=15.6-31.6*(alfa)+21.1*alfa*alfa;

[0136] (3) The calculation formula of the correction coefficient (a1) is:

[0137] a1=a0*(np.power(P / e / 10,0.35)*np.power(0.003*e*Re / D,n));

[0138] (4) The calculation formula of the intermediate variable (a2) is:

[0139] a2=2.5*np.log(2*e / D)+2.5;

[0140] (5) Newton iteration method is used to calculate the variables g0 and (delta), the formula is:

[0141] g0=1. / (a1-a2);

[0142] The initial value (delta) is set to 1, and the error is made small enough through iteration to obtain g.

[0143] (6) Calculate the corrected variable. The empirical formula is:

[0144] eplus=(e / D)*Re*g;

[0145] Then there is a corresponding empirical formula for calculating the average value of the momentum function:

[0146] Rave = 1. / g + a2;

[0147] (7) Calculate the average heat transfer function, the empirical formula is:

[0148] Hr=2.83*np.power(alfa,0.3)*np.power(eplus,0.28)*np.power(P / e / 10.,0.14);

[0149] (8) The calculation of Stanton number (St) is based on the empirical formula:

[0150] St = g / (Hr-Rave+1. / g);

[0151] (9) Calculation of Nusselt number (Nu), Pr Prandtl number can be calculated:

[0152] Nu=St*Re*Pr;

[0153] (10) Finally, the designed heat transfer coefficient can be obtained:

[0154] h=Nu*k / D;

[0155] The computer program corresponding to method 1 is as follows:

[0156]

[0157]

[0158] Method 2: Calculate the heat transfer coefficient of the burner under the impingement cooling structure. For details, refer to Figure 4 , set the empirical formula as a computer program, and the input parameters include: the distribution of impingement cooling holes along the flow direction and span direction, the number of holes, the arrangement pattern of holes (neatly arranged or staggered), the inner and outer diameters of the channel, the size of the holes and the channel height. The specific calculation process includes the nonlinear polynomial fitted by the experiment, which can be used to calculate the Nusselt number and thus the convective heat transfer coefficient. The following is a calculation formula for an impingement jet with staggered holes as an example:

[0159]

[0160] Among them, A and B are constants. m and n represent exponents, which depend on geometric parameters. Gj represents the jet mass flow rate based on the area of ​​the jet hole, Gc represents the channel cross-flow mass flow rate based on the cross-sectional area of ​​the channel, d represents the diameter of the jet hole, Pr represents the Prandtl number, and z represents the height of the impact cooling channel, that is, the distance from the jet to the impact position. Through the above formula, the Nusselt number Nu can be calculated to obtain the heat transfer coefficient h. The final output is the heat transfer coefficient (h), which will be used in the overall program to judge the cooling effect and the corresponding parameters (flow rate, static pressure), so as to judge whether the cooling structure is suitable. The specific calculation process includes, the following statements use python3.11.

[0161] The computer program corresponding to method 2 is as follows:

[0162]

[0163]

[0164] Method 3: Calculate the heat transfer coefficient of the burner under the convection cooling structure. For details, refer to Figure 5 , set the empirical formula as a computer program, and the input parameters include: thermodynamic properties of gas (such as thermal conductivity, dynamic viscosity, specific heat capacity at constant pressure, density), cooling area, distance to the burner, hydraulic diameter, and flow rate. The specific calculation process includes:

[0165] (1) Calculate the Prandtl number (Pr) using the formula:

[0166] Pr = Vis * Cp / k;

[0167] (2) Calculate the flow velocity (u) and Reynolds number (Re). When there is a large temperature difference between the gas T_gas and the wall Tw, if the fluid is heated n = 0.55, and the fluid is cooled n = 0, further calculate the Nusselt number (Nu), the formula is:

[0168] Nu=0.021*np.power(Re,0.8)*np.power(Pr,0.43)*np.power(T_Gas / Tw,n);

[0169] (3) The heat transfer coefficient (h) is calculated based on the Nusselt number using the formula:

[0170] h=k*Nu / Dia;

[0171] In the above formula, Gas represents the input variable of the thermodynamic properties of the gas, Tw represents the temperature of the wall, Rou represents the density of the gas, k represents the thermal conductivity of the gas, Vis represents the dynamic viscosity of the gas, Cp represents the constant pressure specific heat capacity of the gas, Pr represents the Prandtl number, u represents the flow rate, Re represents the Reynolds number, n represents the exponent used to correct the Nusselt number, and Nu represents the Nusselt number. The final output is the heat transfer coefficient (h), which will be used in the overall program to judge the cooling effect and the corresponding parameters (flow rate, static pressure), so as to judge whether the cooling structure is suitable. The specific calculation process includes the following statements using python3.11:

[0172] The computer program corresponding to method 3 is as follows:

[0173]

[0174] Method 4: Calculate the heat transfer coefficient of the burner under the impingement cooling structure. Specifically, you can use strip air films and stacked air films with total pressure as the driving force, or riveting or welding driven by static pressure, or machined air film rings driven by total pressure and static pressure at the same time for more precise control. Set the empirical formula as a computer program, and the input parameters include: gas parameters at the gas end and the cold air end, such as thermal conductivity, dynamic viscosity, constant pressure specific heat capacity, density, etc. By comparing the momentum on both sides of the gas and cold air, combined with the preliminary designed air film geometry parameters (slot height SlotHeight) and burner geometry parameters (outer diameter LinerRo) and considering the influence of the cooling air film on the heat transfer coefficient, the convective heat transfer coefficient (h) can be obtained. The specific calculation process includes:

[0175] (1) Assume momentum ratio m = (cooling air velocity vel_air1*cooling air density rou_air) / (gas velocity vel_air2*gas density rou_air);

[0176] (2) Based on the thermal conductivity of air k_a, the thermal conductivity of gas k_g, the dynamic viscosity coefficients of air and gas Vis_a, Vis_g, and the volume heat capacity of the two Cp_a, Cp_g, the Reynolds number Re of the cold air can be calculated. Based on the air film outlet area Ao, it can be calculated:

[0177] (3) When m<1.3, calculate the heat transfer coefficient using the formula:

[0178] h=0.069*k_a*np.power(Re_x,0.7) / x;

[0179] (4) When m>=1.3, the heat transfer coefficient is calculated as follows:

[0180] h=0.100*k_a*np.power(Re,0.8) / x*np.power(x / SlotHeight,-0.36);

[0181] In the above formula, m represents the momentum ratio, Re_x represents the Reynolds number, x represents the axial distance from the downstream to the air film hole, that is, the distance from the air film hole to a point downstream in the flow direction, and SlotHeight represents the slot height.

[0182] The computer program corresponding to method 4 is as follows:

[0183]

[0184] Method 5: Calculate the burner flow coefficient under the seepage cooling structure. For details, refer to Figure 6 , set the empirical formula as a computer program. The specific calculation process includes: selecting different shape fitting parameters according to the type of hole (flat edge, flange, row hole, machined hole, etc.), combining the total pressure difference and static pressure difference inside and outside the flame tube, normalizing the cold air driving force, and correlating it with the internal and external static pressure ratio and the flow coefficient, and obtaining the flow coefficient after the hole shape correction. In the iterative process, the jet angle is corrected according to the inclination of the flame tube wall. Among them, the intermediate parameter K is based on the pressure loss of the cooling hole and the pressure loss of the cooling hole. The final return value is the flow coefficient Cd.

[0185] The computer program corresponding to method 5 is as follows. The types of holes are flat edge, flanged edge, and machined hole:

[0186]

[0187]

[0188] After the above five calculation methods are completed, in step A2, according to the calculated heat transfer coefficient, the wall adiabatic temperature and the heat flux per unit area are used to determine the specific actual wall temperature. The temperature distribution on the entire wall is analyzed through numerical simulation or empirical formulas. The analysis results include temperature gradient, hot spot area and average temperature. According to the temperature distribution analysis results, a cooling structure combination that can minimize the temperature of the hot spot area and ensure uniform overall temperature distribution is selected.

[0189] Alternatively, in step A3, the pressure ratio is used to determine the cold air flow rate, that is, the amount of coolant flowing through the cooling structure. The cold air flow rate for each cooling structure combination is calculated through simulation or experimental data. Based on the cold air flow rate analysis results, the cooling structure combination that achieves the expected cooling effect at the lowest cold air flow rate is selected.

[0190] The embodiment of the present invention calculates the heat transfer coefficients for the five cooling structures respectively, and can more accurately determine the heat exchange efficiency of the burner under different cooling structures, thereby maximizing the cooling efficiency, reducing the operating temperature of the burner, and thus extending the service life of the modeled burner.

