Integrated design method and system for three-dimensional simulation model of natural gas burner

Abstract

The present invention relates to the field of model design technology, and in particular to an integrated design method and system for a three-dimensional simulation model of a natural gas burner. The method comprises the following steps: collecting geometric parameters and operating parameters of the natural gas burner to obtain initial device parameter information; performing laser micro-texturing on the inner surface of the combustion chamber of the natural gas burner to generate periodic micro-groove array data; constructing a three-dimensional initial model of the natural gas burner using three-dimensional modeling software based on the initial device parameter information and the periodic micro-groove array data; obtaining natural gas fuel characteristic data, inputting the fuel characteristic data into the three-dimensional initial model to simulate the combustion process, and performing a multi-dimensional evaluation of the simulated combustion process to generate a combustion process evaluation result. The present invention solves the problems of low efficiency, high optimization difficulty, and lack of real-time feedback in traditional designs through three-dimensional modeling, combustion simulation, and dynamic optimization and adjustment, and significantly improves the design accuracy and combustion performance of the natural gas burner.

Description

Technical Field

[0001] The present invention relates to the technical field of model design, and in particular to an integrated design method and system for a three-dimensional simulation model of a natural gas burner. Background Art

[0002] Early natural gas burner designs relied primarily on empirical models and experimental verification, resulting in long design cycles, high costs, and difficulties in achieving optimal performance. With the maturity of computational fluid dynamics (CFD) technology, the application of three-dimensional simulation models has gradually developed. Engineers can use numerical simulations to analyze key parameters during the combustion process, such as airflow, temperature distribution, and pollutant emissions, providing a scientific basis for burner design. With the advancement of computing power and the continuous improvement of simulation software, CFD-based three-dimensional simulation models have become widely used in natural gas burner design. By accurately simulating the combustion chamber, gas injection system, and their interactions, designers can optimize the burner's structure and operating parameters, achieving higher combustion efficiency and lower pollutant emissions. Current three-dimensional simulation models for natural gas burners are not limited to airflow and combustion simulations but also integrate comprehensive analysis from multiple fields, such as thermodynamics and electromagnetic fields, providing more comprehensive technical support for efficient and safe burner operation. However, current combustion process evaluation often lacks comprehensive analysis from multiple dimensions, hindering the precise control of combustion efficiency and pollutant emissions. Furthermore, the design process often lacks real-time monitoring and feedback, making it difficult to detect problems and adjust design parameters in a timely manner. This, in turn, results in low design accuracy and combustion performance in natural gas burner simulation models. Summary of the Invention

[0003] Based on this, it is necessary to provide an integrated design method and system for a three-dimensional simulation model of a natural gas burner to solve at least one of the above technical problems.

[0004] To achieve the above object, an integrated design method for a three-dimensional simulation model of a natural gas burner is provided, the method comprising the following steps:

[0005] Step S1: Collecting geometric parameters and operating parameters of the natural gas burner to obtain initial device parameter information; performing laser microtexturing on the combustion chamber inner surface of the natural gas burner to generate periodic microgroove array data; and constructing a three-dimensional initial model of the natural gas burner using three-dimensional modeling software based on the initial device parameter information and the periodic microgroove array data.

[0006] Step S2: Obtaining natural gas fuel characteristic data, inputting the fuel characteristic data into a three-dimensional initial model to simulate the combustion process, and performing a multi-dimensional evaluation of the simulated combustion process to generate a combustion process evaluation result;

[0007] Step S3: Optimizing the three-dimensional initial model based on the combustion process evaluation results. If the combustion process evaluation results do not reach a preset combustion efficiency threshold, the nozzle structure, fuel mixing parameters, and combustion chamber geometric characteristics are collaboratively adjusted to generate a three-dimensional optimized model.

[0008] Step S4: Integrate the three-dimensional optimization model into the combustion control system to conduct actual combustion tests, monitor the flame morphology and temperature field distribution through a high-temperature thermal imager, and obtain combustion feedback data; dynamically calibrate the parameters of the three-dimensional optimization model based on the combustion feedback data to generate a high-precision three-dimensional simulation model of the natural gas burner.

[0009] This invention collects equipment geometry and operating parameters and, in conjunction with fuel characteristics, performs multidimensional combustion process simulation and dynamic optimization. This allows for coordinated control of nozzle structure, fuel mixture ratio, and combustion chamber morphology, significantly improving combustion efficiency and reducing energy waste. Actual combustion feedback data is used to dynamically calibrate the three-dimensional optimization model, creating a highly reliable and adaptable three-dimensional simulation model, providing a reliable basis for subsequent design improvements and control system optimization. Laser microtexturing creates a periodic microgroove array, which enhances heat conduction and airflow disturbance, improving combustion stability and flame morphology, and further enhancing thermal energy utilization. The simulation model is integrated with the combustion control system, and the design process is optimized through high-temperature thermal imaging feedback. This creates an intelligent closed-loop design-simulation-testing-feedback system, driving the development of digital and intelligent combustion systems. Precisely controlling combustion parameters ensures complete fuel combustion and reduces the generation of incomplete combustion products (such as CO and NOx), helping to reduce industrial emissions and enhance environmental performance. Three-dimensional modeling and simulation analysis replace traditional trial-and-error experiments, effectively shortening design iteration cycles, reducing R&D testing costs, and improving engineering development efficiency. Therefore, the present invention solves the problems of low efficiency, difficulty in optimization and lack of real-time feedback in traditional designs through three-dimensional modeling, combustion simulation and dynamic optimization adjustment, and significantly improves the design accuracy and combustion performance of natural gas burners.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: using a multi-source sensor to collect geometric parameters and operating parameters of the natural gas burner to obtain initial equipment parameter information;

[0012] Step S12: extracting the internal surface temperature distribution data of the combustion chamber of the natural gas burner based on the initial equipment parameter information, and performing airflow scouring path analysis on the natural gas burner based on the internal surface temperature distribution data of the combustion chamber, generating high heat load areas and main heat transfer path areas, and uniformly marking them as laser microtexturing priority processing area data;

[0013] Step S13: performing laser microtexturing on the inner surface of the combustion chamber of the natural gas burner based on the laser microtexturing priority processing area data using femtosecond laser pulses to generate periodic microgroove array structure data;

[0014] Step S14: Based on the initial device parameter information set and the periodic micro-groove array structural parameter data, a three-dimensional initial structural model of the natural gas burner is constructed in a three-dimensional modeling software, wherein the construction process includes:

[0015] Establish the geometric entities of the natural gas burner shell and combustion channel;

[0016] Mapping the periodic micro-groove array to the corresponding area of ​​the combustion chamber wall;

[0017] Add operating condition mark points.

[0018] Preferably, performing airflow flushing path analysis on the natural gas burner according to the combustion chamber inner surface temperature distribution data in step S12 includes:

[0019] The thermal field is reconstructed based on the temperature distribution data of the combustion chamber surface to obtain the absolute temperature value and spatial thermal gradient change of each surface node, and a spatial thermal gradient matrix is ​​generated, in which each matrix element contains a three-dimensional coordinate and a corresponding temperature derivative value;

[0020] Based on the spatial thermal gradient matrix, the thermal gradient distribution partitioning and classification of the combustion chamber surface temperature distribution data is performed to generate the thermal partitioning data of the combustion chamber and the inner and outer surfaces;

[0021] A high-heat threshold condition is set and used to perform regional cluster analysis on the thermal partition data of the internal and external surfaces of the combustion chamber. The cluster centers and their associated nodes are extracted to identify high-heat load areas where heat flux is concentrated.

[0022] Perform flow field simulation in high heat load areas to extract the streamline path and velocity vector distribution of the gas in the combustion chamber;

[0023] The scour intensity coefficient of each wall area is calculated based on the streamline path and velocity vector distribution to obtain the airflow scour path intensity map; the scour significant area of ​​the airflow scour path intensity map is screened by the set gas scour threshold to obtain the gas scour significant area;

[0024] The high heat load area and the significant gas scouring area are spatially matched to obtain the main heat transfer path area, and the high heat load area and the main heat transfer path area are subjected to regional intersection operation, and the areas corresponding to the operation results are uniformly marked as laser microtexturing priority processing area data.

[0025] Preferably, performing flow field simulation on the high heat load area includes:

[0026] The combustion chamber geometry model size range is set to 200–500 mm × 200–500 mm × 200–600 mm, the combustion chamber diameter range is 80–150 mm, the length is 200–400 mm, the gas inlet velocity is set between 10–50 m / s, the inlet temperature range is 300–600 K, and the inlet pressure is set to 1.01×10 5 Pa;

[0027] The wall temperature of the high heat load area was set in the range of 900–1500 K, and the outlet pressure was set to 1.01×10 5 Pa, combustion model selects non-premixed combustion model or PDF model.

[0028] Preferably, step S2 includes the following steps:

[0029] Step S21: Acquire natural gas fuel characteristic data;

[0030] Step S22: Inputting the fuel characteristic data into the three-dimensional initial model to construct the combustion process simulation boundary conditions, wherein the boundary conditions include inlet conditions, wall conditions, turbulence model and combustion model;

[0031] Step S23: performing a natural gas combustion process numerical simulation on the fuel characteristic data based on the combustion process simulation boundary conditions to generate a combustion process simulation data set, wherein the natural gas combustion process numerical simulation includes the ignition, heat transfer, diffusion, and emission processes of natural gas in a three-dimensional space;

[0032] Step S24: Perform multi-dimensional quantitative analysis on the combustion process simulation data set to generate a combustion process evaluation result.

[0033] Preferably, if the combustion process evaluation result does not reach a preset combustion efficiency threshold in step S3, then collaboratively adjusting the nozzle structure, fuel mixing parameters, and combustion chamber geometric characteristics includes:

[0034] If the combustion process evaluation result does not reach the preset combustion efficiency threshold, regional combustion anomaly features are extracted from the three-dimensional initial model based on the combustion process evaluation result to obtain a collaborative adjustment target parameter set, where the collaborative adjustment target parameter set includes nozzle exit velocity and angle deviation, air-fuel ratio deviation, and geometric thermal hysteresis zone characteristics;

[0035] The nozzle structure in the three-dimensional initial model is optimized for the curvature of the nozzle internal channel according to the nozzle outlet velocity and angle deviation, and the nozzle structure adjustment data is generated;

[0036] Dynamically control the fuel mixing field of the fuel mixing parameters in the three-dimensional initial model through the air-fuel ratio deviation to generate fuel dynamic mixing field control data;

[0037] The geometric characteristics of the combustion chamber are used to adjust the ratio of the expansion section and the contraction section of the combustion chamber by using the geometric thermal hysteresis zone characteristics, and the local geometric reconstruction data of the combustion chamber is generated;

[0038] The nozzle structure adjustment data, fuel dynamic mixing field control data, and combustion chamber local geometry reconstruction data are coupled and integrated for simulation, and the three-dimensional initial model is optimized using the simulation results to obtain a three-dimensional optimized model.

[0039] Preferably, coupling and integrating the nozzle structure adjustment data, the fuel dynamic mixing field control data, and the combustion chamber local geometry reconstruction data is simulated, and optimizing the three-dimensional initial model through the simulation results includes:

[0040] Perform multi-scale parameter extraction on the nozzle structure adjustment data to generate injection boundary constraint data;

[0041] Conduct time-series segmented modeling of fuel dynamic mixing field control data to generate time-segmented turbulence distribution field data;

[0042] Perform topological slicing and local feature mapping on the local geometric reconstruction data of the combustion chamber to generate structural analysis domain data;

[0043] The injection boundary constraint data, time segmented turbulence distribution field data, and structure analysis domain data are uniformly projected into a master coordinate system for spatial alignment, unit normalization, and scale adjustment to form unified simulation domain coordinate data;

[0044] Based on the cross-domain coupling boundary, multi-field variable coupling integration simulation mapping is performed on the unified simulation domain coordinate data to construct the coupled integrated simulation results;

[0045] The initial 3D model is optimized by coupling the integrated simulation results.

[0046] Preferably, step S4 includes the following steps:

[0047] Step S41: Integrate the three-dimensional optimization model into the combustion control system to perform actual combustion testing;

[0048] Step S42: monitoring the flame morphology and temperature field distribution in the actual combustion test using a high-temperature thermal imager to obtain combustion feedback data;

[0049] Step S43: Analyze the combustion performance of the combustion feedback data, and perform dynamic effect error calibration on the three-dimensional optimization model based on the combustion performance to generate a high-precision three-dimensional simulation model of the natural gas burner.

[0050] Preferably, step S41 includes the following steps:

[0051] Step S411: Start the combustion control system and create an actual combustion test project; import the three-dimensional optimization model into the combustion control system, and input the natural gas fuel characteristic data into the three-dimensional optimization model to generate integrated combustion control model data;

[0052] Step S412: Setting combustion test parameters in the combustion control system, wherein the fuel flow rate is set to 10–30 m³ / h, the air flow rate is set to 20–100 m³ / h, the combustion chamber temperature is set to 900–1500°C, and the combustion duration is set to 600–1800 seconds; generating combustion test parameter setting data;

[0053] Step S413: Setting ignition and preheating parameters in the combustion control system, wherein the ignition energy is set to 1000–1500 J, the preheating temperature is set to 300–600° C., and the preheating time is set to 60–180 seconds; generating ignition and preheating control data;

[0054] Step S414: Start the combustion control system and begin the actual combustion test process; continuously monitor and record key data in the combustion system every 10 seconds, including combustion temperature, combustion pressure, fuel / air mixture ratio, and CO / CO2 / NOx concentrations in the flue gas, to generate a real-time combustion monitoring data sequence;

[0055] Step S415: continuously analyzing the feedback signal of the combustion control system; when it is detected that all test parameters meet the set combustion test parameter range and the emission concentration is lower than the set threshold, it is determined that the actual combustion test process is completed.

[0056] In this specification, an integrated design system for a three-dimensional simulation model of a natural gas burner is provided, which is used to execute the above-mentioned integrated design method for a three-dimensional simulation model of a natural gas burner. The integrated design system for a three-dimensional simulation model of a natural gas burner includes:

[0057] The initial modeling module is used to collect the geometric parameters and operating parameters of the natural gas burner to obtain initial equipment parameter information; perform laser micro-texturing on the combustion chamber surface of the natural gas burner to generate periodic micro-groove array data; and construct a 3D initial model of the natural gas burner using 3D modeling software based on the initial equipment parameter information and periodic micro-groove array data.

[0058] The combustion simulation module is used to obtain natural gas fuel characteristic data, input the fuel characteristic data into the three-dimensional initial model to simulate the combustion process, and perform multi-dimensional evaluation of the simulated combustion process to generate the combustion process evaluation results;

[0059] The model optimization module is used to optimize the 3D initial model based on the combustion process evaluation results. If the combustion process evaluation results do not meet the preset combustion efficiency threshold, the nozzle structure, fuel mixing parameters and combustion chamber geometric characteristics are coordinated to generate a 3D optimized model;

[0060] The parameter calibration module is used to integrate the 3D optimization model into the combustion control system for actual combustion testing. The module monitors the flame morphology and temperature field distribution through a high-temperature thermal imager to obtain combustion feedback data. The module dynamically calibrates the parameters of the 3D optimization model based on the combustion feedback data to generate a high-precision 3D simulation model of the natural gas burner.

[0061] The beneficial effect of the present invention lies in that the initial modeling module accurately constructs a three-dimensional initial model of a natural gas burner by collecting combustion chamber geometric and operating parameters and combining them with periodic microgroove array data generated by laser microtexturing. This process provides a highly accurate geometric foundation for subsequent combustion simulation and model optimization, ensuring the reliability of combustion process simulation. The combustion simulation module simulates the combustion process and performs multi-dimensional evaluation by inputting natural gas fuel characteristic data into the three-dimensional initial model, comprehensively analyzing key indicators such as combustion efficiency, pollutant emissions, and combustion stability. This module can quickly identify combustion performance issues and provide data-driven solutions. Based on the combustion process evaluation results, the model optimization module automatically identifies the reasons for substandard combustion efficiency and performs targeted coordinated optimization adjustments to the nozzle structure, fuel mixing parameters, and combustion chamber geometry. This automated optimization strategy effectively improves combustion efficiency, reduces emissions, lowers energy loss, and enhances the overall system's operational stability. The parameter calibration module combines the three-dimensional optimization model with the combustion control system to conduct actual combustion tests and monitor flame morphology and temperature field distribution in real time. By using the combustion feedback data obtained by the high-precision thermal imager, the system can dynamically calibrate the parameters of the three-dimensional optimization model, thereby realizing a high-precision simulation model. This calibration process can adjust the performance of the equipment in real time in actual applications to ensure the optimal operating state of the burner. The entire system process combines real-time feedback data with intelligent optimization strategies, which greatly shortens the development cycle of natural gas burners, and each round of optimization can provide targeted performance improvements. The results of each optimization and calibration can provide data support for subsequent iterative updates, promoting the continuous improvement of equipment performance. Therefore, the present invention solves the problems of low efficiency, difficulty in optimization and lack of real-time feedback in traditional designs through three-dimensional modeling, combustion simulation and dynamic optimization adjustment, and significantly improves the design accuracy and combustion performance of natural gas burners. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic flow chart of the steps of an integrated design method for a three-dimensional simulation model of a natural gas burner;

[0063] Figure 2 for Figure 1 Detailed implementation steps of step S1 in FIG.

[0064] Figure 3 for Figure 1 Detailed implementation steps of step S2 in FIG.

[0065] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0066] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. It is obvious that the embodiments described are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts are within the scope of protection of the present invention.

[0067] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0068] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0069] To achieve this, please refer to Figures 1 to 3 , an integrated design method for a three-dimensional simulation model of a natural gas burner, the method comprising the following steps:

[0070] Step S1: Collecting geometric parameters and operating parameters of the natural gas burner to obtain initial device parameter information; performing laser microtexturing on the combustion chamber inner surface of the natural gas burner to generate periodic microgroove array data; and constructing a three-dimensional initial model of the natural gas burner using three-dimensional modeling software based on the initial device parameter information and the periodic microgroove array data.

[0071] Step S2: Obtaining natural gas fuel characteristic data, inputting the fuel characteristic data into a three-dimensional initial model to simulate the combustion process, and performing a multi-dimensional evaluation of the simulated combustion process to generate a combustion process evaluation result;

[0072] Step S3: Optimizing the three-dimensional initial model based on the combustion process evaluation results. If the combustion process evaluation results do not reach a preset combustion efficiency threshold, the nozzle structure, fuel mixing parameters, and combustion chamber geometric characteristics are collaboratively adjusted to generate a three-dimensional optimized model.

[0073] Step S4: Integrate the three-dimensional optimization model into the combustion control system to conduct actual combustion tests, monitor the flame morphology and temperature field distribution through a high-temperature thermal imager, and obtain combustion feedback data; dynamically calibrate the parameters of the three-dimensional optimization model based on the combustion feedback data to generate a high-precision three-dimensional simulation model of the natural gas burner.

[0074] This invention collects equipment geometry and operating parameters and, in conjunction with fuel characteristics, performs multidimensional combustion process simulation and dynamic optimization. This allows for coordinated control of nozzle structure, fuel mixture ratio, and combustion chamber morphology, significantly improving combustion efficiency and reducing energy waste. Actual combustion feedback data is used to dynamically calibrate the three-dimensional optimization model, creating a highly reliable and adaptable three-dimensional simulation model, providing a reliable basis for subsequent design improvements and control system optimization. Laser microtexturing creates a periodic microgroove array, which enhances heat conduction and airflow disturbance, improving combustion stability and flame morphology, and further enhancing thermal energy utilization. The simulation model is integrated with the combustion control system, and the design process is optimized through high-temperature thermal imaging feedback. This creates an intelligent closed-loop design-simulation-testing-feedback system, driving the development of digital and intelligent combustion systems. Precisely controlling combustion parameters ensures complete fuel combustion and reduces the generation of incomplete combustion products (such as CO and NOx), helping to reduce industrial emissions and enhance environmental performance. Three-dimensional modeling and simulation analysis replace traditional trial-and-error experiments, effectively shortening design iteration cycles, reducing R&D testing costs, and improving engineering development efficiency. Therefore, the present invention solves the problems of low efficiency, difficulty in optimization and lack of real-time feedback in traditional designs through three-dimensional modeling, combustion simulation and dynamic optimization adjustment, and significantly improves the design accuracy and combustion performance of natural gas burners.