[0191] In a specific embodiment, step A2 specifically includes:

[0192] A21, arranging the preset cooling structure at different positions of the burner to obtain permutations and combinations at different positions, wherein each permutation and combination comprises a plurality of cooling structures at different positions;

[0193] A22, calculate the overall actual wall temperature corresponding to each arrangement and combination according to the actual wall temperature of different cooling structures;

[0194] A23, determining a target overall actual wall temperature from a plurality of overall actual wall temperatures, and determining a target cooling structure combination corresponding to the target overall actual wall temperature and corresponding initial cooling structure parameters, wherein the target overall actual wall temperature represents the lowest temperature among all temperatures.

[0195] The embodiment of the present invention sets preset cooling structures at different positions of the burner and arranges and combines them. By calculating and comparing the actual overall wall temperature of each arrangement and combination, the most suitable cooling structure combination can be found, and the wall temperature distribution of the burner is more uniform, thereby further extending the service life of the modeled target burner.

[0196] In a specific embodiment, step A3 specifically includes:

[0197] A31, arranging the preset cooling structure at different positions of the burner to obtain permutations and combinations at different positions, wherein each permutation and combination comprises a plurality of cooling structures at different positions;

[0198] A32, calculating the cold air flow corresponding to each arrangement combination according to the pressure ratio and the preset gas flow;

[0199] A33, selecting a target cold air flow rate higher than a preset cold air flow rate from a plurality of cold air flow rates, and determining a target cooling structure combination corresponding to the target cold air flow rate and a corresponding initial cooling structure parameter.

[0200] The embodiment of the present invention analyzes the cooling structures of different arrangements and combinations and calculates the cold air flow rate under each combination, so as to better match the actual cooling requirements, thereby optimizing the cooling effect of the final target burner, avoiding overcooling or insufficient cooling, and making the modeling of the target burner more accurate and in line with actual needs.

[0201] In an optional implementation, determining a target static pressure parameter at an outlet that matches the target gas flow rate specifically includes:

[0202] B1, when it is calculated that the target gas flow at the current outlet is within the preset flow range, the preset static pressure value is used as the target static pressure parameter of the current burner outlet;

[0203] B2, when it is calculated that the target gas flow at the current outlet exceeds the preset flow range, the preset static pressure value is reset, and the target gas flow at the current outlet is calculated again, until the target gas flow at the current outlet is within the preset flow range, and the corresponding preset static pressure value is used as the target static pressure parameter of the current outlet of the burner.

[0204] It can be understood that in B1, the target gas flow at the current outlet is first calculated. If the calculated gas flow is within the preset flow range, no further adjustment is required, and the current preset static pressure value is directly used as the target static pressure parameter of the outlet. In the current situation, the initially set static pressure parameter can already guarantee the required gas flow, so no additional recalculation or adjustment is required. In B2, if the calculated target gas flow exceeds the preset flow range, it indicates that the current preset static pressure value cannot meet the flow requirement. At this time, the preset static pressure value is reset, and the target gas flow of the current outlet is calculated again. The current calculation process will continue, that is, each time the static pressure value is adjusted, the flow needs to be recalculated until the flow falls within the preset range. Finally, the static pressure value that makes the gas flow meet the requirements is determined as the target static pressure parameter.

[0205] The embodiment of the present invention ensures that the gas flow rate at the burner outlet is always maintained within a preset range by real-time calculation and adjustment of the target static pressure parameters. During the modeling process, the actual operating conditions can be better matched with the theoretical parameters, thereby reducing the burner modeling error caused by the mismatch between static pressure and flow rate.

[0206] In this embodiment, a gas turbine silo type diffusion burner automatic modeling system is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0207] This embodiment provides a gas turbine silo type diffusion burner automatic modeling system, such as Figure 7 As shown, including:

[0208] The burner initial condition acquisition module 701 is used to obtain the preset performance requirements, preset size restrictions, and overall input parameters of the burner under full load conditions of the target burner, wherein the preset performance requirements represent the physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions represent the preset constraints on the geometric shape and size of the burner, and the overall input parameters represent the physical parameters of the gas at different inlet positions in the burner under full load;

[0209] A burner structural parameter setting module 702 is used to set structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions;

[0210] The target gas flow calculation module 703 is used to calculate the target gas flow at different outlets in the burner according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets on the burner, wherein the target gas flow represents the total flow of the gas at the outlet;

[0211] A target static pressure parameter determination module 704 is used to determine a target static pressure parameter at an outlet that matches the target gas flow rate according to the target gas flow rate;

[0212] The burner automatic modeling module 705 is used to construct a target burner using an automatic modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets after obtaining the target static pressure parameters at all outlets.