[0075] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a flow chart of the steps of an integrated design method for a three-dimensional simulation model of a natural gas burner according to the present invention. In this example, the integrated design method for a three-dimensional simulation model of a natural gas burner includes the following steps:

[0076] Step S1: Collecting geometric parameters and operating parameters of the natural gas burner to obtain initial device parameter information; performing laser microtexturing on the combustion chamber inner surface of the natural gas burner to generate periodic microgroove array data; and constructing a three-dimensional initial model of the natural gas burner using three-dimensional modeling software based on the initial device parameter information and the periodic microgroove array data.

[0077] Step S2: Obtaining natural gas fuel characteristic data, inputting the fuel characteristic data into a three-dimensional initial model to simulate the combustion process, and performing a multi-dimensional evaluation of the simulated combustion process to generate a combustion process evaluation result;

[0078] Step S3: Optimizing the three-dimensional initial model based on the combustion process evaluation results. If the combustion process evaluation results do not reach a preset combustion efficiency threshold, the nozzle structure, fuel mixing parameters, and combustion chamber geometric characteristics are collaboratively adjusted to generate a three-dimensional optimized model.

[0079] Step S4: Integrate the three-dimensional optimization model into the combustion control system to conduct actual combustion tests, monitor the flame morphology and temperature field distribution through a high-temperature thermal imager, and obtain combustion feedback data; dynamically calibrate the parameters of the three-dimensional optimization model based on the combustion feedback data to generate a high-precision three-dimensional simulation model of the natural gas burner.

[0080] In one embodiment of the present invention, a 3D laser scanner is used to perform high-precision scanning of the natural gas burner's geometry, acquiring geometric parameters of various burner components, including nozzle dimensions, combustion chamber shape, and surface structure. Simultaneously, on-site sensors (such as flowmeters, temperature sensors, and pressure sensors) collect operating parameters of the natural gas burner, such as natural gas flow rate, inlet pressure, and intake temperature, to construct initial device parameter information. Subsequently, laser microtexturing technology is used to treat the combustion chamber surface, generating data for a periodic microgroove array using a laser scanning system. This surface treatment can influence airflow and combustion characteristics, thereby improving combustion efficiency. The device parameters and microgroove data are imported into 3D modeling software (such as SolidWorks or ANSYS DesignModeler), and an initial 3D model of the natural gas burner is generated based on the existing data. Natural gas fuel property data, including calorific value, density, viscosity, and chemical composition, is collected. This data is then imported into combustion simulation software (such as ANSYS Fluent or COMSOL Multiphysics) to simulate the combustion process. The simulation includes flame propagation, temperature distribution, pollutant generation, and combustion efficiency. During the simulation, the input fuel characteristic data is combined with the initial 3D model to calculate multiple metrics, including flame propagation path, airflow distribution, temperature gradient, and flue gas emissions. A multi-dimensional evaluation generates simulation results for the combustion process, analyzing and confirming performance data such as combustion efficiency, flame stability, pollutant emissions, and temperature distribution. Based on the combustion process evaluation results generated in step S2, if the combustion efficiency does not meet the preset combustion efficiency threshold (e.g., below 95%), the burner structure needs to be optimized. Specific optimization measures include: adjusting the nozzle diameter, aperture, number of holes, and injection angle based on the combustion simulation results to improve the mixing of gas and air and ensure more complete combustion. By adjusting the fuel-air ratio, the mixing process is optimized to ensure an optimal oxygen concentration within the combustion chamber. Fine-tuning the combustion chamber geometry, such as adjusting the curvature of the combustion chamber walls or adding airflow guides, is performed to optimize airflow distribution and flame stability. Multiple simulations are compared with experimental data to ultimately generate a 3D optimized model to improve combustion efficiency and equipment stability. The resulting 3D optimized model is then integrated into the combustion control system for actual combustion testing. A high-temperature thermal imager monitors flame morphology and temperature distribution, collecting real-time combustion feedback data. This feedback includes flame stability, changes in flame morphology, and temperature distribution. During testing, the control system adjusts parameters such as fuel flow, intake air temperature, and pressure to ensure optimal combustion performance. Based on this combustion feedback data, the 3D optimization model is dynamically calibrated, adjusting model parameters such as nozzle structure and fuel mixture ratio to ensure the most accurate simulation model.After repeated debugging and calibration, a high-precision three-dimensional simulation model of the natural gas burner was finally generated, which can reflect the changes in the combustion process in real time and provide an accurate basis for subsequent optimization and monitoring.

[0081] As an example of the present invention, refer to Figure 2 As shown, in this example, step S1 includes:

[0082] Step S11: using a multi-source sensor to collect geometric parameters and operating parameters of the natural gas burner to obtain initial equipment parameter information;

[0083] Step S12: extracting the internal surface temperature distribution data of the combustion chamber of the natural gas burner based on the initial equipment parameter information, and performing airflow scouring path analysis on the natural gas burner based on the internal surface temperature distribution data of the combustion chamber, generating high heat load areas and main heat transfer path areas, and uniformly marking them as laser microtexturing priority processing area data;

[0084] Step S13: performing laser microtexturing on the inner surface of the combustion chamber of the natural gas burner based on the laser microtexturing priority processing area data using femtosecond laser pulses to generate periodic microgroove array structure data;

[0085] Step S14: Based on the initial device parameter information set and the periodic micro-groove array structural parameter data, a three-dimensional initial structural model of the natural gas burner is constructed in a three-dimensional modeling software, wherein the construction process includes:

[0086] Establish the geometric entities of the natural gas burner shell and combustion channel;

[0087] Mapping the periodic micro-groove array to the corresponding area of ​​the combustion chamber wall;

[0088] Add operating condition mark points.

[0089] This invention uses multi-source sensors to simultaneously acquire geometric and operating parameters (such as pressure, flow rate, and temperature) of a natural gas burner, ensuring comprehensive and accurate initial device parameter information and providing a highly reliable raw data foundation for subsequent modeling, analysis, and optimization. By analyzing the combustion chamber's internal surface temperature distribution and tracing the airflow path, high heat load areas and key heat transfer and exchange paths are precisely identified as priority areas for laser microtexturing, effectively improving the functional focus and thermal management efficiency of the microstructure design. A periodic microgroove array structure is applied within these selected areas to enhance the combustion chamber's ability to control airflow disturbances, improve heat conduction and fuel mixing uniformity, and thus improve combustion stability and flame structure quality. During the 3D modeling phase, not only is the outer shell and combustion channel geometry reconstructed, but the periodic microgroove structure is accurately mapped, and operating condition markers are added. This ensures that the model more realistically reflects the physical structure and dynamic response, providing a highly consistent data model for subsequent combustion process simulation and optimization. From multi-source sensing, data-driven identification, laser precision machining, to 3D structural modeling, a complete front-end digital twin chain is formed, supporting refined device design, performance analysis, and manufacturing tracking. Accurate microstructure modeling and thermodynamic feature mapping provide realistic boundaries and initial conditions for combustion process simulation, significantly enhancing the credibility and guiding value of subsequent combustion evaluation and optimization results.

[0090] In this embodiment of the present invention, sensors suitable for collecting geometric parameters (such as size and shape) and operating parameters (such as temperature, pressure, and flow) are selected. For example, a laser scanner is used to acquire geometric data, and a temperature sensor (such as an infrared sensor or thermocouple) is used to acquire combustion chamber temperature data. Sensors are installed at key locations on the natural gas burner, such as the combustion chamber walls, nozzle, and combustion channel, to ensure real-time data acquisition. A data acquisition system records various parameters in real time and stores the data on a computer or cloud platform, providing initial equipment parameters for subsequent analysis. Using the collected combustion chamber surface temperature data, computational fluid dynamics (CFD) software is used to perform numerical simulations to determine the temperature distribution throughout the combustion chamber. The simulation calculates the temperature field using physical models of heat conduction, convection, and radiation. Based on this temperature distribution data, CFD is used to analyze the airflow within the combustion chamber, identify the paths where the airflow contacts the walls, and identify the primary airflow scour paths. Based on this temperature distribution data, areas with high heat loads are identified, which are often associated with combustion efficiency and require special attention. Combining airflow path analysis with the identification of high-heat-load areas, these areas are marked as priority areas for laser microtexturing. These areas are key optimization targets and provide a basis for laser processing. Select equipment suitable for femtosecond laser pulse processing. Femtosecond laser pulses offer high peak power and short pulse duration, making them suitable for precision processing. Based on the priority areas identified in step S12, use CAD or CAM software to develop laser processing paths. These paths should cover the high-heat-load areas on the combustion chamber inner wall and form a periodic microgroove structure. Focus the femtosecond laser pulses on the combustion chamber surface, and precisely control the laser pulse frequency and energy to engrave the microgroove array. Ensure that the periodicity, depth, and spacing of each microgroove meet the design requirements. Monitor the laser processing process in real time to ensure good contact between the laser pulse and the combustion chamber surface, and adjust processing parameters such as laser power and scanning speed as needed. Import the initial equipment parameter data and the periodic microgroove array structure data into 3D modeling software (such as SolidWorks, AutoCAD, or ANSYS Design Modeler) as the basis for modeling. Based on the initial device parameter data, the geometric entities of the natural gas burner housing and combustion channel are first created in the modeling software, ensuring that the size and shape match the actual device. The microgroove array structure formed by femtosecond laser processing is mapped to the corresponding areas on the inner wall of the combustion chamber, which should match the priority areas of laser microtexturing. Different operating conditions (such as temperature, pressure, flow rate, etc.) are marked in the 3D model. These points will be used for subsequent simulation analysis or parameter monitoring during actual operation. The initial 3D structural model is optimized to ensure its stability and efficiency in actual operation. Virtual simulation is performed to verify that the airflow, temperature distribution, and heat load in the combustion chamber meet expectations.

[0091] Preferably, performing airflow flushing path analysis on the natural gas burner according to the combustion chamber inner surface temperature distribution data in step S12 includes:

[0092] The thermal field is reconstructed based on the temperature distribution data of the combustion chamber surface to obtain the absolute temperature value and spatial thermal gradient change of each surface node, and a spatial thermal gradient matrix is ​​generated, in which each matrix element contains a three-dimensional coordinate and a corresponding temperature derivative value;

[0093] Based on the spatial thermal gradient matrix, the thermal gradient distribution partitioning and classification of the combustion chamber surface temperature distribution data is performed to generate the thermal partitioning data of the combustion chamber and the inner and outer surfaces;

[0094] A high-heat threshold condition is set and used to perform regional cluster analysis on the thermal partition data of the internal and external surfaces of the combustion chamber. The cluster centers and their associated nodes are extracted to identify high-heat load areas where heat flux is concentrated.

[0095] Perform flow field simulation in high heat load areas to extract the streamline path and velocity vector distribution of the gas in the combustion chamber;

[0096] The scour intensity coefficient of each wall area is calculated based on the streamline path and velocity vector distribution to obtain the airflow scour path intensity map; the scour significant area of ​​the airflow scour path intensity map is screened by the set gas scour threshold to obtain the gas scour significant area;

[0097] The high heat load area and the significant gas scouring area are spatially matched to obtain the main heat transfer path area, and the high heat load area and the main heat transfer path area are subjected to regional intersection operation, and the areas corresponding to the operation results are uniformly marked as laser microtexturing priority processing area data.

[0098] This method reconstructs the thermal field of the combustion chamber's internal surface temperature distribution data to construct a spatial thermal gradient matrix containing three-dimensional coordinates and temperature derivatives. This accurately captures the spatial variation of heat, providing high-resolution input for identifying high-heat-load areas and avoiding the coarse-grained misjudgment of traditional average temperature-based methods. Combining thermal gradient zoning and classification with cluster analysis based on high-heat thresholds effectively focuses on areas of concentrated heat flux. Simultaneously, flow field simulation technology is introduced to extract gas flow paths and velocity vectors, and calculate wall scour intensity to form a gas scour intensity map, enabling a more physically based assessment of areas affected by the "heat + flow" coupling. A set scour intensity threshold is used to filter the gas scour path intensity map, eliminating reliance on manual experience and enabling quantitative identification of high-scour intensity regions, providing clear target areas for subsequent structural processing. By spatially matching high-heat-load areas with areas of significant scour and calculating their intersection, the primary heat transfer and heat exchange paths are precisely delineated, ensuring that the laser microtexturing priority treatment areas are truly concentrated in the most critical locations for heat transfer enhancement, thereby improving microtexturing efficiency and resource utilization. The entire process is based on data matrices, thermal flow models, and flow field simulation calculations, independent of prior design experience. This system constructs an intelligent analysis framework that can adaptively identify key areas, providing more robust support for microtexture design under complex structures or operating conditions. Accurately identifying and texturing significant areas of the heat transfer path helps improve heat exchange efficiency and surface disturbance capabilities, promoting uniform mixing of gas and air and ensuring complete combustion, thereby achieving the combined effects of improving combustion efficiency, reducing energy consumption, and minimizing heat loss.

[0099] In embodiments of the present invention, temperature data acquired from sensors should be processed and converted into a format suitable for thermal field reconstruction. For example, two-dimensional or three-dimensional temperature distribution data can be imported into CFD (computational fluid dynamics) software or dedicated thermal analysis tools (such as COMSOL Multiphysics or ANSYS Fluent). A thermal field reconstruction algorithm (such as one based on finite element analysis or interpolation) is used to calculate the absolute temperature value of each surface node. Common algorithms include Kriging or inverse problem methods, which can efficiently generate temperature distributions for complex surfaces. The temperature gradient is calculated based on the temperature value of each node and the temperature changes of its neighboring nodes, forming a temperature derivative matrix. Each element of the spatial thermal gradient matrix contains a corresponding three-dimensional coordinate and a temperature derivative value. Based on the range of the thermal gradient variation, specific classification criteria can be set, such as classifying the temperature derivative into several levels (e.g., high temperature, medium temperature, and low temperature regions). Using partitioning criteria, the spatial thermal gradient matrix is ​​classified to divide the internal and external surfaces of the combustion chamber into different thermal zones. For each region, its boundaries are calculated and the corresponding region type is labeled. This generates thermal zoning data, typically output as a 2D or 3D dataset containing the spatial location and temperature gradient characteristics of each region. Based on the equipment's operating requirements, a high-heat threshold is set, indicating that regions exceeding this threshold are high-heat-load regions. For example, a temperature gradient exceeding a specific value or an absolute temperature exceeding a critical value can be used as the criterion for high-heat regions. Clustering algorithms (such as K-means and DBSCAN) are used to analyze the thermal zoning data, extracting cluster centers and their associated nodes to identify areas of concentrated heat flux, which are typically high-heat-load regions. Cluster analysis helps identify areas of high heat density and strong heat transfer. The flow field within the combustion chamber is simulated using CFD simulation software (such as ANSYS Fluent and COMSOL Multiphysics). Initial combustion gas conditions (temperature, pressure, flow velocity, etc.) are input, and the software calculates the flow path, velocity distribution, and vortex flow within the combustion chamber. Velocity vector diagrams are extracted from the flow field simulation results, showing the direction and velocity of the airflow. This velocity data is used in subsequent scour intensity calculations. The velocity vector data extracted from the flow field simulation can be used to calculate the scour intensity coefficient of the airflow on the wall. The commonly used calculation method is to calculate the scour intensity coefficient based on the flow velocity and the kinetic energy of the gas particles. The formula is as follows: ;in is the scour intensity coefficient, is the flow rate, is the gas density, is the gas particle diameter, is the impact angle. Based on the scour intensity coefficient for each region, a scour path intensity map is generated. This map can be presented as a heat map or color-coded to show which areas are most affected by airflow scour. A gas scour threshold is set, and areas exceeding this value are considered to be areas with significant airflow scour. These areas are typically areas with high airflow velocity and high scour intensity. Based on the set scour threshold, the airflow scour path intensity map is filtered to extract areas with significant scour. High heat load areas and areas with significant gas scour are matched in three-dimensional space to find their intersection areas. These intersection areas are areas with both high heat load and strong airflow scour, indicating that these areas are most in need of optimization. Using geometric analysis tools (such as CAD software or custom algorithms), an intersection operation is performed on the high heat load areas and areas with significant airflow scour to generate the final data for the priority areas for laser microtexturing. These areas will be the priority targets for laser microtexturing treatment.

[0100] Preferably, performing flow field simulation on the high heat load area includes:

[0101] The combustion chamber geometry model size range is set to 200–500 mm × 200–500 mm × 200–600 mm, the combustion chamber diameter range is 80–150 mm, the length is 200–400 mm, the gas inlet velocity is set between 10–50 m / s, the inlet temperature range is 300–600 K, and the inlet pressure is set to 1.01×10 5 Pa;

[0102] The wall temperature of the high heat load area was set in the range of 900–1500 K, and the outlet pressure was set to 1.01×10 5 Pa, combustion model selects non-premixed combustion model or PDF model.

[0103] By setting the combustion chamber geometry range of 200–500mm×200–500mm×200–600mm, and combining the combustion chamber diameter of 80–150mm and the length of 200–400mm, the simulation model can be highly consistent with the structural dimensions of various industrial-grade natural gas burners, ensuring that the simulation results have broad engineering adaptability and practical guiding significance. The gas inlet flow rate is set in the range of 10–50m / s, the temperature is set to 300–600K, and the pressure is atmospheric pressure (about 1.01×10 5Pa), matching the physical properties of the gas under real operating conditions, making the turbulence development, velocity distribution and boundary layer behavior of the gas in the cavity more realistic, providing accurate basic data for subsequent flushing path and heat flux distribution analysis. Setting the wall temperature of the high heat load area in the thermal boundary condition range of 900–1500K can accurately simulate the influence of high-temperature heat transfer on local flow behavior and thermal boundary layer formation, and enhance the model's ability to identify and predict actual heat transfer hotspots. Using a non-premixed combustion model or a PDF (Probability Density Function) combustion model, the simulation process can accurately describe the combustion reaction process and heat release behavior of the gas in a non-uniform mixed state, which is particularly suitable for multi-condition, multi-region, and multi-scale unsteady combustion scenario analysis. Set the outlet pressure to normal pressure (1.01×10 5 Keeping the inlet pressure (Pa) consistent with the boundary conditions and physical continuity of the overall simulation model ensures the closedness and physical continuity of the overall simulation model, which helps improve the convergence speed and stability of the calculation and reduce simulation errors. Accurately simulating information such as airflow velocity vectors, pressure distribution, and temperature field evolution provides a quantitative basis for the precise identification of scouring paths and thermal gradient enhancement paths, further enhancing the scientific nature of laser microtexturing area delineation and processing efficiency.