[0213] The further functional description of each of the above modules and the corresponding optional implementation methods are the same as those of the above corresponding embodiments and will not be repeated here.

[0214] The gas turbine silo diffusion burner automatic modeling system in this embodiment is presented in the form of functional units, where the units refer to ASIC (Application Specific Integrated Circuit) circuits, processors and memories that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0215] The embodiment of the present invention also provides a computer device having the above Figure 7 The automated modeling system for a gas turbine silo-type diffusion burner is shown.

[0216] See also Figure 8 , Figure 8 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 8As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 8 A processor 10 is taken as an example.

[0217] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0218] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0219] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0220] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0221] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0222] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0223] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0224] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the claims.

Claims

1. An automated modeling method for a gas turbine silo diffusion burner, characterized in that: The method comprises: Obtaining preset performance requirements, preset size restrictions, and overall input parameters of the target burner under full load conditions, wherein the preset performance requirements represent physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions represent preset constraints on the geometric shape and size of the burner, and the overall input parameters represent physical parameters of the gas at different inlet positions in the burner under full load; Setting structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions; Calculate the target gas flow rates at different outlets of the burner according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets of the burner, wherein the target gas flow rate represents the total flow rate of the gas at the outlet; Determining a target static pressure parameter at an outlet that matches the target gas flow rate according to the target gas flow rate; After the target static pressure parameters at all outlets are obtained, the target burner is constructed using an automated modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets.

2. The method according to claim 1, characterized in that The overall input parameters include gas flow, gas calorific value, total burner inlet temperature, and total burner inlet pressure; the preset size restrictions include head size restrictions; the preset performance requirements include resistance coefficient, outlet temperature distribution coefficient, combustion efficiency, combustion temperature, internal and external pressure difference, and flame tube head dynamic pressure; The setting of structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions specifically includes: Design the burner head size based on the overall input parameters and head size constraints; Calculating the total pressure loss based on the burner head size and the total pressure at the burner inlet; Determine the radius parameter of the flame tube outer cover according to the overall input parameters and the burner head size; Determine the flame tube radius parameter according to the gas flow rate, gas calorific value, total temperature of the burner inlet, total pressure of the burner inlet, resistance coefficient and total pressure loss; Determine the flame tube length parameter according to the total pressure loss, the flame tube radius parameter, the flame tube head dynamic pressure and the outlet temperature distribution coefficient; Determine the number of flame tube nozzles according to the combustion efficiency; wherein the flame tube outer cover radius parameter, the flame tube radius parameter, the flame tube length parameter, and the number of flame tube nozzles together constitute the initial flame tube structure parameter; Determining the initial swirler structural parameters according to the gas flow rate, gas calorific value, total burner inlet temperature, total burner inlet pressure, and initial flame tube structural parameters; According to the initial cyclone structural parameters, a flame combustion simulation is performed using a simulation software to obtain a flame combustion simulation result; Determining initial combustion hole parameters based on the simulation results, gas flow rate, gas calorific value, total burner inlet temperature, total burner inlet pressure, and initial flame tube structural parameters; Determining the wall adiabatic temperature according to the initial combustion hole parameters, gas flow rate, gas calorific value, total burner inlet temperature, total burner inlet pressure, initial flame tube structural parameters, and combustion temperature; According to the wall adiabatic temperature or the internal and external pressure difference, heat transfer analysis is performed according to the arrangement and combination of different types of preset cooling structures to determine the target cooling structure combination and the corresponding initial cooling structure parameters.

3. The method according to claim 2, characterized in that The method further comprises: Dividing the burner into a plurality of cross sections according to the gas flow direction in the burner based on the initial combustion hole parameters and the initial cooling component structure parameters; The isentropic calculation is performed on each divided cross section to obtain the parameters of each cross section.