[0104] In this embodiment of the present invention, a three-dimensional geometric model of the combustion chamber is created in CFD software (such as ANSYS Fluent or COMSOL Multiphysics). The length, width, and height ratios of the combustion chamber are set within a specified dimension range (200–500 mm × 200–500 mm × 200–600 mm), ensuring that the model can accommodate the required flow and heat transfer characteristics. The length range is 200–400 mm, and the width and height are 200–500 mm (specific values ​​depend on the actual design). The combustion chamber inner diameter is set between 80–150 mm. A typical diameter value is set based on the actual combustion chamber design, ensuring that it meets the gas flow requirements in actual projects. The geometric model is created using a CAD modeling tool (such as SolidWorks or AutoCAD) or directly within the CFD software to ensure geometric accuracy. The combustion chamber geometric model includes the walls, inlet, and outlet regions, with appropriate flow zones set. The inlet boundary conditions are configured based on the specified gas flow rate and temperature ranges, with the flow rate set within a range of 10–50 m / s. The inlet velocity can be set to a fixed value or to a velocity profile (e.g., laminar or turbulent velocity profile) based on the simulation requirements. The inlet temperature should be set between 300–600 K. Different combustion conditions can be simulated by setting the inlet temperature. The inlet pressure is generally set to atmospheric pressure, approximately 1.01×10 5 Pa. For gas flow in a normal environment, it is sufficient to keep the inlet pressure at normal pressure. Set the outlet pressure to normal pressure, also 1.01×105 Pa. For high heat load areas, the wall temperature is set between 900–1500 K. This range generally represents the temperature conditions in high heat load areas. The wall temperature has a significant impact on heat flow calculations and the airflow flushing path. The non-premixed combustion model applies to combustion scenarios where gas and oxygen mix within the combustion chamber. When using the non-premixed combustion model in CFD, the fuel and oxygen mixture ratio of the gas must be set to simulate the mixing and combustion process after the airflow enters the combustion chamber. The PDF (Probability Density Function) model is used to more accurately simulate the coupling between turbulence and combustion. The PDF model simulates the mixing and reaction processes between different gas molecules in turbulent flow and is suitable for complex combustion systems. This model requires input of the chemical reaction mechanism and relevant physical properties of the gas. An appropriate turbulence model is selected to describe the turbulent characteristics of the airflow. Common turbulence models include the k−ϵ model and the k−ω model. Based on actual needs, a model suitable for describing the turbulent characteristics within the combustion chamber can be selected. In CFD simulations, ensure that the physical properties of the input gas (such as density, viscosity, and specific heat capacity) affect flow and heat transfer characteristics, especially the gas state at different temperatures. Establish a combustion kinetics model to determine the reaction rate and the chemical mechanism of the combustion process. If using a PDF model, select an appropriate chemical reaction mechanism (such as the Lagrangian PDF model). Select an appropriate solver to ensure that the simulation captures the dynamics of the airflow, temperature distribution, and combustion process. Generally, steady-state or transient solvers are chosen, depending on the simulation objectives. Through CFD simulations, the airflow path, velocity distribution, temperature distribution, and turbulence characteristics within the combustion chamber are determined. Flow and temperature fields are displayed using vector diagrams, streamline plots, and isothermal plots to analyze airflow characteristics in areas with high heat loads. Analyze the wall temperature distribution to identify areas with high heat loads and determine whether these areas require special attention. Comparing temperature data with flow field data verifies that the temperature distribution meets design requirements and evaluates the impact of flow on wall heat transfer. Based on the flow field results, further calculations of airflow scour intensity are performed to identify areas with high scour intensity and assess their impact on the equipment.

[0105] As an example of the present invention, refer to Figure 3 As shown, in this example, step S2 includes:

[0106] Step S21: Acquire natural gas fuel characteristic data;

[0107] Step S22: Inputting the fuel characteristic data into the three-dimensional initial model to construct the combustion process simulation boundary conditions, wherein the boundary conditions include inlet conditions, wall conditions, turbulence model and combustion model;

[0108] Step S23: performing a natural gas combustion process numerical simulation on the fuel characteristic data based on the combustion process simulation boundary conditions to generate a combustion process simulation data set, wherein the natural gas combustion process numerical simulation includes the ignition, heat transfer, diffusion, and emission processes of natural gas in a three-dimensional space;

[0109] Step S24: Perform multi-dimensional quantitative analysis on the combustion process simulation data set to generate a combustion process evaluation result.

[0110] The present invention obtains the fuel characteristic data of natural gas (such as composition, specific heat capacity, combustion heat, diffusion coefficient, etc.) to provide a real and effective thermophysical property basis for the simulation process, so that the simulation model has good physical consistency and engineering reference when describing the combustion behavior of natural gas. The fuel characteristic data is input into the three-dimensional initial model to construct boundary conditions including inlet flow velocity temperature, wall heat flux, turbulence model (such as k-ε model or LES model) and combustion model (such as non-premixed model, EDC model, etc.), effectively simulating the complex coupling conditions of the real combustion chamber and significantly improving the prediction accuracy of combustion behavior. The numerical simulation of natural gas combustion covers the entire process from initial ignition to heat release, material diffusion and product emission. It can systematically reproduce the heat-fluid-mass multi-field coupling evolution law in the combustion reaction chain, and support the key hot zone, oxygen dissipation zone, NO x Accurately track core mechanisms such as the generation zone. Multidimensional quantitative analysis based on simulated data sets (including temperature fields, velocity fields, combustion efficiency, heat release rate, pollutant concentration, and other physical quantities) comprehensively evaluates combustion efficiency, heat utilization, and environmental impact, outputting targeted assessment results and providing reliable judgment basis for subsequent optimization models. Multidimensional simulation analysis can reveal the coupling relationship between natural gas burner structure and combustion performance, providing engineers with parameter sensitivity analysis results and performance bottleneck identification tools, thereby providing quantitative optimization direction for design solutions such as nozzle shape, mixing strategy, and heat exchange structure.

[0111] In an embodiment of the present invention, fuel property data of natural gas is obtained, including the fuel's calorific value, density, specific heat capacity, viscosity, chemical composition (such as methane content, carbon dioxide, nitrogen, oxygen, etc.), and thermodynamic data of the combustion reaction. These data can usually be obtained through experimental measurements or from the fuel supplier's technical manual. The obtained fuel data is organized into a format suitable for input into the simulation software. Common formats are CSV, Excel, or JSON files, ensuring that all necessary thermophysical property data, chemical composition, and reaction kinetic parameters are included. Based on the geometric dimensions of the combustion chamber (as set in step S11), an initial model of the combustion chamber is constructed using 3D modeling software (such as ANSYS, COMSOL, SolidWorks, etc.), and the model is imported into a CFD simulation environment (such as ANSYS Fluent, OpenFOAM, etc.). The physical and chemical properties of the fuel are set in the simulation software to ensure that the input natural gas composition and thermophysical property data accurately reflect the actual fuel characteristics. Configure the fuel composition, such as the ratio of methane (CH4), ethane (C2H6), propane (C3H8), etc., and select an appropriate combustion reaction mechanism based on the combustion characteristics of these components (for example, using a detailed chemical reaction mechanism model). Set the initial conditions such as the gas flow rate, temperature, and pressure. For example, set the inlet temperature to 300–600K, the inlet flow rate to 10–50 m / s, and the atmospheric pressure (1.01×10 5Pa). Set wall heat flux boundary conditions. The wall temperature is generally set to the temperature of the high heat load area (900–1500K). Select an appropriate turbulence model based on the flow characteristics, such as the k−ϵ model or the k−ω model. The selected model should accurately capture the turbulent characteristics within the combustion chamber. Choose a model suitable for natural gas combustion, such as the non-premixed combustion model (suitable for combustion after the fuel and oxygen are mixed) or the PDF model (suitable for complex turbulent combustion). Both models can simulate gas diffusion, ignition, and flame propagation during the combustion process. Simulate the initial ignition of natural gas and oxygen in the combustion chamber. By setting appropriate initial ignition conditions (such as ignition source location and ignition energy), simulate the ignition of natural gas in the combustion chamber. Based on the combustion model and flow field data, simulate heat transfer during the combustion process, including radiation, convection, and conduction. Heat is transferred to the combustion chamber walls through the flame and high-temperature gases generated by the combustion, and further transferred to the equipment surfaces. Simulate the diffusion behavior of the gas, especially how the fuel gas mixes and reacts with oxygen in the air in a turbulent environment. Simulate the generation and emission of post-combustion emissions, such as carbon dioxide, nitrogen oxides (NOx), and carbon monoxide (CO). The simulation should consider combustion efficiency and the reactions and conversions of chemical species during combustion. Select an appropriate time step and computational accuracy to perform steady-state or transient simulations. Use CFD software to solve multiple variables within the combustion chamber, including the flow field, temperature field, and chemical reaction field, and record the data. Use numerical solvers, such as the finite volume method (FVM) in fluid dynamics, to solve the governing equations. Analyze the temperature distribution during combustion, particularly the ignition zone, flame propagation path, and temperature field within the combustion chamber walls. Based on the temperature distribution, areas of high heat load and low heat transfer efficiency can be identified, allowing for further optimization of the combustion process. Analyze the velocity distribution of the airflow, particularly the turbulent characteristics and airflow path within the combustion chamber. Streamline plots and vector diagrams display information such as airflow direction and velocity to assess whether the airflow distribution is uniform and whether undesirable flow structures (such as backflow and vortexes) exist during combustion. Emissions during combustion, including the concentration distribution of carbon dioxide, nitrogen oxides, and carbon monoxide, should be evaluated. Based on emission data, further analysis is conducted to determine how well combustion efficiency meets environmental requirements. Simulation data is used to calculate combustion efficiency and assess heat utilization. Areas with high combustion efficiency typically have higher temperatures and better heat exchange capacity. Quantitative analysis of the reaction process within the combustion chamber assesses combustion stability and reaction rate. Combining airflow velocity and temperature changes within the combustion chamber, analysis is conducted to determine whether the combustion process is smooth and whether there are any factors causing oscillation or instability.

[0112] Preferably, if the combustion process evaluation result does not reach a preset combustion efficiency threshold in step S3, then collaboratively adjusting the nozzle structure, fuel mixing parameters, and combustion chamber geometric characteristics includes:

[0113] If the combustion process evaluation result does not reach the preset combustion efficiency threshold, regional combustion anomaly features are extracted from the three-dimensional initial model based on the combustion process evaluation result to obtain a collaborative adjustment target parameter set, where the collaborative adjustment target parameter set includes nozzle exit velocity and angle deviation, air-fuel ratio deviation, and geometric thermal hysteresis zone characteristics;

[0114] The nozzle structure in the three-dimensional initial model is optimized for the curvature of the nozzle internal channel according to the nozzle outlet velocity and angle deviation, and the nozzle structure adjustment data is generated;

[0115] Dynamically control the fuel mixing field of the fuel mixing parameters in the three-dimensional initial model through the air-fuel ratio deviation to generate fuel dynamic mixing field control data;

[0116] The geometric characteristics of the combustion chamber are used to adjust the ratio of the expansion section and the contraction section of the combustion chamber by using the geometric thermal hysteresis zone characteristics, and the local geometric reconstruction data of the combustion chamber is generated;

[0117] The nozzle structure adjustment data, fuel dynamic mixing field control data, and combustion chamber local geometry reconstruction data are coupled and integrated for simulation, and the three-dimensional initial model is optimized using the simulation results to obtain a three-dimensional optimized model.

[0118] The present invention extracts local abnormal features based on the combustion process evaluation results, can quickly identify the key areas that lead to reduced combustion efficiency and their associated physical parameters, establish a collaborative adjustment target parameter set with "nozzle structure-mixing parameters-geometry" as the core, and achieve a technological leap from "global blind adjustment" to "regional targeted regulation" in the optimization process. Through quantitative analysis of nozzle outlet velocity and angular deviation, parametric modeling and reconstruction of nozzle channel curvature are implemented to optimize internal streamline distribution, reduce flow field separation and turbulent dissipation phenomena, thereby improving fuel injection uniformity and ignition stability, and enhancing the front-end flame anchoring capability. According to the air-fuel ratio deviation, the ratio of fuel and combustion-supporting gas is adjusted and spatial mixing is optimized, effectively improving the temperature rise hysteresis, flame instability or sharp increase of pollutants caused by local rich or lean combustion, ensuring that the air-fuel ratio in the entire combustion space is close to the optimal working range, and improving the uniformity of heat release. In view of the characteristics of the geometric thermal hysteresis zone, by adjusting the ratio and transition relationship of the expansion section and the contraction section of the combustion chamber, the backflow disturbance path of the hot air flow can be optimized, the local dead zone and the accumulation of high-temperature residual flames can be weakened, the overall flow connectivity and heat transfer efficiency can be enhanced, and the flame can be stably propagated and burned efficiently. By integrating the nozzle structure adjustment data, fuel mixing control data and combustion chamber geometry reconstruction data, multi-physics field simulation coupling analysis can be carried out, and parameter linkage optimization can be completed within a unified platform, thereby improving the response efficiency of simulation decisions and engineering implementation. The three-dimensional optimization model after collaborative optimization has higher combustion efficiency, lower temperature gradient concentration and better fluid-heat coupling structure, which can provide a solid foundation for subsequent high-precision combustion control modeling and provide a more realistic simulation reference for engineering design.

[0119] In an embodiment of the present invention, the combustion process evaluation results are quantitatively analyzed, with particular attention paid to indicators such as combustion efficiency, temperature distribution, and emission concentration. These indicators are used to identify efficiency bottlenecks or abnormal areas in the combustion process, such as uneven flame propagation, excessively high emission concentrations, or unstable combustion zones. Based on the evaluation results, detailed analysis is performed on various areas within the combustion chamber to extract characteristics of combustion anomalies. For example, the following features can be extracted: identifying uneven nozzle outlet airflow velocity or inconsistent nozzle jet direction; analyzing deviations in the fuel-air mixture ratio to identify uneven air or fuel supply; and identifying thermal stagnation zones in the combustion chamber—areas where airflow and heat accumulation lead to localized temperature anomalies. These abnormal characteristics are integrated into a set of target parameters for coordinated adjustment. This parameter set includes nozzle outlet velocity and angle deviation, air-fuel ratio deviation, and geometric thermal stagnation zone characteristics, which serve as the basis for adjusting the three-dimensional model. Based on the nozzle outlet velocity and angle deviation data, the internal channel curvature of the nozzle is optimized. The geometry of the nozzle structure is adjusted, including the nozzle outlet angle, jet velocity distribution, and flow characteristics. The nozzle's taper, inner wall curvature, or nozzle orifice angle can be optimized to improve airflow uniformity and combustion efficiency. During the optimization process, nozzle structural adjustment data is generated, including nozzle channel geometry, curvature changes, and outlet angle adjustments. Based on air-fuel ratio deviation data, the fuel-air mixing field is regulated. Dynamic mixing field control technology is introduced to optimize the fuel-air mixing pattern. Parameters such as air and fuel inlet flow rates, pressures, and temperatures are adjusted to improve fuel-air mixing uniformity. Simulation calculations generate dynamic fuel mixing field control data, including mixer adjustment parameters and air and fuel flow distribution. Based on the characteristics of the geometric thermal hysteresis zone, the ratio of the combustion chamber's expansion and contraction sections is adjusted. By adjusting the combustion chamber's shape, the formation of thermal hysteresis zones is avoided and airflow stability is promoted. Flow guide devices, such as guide vanes or vortex generators, are added to the expansion section of the combustion chamber to help distribute heat and airflow more evenly. Adjustments to the combustion chamber's geometric structure generate local geometric reconstruction data, including adjustment parameters for the expansion and contraction sections and the position of the flow guide devices. The nozzle structure adjustment data, fuel dynamic mixing field control data and combustion chamber local geometry reconstruction data are integrated. These data are input into the three-dimensional simulation model, and coupled integrated simulation is performed to evaluate the effect of the optimized combustion process. The optimized three-dimensional model is subjected to multi-physics field coupled simulation such as flow, combustion, and heat transfer using CFD software. During the simulation process, key indicators such as combustion efficiency, temperature distribution, and emissions can be analyzed again. Based on the integrated simulation results, the three-dimensional initial model is optimized and adjusted. If the simulation results show that the combustion efficiency meets the standards and the emissions and temperature distribution meet the requirements, the optimized three-dimensional model is finally obtained. After the optimization is completed, a three-dimensional optimization model based on coordinated adjustment is obtained. This model can be used in actual production for more efficient and environmentally friendly natural gas combustion.

[0120] Of particular importance is the use of geometric thermal hysteresis characteristics to adjust the ratio of the expansion and contraction sections of the combustion chamber's geometric characteristics, which also includes:

[0121] Perform a joint geometry-flow analysis on the characteristic data of the geometric thermal hysteresis zone to identify the expansion and contraction sections where ignition lag occurs in the corresponding combustion chamber structure sections, and generate data on the key structural sections of the combustion chamber;

[0122] Perform local proportional inversion processing on the data of key structural sections of the combustion chamber. Based on the local thermal hysteresis intensity, flame propagation speed and pressure drop distribution, optimize the length and area ratio of the expansion section and the contraction section to generate proportional optimization adjustment parameter data;

[0123] Perform local topology correction on the original combustion chamber geometric model data, apply proportional optimization to adjust parameter data to achieve geometric deformation reconstruction of the expansion and contraction sections, and generate local geometric reconstruction data of the combustion chamber;

[0124] CFD thermal-fluid dual-field coupling simulation is performed on the local geometric reconstruction data of the combustion chamber to analyze the flame propagation path, pressure fluctuation and thermal hysteresis behavior of the modified structure, and generate local geometric optimization verification data.

[0125] In an embodiment of the present invention, by inputting the characteristic data of the geometric thermal hysteresis zone, including the temperature accumulation area, the local velocity reduction area, the vortex residual point, the fuel accumulation area, etc. during the combustion process. The characteristics of the thermal hysteresis zone are mapped to the three-dimensional combustion chamber geometric model; the flow field (velocity vector field) and the temperature field are combined to cluster and locate the boundaries of the ignition delay areas in the expansion section and the contraction section; it is determined whether the ignition delay point in the structure falls on the expansion section (flame delay) or the contraction section (backflow stagnation), and the key structural section data of the combustion chamber is generated, and the position of the expansion / contraction section that needs structural adjustment and its local properties are calibrated. A local proportional inversion function group is established to calculate the thermal hysteresis intensity. , flame propagation speed , pressure drop As the function input, derive the response surface model of the effect of structure on combustion behavior; optimize the expansion section length , contraction section length , cross-sectional area The ratio makes the flame propagation smooth, the pressure drop is reduced, and the thermal hysteresis zone is weakened. Preferably, the multi-objective optimization can be performed based on the following formula: ;in To optimize the target ratio, 、 as well as For the corresponding variable feature weights, proportional optimization adjustment parameter data is generated, including the target dimensions and adjustment directions for each structural segment. Local topological mapping is performed on the original model to identify the control nodes and mesh elements of the expansion and contraction segments. The control node coordinates are geometrically deformed (stretching and curvature adjustment) based on the optimization parameters. The new expansion and contraction segments are reconstructed, maintaining channel continuity and transition smoothness. Local geometric reconstruction data of the combustion chamber is generated, reflecting the new structural model after the geometric adjustment. Dual-physics simulation is performed on the reconstructed structure using a CFD platform (such as Ansys Fluent or OpenFOAM). Boundary conditions (nozzle injection velocity, fuel properties, turbulence model, and wall heat transfer) are set. A combustion model (such as EDM, PDF, or G-equation) is applied to simulate flame propagation. The thermal field (temperature distribution and heat flux) and flow field (velocity, pressure, and vorticity) are jointly calculated. Key performance indicators (KPIs) are extracted, including the continuity of the flame propagation path, the shift of the primary combustion zone, the stability of pressure fluctuations, and the elimination of thermal hysteresis regions. This generates local geometry optimization verification data for feedback verification of the structural adjustment results.

[0126] Preferably, coupling and integrating the nozzle structure adjustment data, the fuel dynamic mixing field control data, and the combustion chamber local geometry reconstruction data is simulated, and optimizing the three-dimensional initial model through the simulation results includes:

[0127] Perform multi-scale parameter extraction on the nozzle structure adjustment data to generate injection boundary constraint data;

[0128] Conduct time-series segmented modeling of fuel dynamic mixing field control data to generate time-segmented turbulence distribution field data;

[0129] Perform topological slicing and local feature mapping on the local geometric reconstruction data of the combustion chamber to generate structural analysis domain data;

[0130] The injection boundary constraint data, time segmented turbulence distribution field data, and structure analysis domain data are uniformly projected into a master coordinate system for spatial alignment, unit normalization, and scale adjustment to form unified simulation domain coordinate data;

[0131] Based on the cross-domain coupling boundary, multi-field variable coupling integration simulation mapping is performed on the unified simulation domain coordinate data to construct the coupled integrated simulation results;

[0132] The initial 3D model is optimized by coupling the integrated simulation results.