4. The method according to claim 2, characterized in that: The preset cooling structure includes a ribbed enhanced cooling structure, an impingement cooling structure, a convection cooling structure, an air film cooling structure, and a seepage cooling structure; The heat transfer analysis is performed according to the wall adiabatic temperature or the internal and external pressure difference according to the arrangement and combination of different types of preset cooling structures to determine the target cooling structure combination and the corresponding initial cooling structure parameters, specifically including: Calculate the heat transfer coefficient of the lower burner with different cooling structures based on a preset empirical formula; Calculating the actual wall temperature according to the heat transfer coefficient and the wall adiabatic temperature, performing temperature distribution analysis based on the actual wall temperature, and selecting a target cooling structure combination and corresponding initial cooling structure parameters from permutations and combinations of different types of preset cooling structures according to the temperature distribution analysis results; Alternatively, the pressure ratio is calculated according to the heat transfer coefficient and the internal and external pressure difference, and a cold air flow analysis is performed based on the pressure ratio. According to the cold air flow analysis results, a target cooling structure combination and corresponding initial cooling structure parameters are selected from permutations and combinations of different types of preset cooling structures.

5. The method according to claim 4, characterized in that The temperature distribution analysis is performed based on the actual wall temperature, and a target cooling structure combination and corresponding initial cooling structure parameters are selected from permutations and combinations of different types of preset cooling structures according to the temperature distribution analysis result, specifically including: The preset cooling structure is arranged at different positions of the burner to obtain different arrangement combinations at different positions, wherein each arrangement combination includes multiple cooling structures at different positions; Calculate the overall actual wall temperature corresponding to each arrangement and combination according to the actual wall temperature of different cooling structures; A target overall actual wall temperature is determined from a plurality of overall actual wall temperatures, and a target cooling structure combination corresponding to the target overall actual wall temperature and corresponding initial cooling structure parameters are determined, wherein the target overall actual wall temperature represents the lowest temperature among all temperatures.

6. The method according to claim 4, characterized in that The cold air flow analysis is performed based on the pressure ratio, and a target cooling structure combination and corresponding initial cooling structure parameters are selected from permutations and combinations of different types of preset cooling structures according to the cold air flow analysis result, specifically including: The preset cooling structure is arranged at different positions of the burner to obtain different arrangement combinations at different positions, wherein each arrangement combination includes multiple cooling structures at different positions; Calculate the cold air flow rate corresponding to each arrangement and combination according to the pressure ratio and the preset gas flow rate; A target cold air flow rate higher than a preset cold air flow rate is selected from a plurality of cold air flow rates, and a target cooling structure combination corresponding to the target cold air flow rate and a corresponding initial cooling structure parameter are determined.

7. The method according to any one of claims 1 to 6, characterized in that: Determining a target static pressure parameter at an outlet matching the target gas flow rate specifically includes: When it is calculated that the target gas flow at the current outlet is within the preset flow range, the preset static pressure value is used as the target static pressure parameter of the current burner outlet; When it is calculated that the target gas flow at the current outlet exceeds the preset flow range, the preset static pressure value is reset and the target gas flow at the current outlet is calculated again until the target gas flow at the current outlet is within the preset flow range. The corresponding preset static pressure value is used as the target static pressure parameter of the current outlet of the burner.

8. An automatic modeling system for gas turbine silo diffusion burners, characterized in that: The system comprises: A burner initial condition acquisition module, used to acquire preset performance requirements, preset size restrictions, and overall input parameters of the burner under full load conditions of the target burner, wherein the preset performance requirements represent physical and / or chemical performance indicators to be met by the burner during operation, the preset size restrictions represent preset constraints on the geometric shape and size of the burner, and the overall input parameters represent physical parameters of the gas at different inlet positions in the burner under full load; A burner structural parameter setting module, used to set structural parameters of components at different positions on the silo type diffusion burner based on the preset performance requirements, preset size restrictions and overall input parameters of the burner under full load conditions; A target gas flow calculation module is used to calculate the target gas flow at different outlets in the burner according to the structural parameters of the components at different positions and the preset static pressure values ​​of different outlets on the burner, wherein the target gas flow represents the total flow of the gas at the outlet; A target static pressure parameter determination module, used to determine a target static pressure parameter at an outlet that matches the target gas flow rate; The burner automatic modeling module is used to construct a target burner using an automatic modeling tool based on the structural parameters of the components at different positions and the target static pressure parameters at all outlets after obtaining the target static pressure parameters at all outlets.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the automatic modeling method for a gas turbine silo-type diffusion burner according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the automatic modeling method for a gas turbine silo-type diffusion burner according to any one of claims 1-7.

11. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the automatic modeling method for a gas turbine silo-type diffusion burner according to any one of claims 1 to 7.

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