[0133] The present invention performs multi-scale extraction, time series modeling and feature mapping on the nozzle structure, fuel mixing and combustion chamber geometry reconstruction data respectively, and constructs unified simulation domain coordinate data, which can achieve collaborative coupling across physical quantities and time and space dimensions, providing a unified and controllable simulation basis for complex combustion systems. By projecting data from different sources into the master coordinate system and implementing spatial alignment, unit normalization and scale adjustment, the simulation distortion problem caused by inconsistent size and physical units between multi-parameter inputs can be effectively solved, and the consistency of data input and simulation repeatability can be enhanced. Implementing time-segmented turbulence modeling on dynamic mixing field control data helps to accurately capture the flow disturbance behavior and non-steady-state fuel distribution pattern in different combustion stages, and significantly improves the modeling accuracy of transient flame propagation characteristics, flame entrainment and other phenomena. Based on the topological slicing and feature mapping of local geometric reconstruction data, a structural analysis domain is constructed, which not only retains the factors affecting the flow and heat exchange of complex boundary morphology, but also improves the spatial response simulation capability of high thermal hysteresis areas and flow field splitting zones, ensuring the authenticity and effectiveness of structural adjustments. By leveraging the coupling conditions between the injection boundary, turbulence field, and geometric domain to construct a multi-physics simulation mapping, the system comprehensively simulates the flow-heat-chemical-structural coupling mechanism in the combustion process, accurately predicting key performance indicators such as localized combustion instability, concentrated temperature peaks, and wall thermal stresses. By integrating simulation results into feedback optimization of the initial model, precise corrections can be made to the nozzle layout, fuel distribution, and structural dimensions, resulting in a more efficient flame propagation path, more stable combustion behavior, and more balanced heat flux distribution, providing a highly reliable optimization design basis for engineering applications.

[0134] In an embodiment of the present invention, the internal structure of the nozzle is meshed and decomposed based on the geometric dimensions and fluid properties in the adjustment data. Key geometric parameters and velocity vector features are extracted at different scales (microchannel, nozzle, flow field influence zone) to generate injection boundary constraint data, which is used to define the jet inlet boundary conditions in subsequent simulations. Dynamic data is segmented and modeled along the time axis (e.g., with a time step of Δt = 0.01s). A fuel-air turbulent mixing model is constructed for each time period, and its transient turbulence distribution function is established to form time-segmented turbulence distribution field data to support transient simulation analysis. Using topological slicing technology, the three-dimensional combustion chamber model is decomposed into multiple local substructure units. The geometric characteristics of each substructure unit are mapped to physical influencing factors (e.g., pressure drop coefficient, streamline offset factor), generating structural analysis domain data that reflects the impact of local geometric deformation on the overall flow field. A unified master coordinate system is established, with the nozzle center axis as the Z-axis reference direction. For the injection boundary constraint data, time-segmented turbulence distribution data, and structural analysis domain data, the following steps are performed: A coordinate mapping matrix is ​​used to calibrate the spatial positions of the three data types, unifying length units (e.g., mm → m), temperature units (e.g., Kelvin), and pressure units (e.g., Pa). The data is then interpolated to conform to a unified grid scale, resulting in unified simulation domain coordinate data with temporal and spatial consistency and scale compatibility. Based on this unified simulation domain coordinate data, cross-domain coupling boundaries (e.g., nozzle exit-combustion core region, fuel mixing region-expansion region boundary) are defined. A synergistic model of multiple field variables (temperature T, velocity V, pressure P, species concentration Ci) is constructed: the control volume is constructed using the finite volume method (FVM); coupled boundary conditions (e.g., continuity, momentum conservation, and energy transfer) are set; and a multiphysics solver (e.g., Fluent, OpenFOAM, etc.) is introduced for coupled integrated simulation, resulting in a coupled integrated simulation result dataset, including flow, temperature, and chemical reaction rate fields. The heat release rate and temperature distribution in the combustion zone are analyzed, and secondary local optimization is performed on areas with low combustion efficiency. The air-fuel ratio and turbulence parameters are further calibrated based on the concentrations of species such as NOx and CO in the simulation. Based on the presence of recirculation zones or dead zones in the simulated flow field, the local geometry of the combustion chamber is iteratively adjusted to generate an optimized 3D model (i.e., a 3D optimized model) that achieves higher combustion efficiency, lower emissions, and more stable flow performance.

[0135] Preferably, step S4 includes the following steps:

[0136] Step S41: Integrate the three-dimensional optimization model into the combustion control system to perform actual combustion testing;

[0137] Step S42: monitoring the flame morphology and temperature field distribution in the actual combustion test using a high-temperature thermal imager to obtain combustion feedback data;

[0138] Step S43: Analyze the combustion performance of the combustion feedback data, and perform dynamic effect error calibration on the three-dimensional optimization model based on the combustion performance to generate a high-precision three-dimensional simulation model of the natural gas burner.

[0139] By integrating the optimized 3D model into a combustion control system and conducting actual combustion tests, the present invention verifies the simulation model's ability to fit real-world operating conditions. This establishes a closed-loop control system of "model-measurement-feedback-correction," significantly enhancing the model's credibility and engineering adaptability. Utilizing a high-temperature thermal imager for full-field dynamic monitoring of the flame morphology and temperature field, the system rapidly acquires high-resolution, timely thermal distribution maps, effectively capturing the real-time characteristics of the combustion core, boundary layer, and thermal hysteresis zone, providing fundamental data support for subsequent error calibration. Comparing and analyzing the monitored combustion feedback data with the simulated prediction data identifies deviations in the model's flame structure, peak temperature location, and heat flux density. By constructing combustion performance index functions, the model parameters are dynamically adjusted to achieve targeted error correction and behavior correction. Continuously iteratively correcting the optimized 3D model through a feedback calibration mechanism significantly improves the model's accuracy in describing complex combustion behaviors (such as flashback, flameout, and localized overheating), ultimately resulting in a high-fidelity 3D simulation model with engineering-grade accuracy and control precision.

[0140] In this embodiment of the present invention, the 3D optimization model is converted into controllable physical parameters (such as fuel flow rate, ignition position, and nozzle angle), which are then imported into the parameter setting module of the combustion control system. A structural device corresponding to the 3D model (such as an adjustable nozzle and a modular combustion chamber) is installed in a test furnace or industrial test platform. The actual combustion test program is initiated, and initial conditions such as natural gas flow rate, air volume, and preheat temperature are set to be consistent with the simulation boundaries. This creates an integrated structure-control test combustion device, achieving physical reproduction of the 3D optimization model and a controllable combustion test environment. A high-temperature infrared thermal imager (temperature range > 2000K, frame rate ≥ 50Hz) is used for non-contact, real-time monitoring of the combustion flame area. A high-speed industrial camera is used to capture the flame morphology evolution process, recording key morphological indicators such as edge contour, oscillation frequency, and flame anchor position. Monitoring content includes temperature field distribution data: temperature gradients in the flame core, edge, and recirculation zones. Flame morphology data: flame length, width, cone angle, and stability fluctuations (spectral analysis). Data from the system's inner wall temperature sensor and exhaust emission analyzer, including NOx / CO / CH4 concentrations and combustion residues, are simultaneously recorded. Complete combustion feedback data is generated, including thermal imaging of the temperature field, time series data on flame morphology, and combustion stability curves. The thermal imaging data is spatially compared with the simulated temperature field to calculate temperature deviations in key areas. Image contour analysis of the flame morphology is performed, and boundary fitting is performed with the 3D simulated flame structure to extract error regions. Combustion feedback data is compared with simulation results to identify three error sources: structural error (geometric reconstruction deviation); dynamic response error (inconsistency between transient mixing and ignition); and boundary condition error (initial gas temperature / pressure settings not matching actual conditions). Using an inverse error mapping mechanism, the temperature error distribution and flame morphology deviation are fed back to the simulation model. The nozzle boundary velocity distribution, fuel distribution function, and wall heat conduction parameters are dynamically corrected. A machine learning regression model (such as LSTM or GPR) is used to dynamically compensate and predict the simulated boundary conditions. This results in a high-precision 3D simulation model of the natural gas burner, with an error control within ±3%, and a highly consistent thermal response and structural matching capability with actual combustion behavior.

[0141] Preferably, step S41 includes the following steps:

[0142] Step S411: Start the combustion control system and create an actual combustion test project; import the three-dimensional optimization model into the combustion control system, and input the natural gas fuel characteristic data into the three-dimensional optimization model to generate integrated combustion control model data;

[0143] Step S412: Setting combustion test parameters in the combustion control system, wherein the fuel flow rate is set to 10–30 m³ / h, the air flow rate is set to 20–100 m³ / h, the combustion chamber temperature is set to 900–1500°C, and the combustion duration is set to 600–1800 seconds; generating combustion test parameter setting data;

[0144] Step S413: Setting ignition and preheating parameters in the combustion control system, wherein the ignition energy is set to 1000–1500 J, the preheating temperature is set to 300–600° C., and the preheating time is set to 60–180 seconds; generating ignition and preheating control data;

[0145] Step S414: Start the combustion control system and begin the actual combustion test process; continuously monitor and record key data in the combustion system every 10 seconds, including combustion temperature, combustion pressure, fuel / air mixture ratio, and CO / CO2 / NOx concentrations in the flue gas, to generate a real-time combustion monitoring data sequence;

[0146] Step S415: continuously analyzing the feedback signal of the combustion control system; when it is detected that all test parameters meet the set combustion test parameter range and the emission concentration is lower than the set threshold, it is determined that the actual combustion test process is completed.

[0147] This invention integrates a three-dimensional optimization model and natural gas fuel property data into a combustion control system to form an integrated combustion control model. This seamlessly integrates simulation modeling with actual control, significantly improving the accuracy and predictability of model-driven combustion test control. It supports flexible settings for key parameters such as fuel flow, air flow, combustion chamber temperature, and test time, adapting to combustion behavior research under diverse operating conditions and enhancing the engineering adaptability and parameter space exploration capabilities of system testing. Precise settings for ignition energy, preheating temperature, and preheating time ensure stable combustion system startup, reducing the risk of abnormal ignition or incomplete combustion, and improving the safety and repeatability of the testing process. Multi-dimensional key data, including combustion temperature, pressure, air-fuel ratio, and flue gas composition (CO / CO2 / NOx), are recorded on a 10-second cycle, forming a complete real-time combustion monitoring data sequence. This provides high-quality input for subsequent data analysis, model calibration, and anomaly diagnosis. The system dynamically determines the end of the test when all indicators meet the set ranges and pollutant concentrations meet threshold requirements based on real-time feedback signals and preset control parameters. This improves the intelligence and operational efficiency of the testing process, reduces human intervention, and ensures experimental consistency and safety. The highly timely, full-scale, and structured test data obtained will provide a solid data foundation for subsequent three-dimensional simulation model error calibration, further improving the model's simulation and generalization capabilities for complex combustion behaviors.

[0148] In the embodiment of the present invention, by starting the combustion control system and creating an actual combustion test project (step S411), the three-dimensional optimization model is imported into the combustion control system, and the natural gas fuel characteristic data is input into the three-dimensional optimization model, thereby generating integrated combustion control model data; then, the combustion test parameters are set in the combustion control system (step S412), wherein the fuel flow rate is set between 10-30m³ / h, the air flow rate is set between 20-100m³ / h, the combustion chamber temperature is set within the range of 900-1500°C, and the combustion duration is set to 600-1800 seconds, thereby generating combustion test parameter setting data; then, the ignition and preheating stage parameters are set (step S413), the ignition energy is controlled between 1000-1500J, and the preheating temperature is 300-6 00°C, the preheating time is 60-180 seconds, and ignition and preheating control data are generated; after completing the parameter setting, the combustion control system is started to formally start the actual combustion test process (step S414), with each 10-second time unit continuously monitoring and recording various key data in the combustion system, including combustion temperature, combustion pressure, fuel / air mixture ratio, and CO, CO2, NOx concentrations in the flue gas, thereby generating a real-time combustion monitoring data sequence; finally, the feedback signal of the combustion control system is continuously analyzed during the test (step S415). When it is detected that all test parameters meet the set combustion test parameter range and the emission concentration is lower than the set threshold, the actual combustion test process is automatically determined to be over, completing the engineering-level combustion performance verification of the three-dimensional optimization model.

[0149] It is particularly important that step S43 further includes the following steps:

[0150] Step S431: Extracting combustion performance parameters from combustion feedback data, where the combustion performance parameters include flame stability, temperature distribution uniformity, combustion efficiency, and NO x Emission trends;

[0151] Step S432: Performing a temporal and spatial comparison between the combustion performance index data and the corresponding simulated performance data in the three-dimensional optimization model, extracting the error sources and error distribution trends, and generating dynamic effect deviation characteristic data; performing parameter back-substitution correction on the dynamic effect deviation characteristic data to generate model parameter correction data;

[0152] Step S433: calibrate the dynamic effect error of the three-dimensional optimization model based on the model parameter correction data to generate a high-precision three-dimensional simulation model of the natural gas burner.

[0153] In the embodiment of the present invention, a high-frequency sampling data processing algorithm is used to perform multi-dimensional statistics on the combustion feedback data; the following key combustion performance parameters are extracted: flame stability parameters: including flame shedding frequency, flashback probability, and flame anchor position fluctuation; temperature distribution uniformity: temperature difference of each cross section, temperature gradient amplitude; combustion efficiency: unburned carbon concentration, fuel utilization rate; NO x Emission trend: NO per unit mass x The generation rate and peak moment position; the proposed parameters will be standardized into comparable time-space curves or time series field distribution data to generate a combustion performance parameter set, providing a comparison benchmark for subsequent error analysis. The simulation output and combustion feedback data will be aligned in the spatial coordinate domain and time axis; the extracted error terms include: flame anchor point offset distance, temperature uniformity difference field, combustion efficiency deviation rate, NO x The system analyzes the peak misalignment of the time series; constructs an error tensor using a spatiotemporal dynamic error mapping method; identifies the sources of deviation: structural errors (nozzle, expansion section) and parameter errors (mixing ratio, turbulence intensity); constructs an inverse calibration model using the mapping relationship between the deviation distribution and the structural / control parameters; outputs the simulation model control parameters that need to be adjusted, such as injection velocity correction, mixing ratio fine-tuning coefficient, wall heat flux correction factor, etc., to generate dynamic effect deviation characteristic data and model parameter correction data. This correction data is input into the 3D optimization model; and performs dynamic parameter reconstruction: recalibrating the nozzle boundary conditions (velocity, angle); adjusting the reaction rate or eddy loss factor in the combustion model; and correcting the turbulence model boundary scale and heat transfer coefficient in the CFD model. A new round of high-precision simulation is performed, focusing on assessing whether the error terms have converged to the tolerance range. If not, back-iteration is repeated (forming a closed-loop simulation calibration mechanism) to generate a high-precision 3D simulation model of the natural gas burner, which can be used for subsequent control strategy design or structural optimization.

[0154] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced therein.

[0155] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. An integrated design method for a three-dimensional simulation model of a natural gas burner, characterized in that: The following steps are involved: Step S1: Collecting geometric parameters and operating parameters of the natural gas burner to obtain initial equipment parameter information; Laser micro-texturing is performed on the inner surface of the combustion chamber of the natural gas burner to generate periodic micro-groove array data; Based on the initial device parameter information and the periodic micro-groove array data, a three-dimensional initial model of the natural gas burner is constructed using three-dimensional modeling software; wherein step S1 includes the following steps: Step S11: using a multi-source sensor to collect geometric parameters and operating parameters of the natural gas burner to obtain initial equipment parameter information; Step S12: extracting the internal surface temperature distribution data of the combustion chamber of the natural gas burner based on the initial equipment parameter information, and performing airflow scouring path analysis on the natural gas burner based on the internal surface temperature distribution data of the combustion chamber, generating high heat load areas and main heat transfer path areas, and uniformly marking them as laser microtexturing priority processing area data; Step S13: performing laser microtexturing on the inner surface of the combustion chamber of the natural gas burner based on the laser microtexturing priority processing area data using femtosecond laser pulses to generate periodic microgroove array structure data; Step S14: Based on the initial device parameter information set and the periodic micro-groove array structural parameter data, a three-dimensional initial structural model of the natural gas burner is constructed in a three-dimensional modeling software, wherein the construction process includes: Establish the geometric entities of the natural gas burner shell and combustion channel; Mapping the periodic micro-groove array to the corresponding area of ​​the combustion chamber wall; Add operating condition mark points; Step S2: Obtaining natural gas fuel characteristic data, inputting the fuel characteristic data into a three-dimensional initial model to simulate the combustion process, and performing a multi-dimensional evaluation of the simulated combustion process to generate a combustion process evaluation result; Step S3: Optimizing the three-dimensional initial model based on the combustion process evaluation results. If the combustion process evaluation results do not reach a preset combustion efficiency threshold, the nozzle structure, fuel mixing parameters, and combustion chamber geometric characteristics are collaboratively adjusted to generate a three-dimensional optimized model. Step S4: Integrate the three-dimensional optimization model into the combustion control system to conduct actual combustion tests, monitor the flame morphology and temperature field distribution through a high-temperature thermal imager, and obtain combustion feedback data; dynamically calibrate the parameters of the three-dimensional optimization model based on the combustion feedback data to generate a high-precision three-dimensional simulation model of the natural gas burner.

2. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 1, characterized in that: In step S12, the airflow flushing path analysis of the natural gas burner according to the combustion chamber inner surface temperature distribution data includes: The thermal field is reconstructed based on the temperature distribution data of the combustion chamber surface to obtain the absolute temperature value and spatial thermal gradient change of each surface node, and a spatial thermal gradient matrix is ​​generated, in which each matrix element contains a three-dimensional coordinate and a corresponding temperature derivative value; Based on the spatial thermal gradient matrix, the thermal gradient distribution partitioning and classification of the combustion chamber surface temperature distribution data are performed to generate the thermal partitioning data of the combustion chamber inner and outer surfaces; A high-heat threshold condition is set and used to perform regional cluster analysis on the thermal partition data of the internal and external surfaces of the combustion chamber. The cluster centers and their associated nodes are extracted to identify high-heat load areas where heat flux is concentrated. Perform flow field simulation in high heat load areas to extract the streamline path and velocity vector distribution of the gas in the combustion chamber; The scour intensity coefficient of each wall area is calculated based on the streamline path and velocity vector distribution to obtain the airflow scour path intensity map; the scour significant area of ​​the airflow scour path intensity map is screened by the set gas scour threshold to obtain the gas scour significant area; The high heat load area and the significant gas scouring area are spatially matched to obtain the main heat transfer path area, and the high heat load area and the main heat transfer path area are subjected to regional intersection operation, and the areas corresponding to the operation results are uniformly marked as laser microtexturing priority processing area data.

3. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 2, characterized in that: Flow simulation for high heat load areas includes: The combustion chamber geometry model size range is set to 200–500 mm × 200–500 mm × 200–600 mm, the combustion chamber diameter range is 80–150 mm, the length is 200–400 mm, the gas inlet velocity is set between 10–50 m / s, the inlet temperature range is 300–600 K, and the inlet pressure is set to 1.01×10 5 Pa; The wall temperature of the high heat load area was set in the range of 900–1500 K, and the outlet pressure was set to 1.01×10 5 Pa, combustion model selects non-premixed combustion model or PDF model.

4. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: Acquire natural gas fuel characteristic data; Step S22: Inputting the fuel characteristic data into the three-dimensional initial model to construct the combustion process simulation boundary conditions, wherein the boundary conditions include inlet conditions, wall conditions, turbulence model and combustion model; Step S23: performing a natural gas combustion process numerical simulation on the fuel characteristic data based on the combustion process simulation boundary conditions to generate a combustion process simulation data set, wherein the natural gas combustion process numerical simulation includes the ignition, heat transfer, diffusion, and emission processes of natural gas in a three-dimensional space; Step S24: Perform multi-dimensional quantitative analysis on the combustion process simulation data set to generate a combustion process evaluation result.

5. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 1, characterized in that: If the combustion process evaluation result does not reach the preset combustion efficiency threshold in step S3, the nozzle structure, fuel mixing parameters and combustion chamber geometric characteristics are coordinated and adjusted, including: If the combustion process evaluation result does not reach the preset combustion efficiency threshold, regional combustion anomaly features are extracted from the three-dimensional initial model based on the combustion process evaluation result to obtain a collaborative adjustment target parameter set, where the collaborative adjustment target parameter set includes nozzle exit velocity and angle deviation, air-fuel ratio deviation, and geometric thermal hysteresis zone characteristics; The nozzle structure in the three-dimensional initial model is optimized for the curvature of the nozzle internal channel according to the nozzle outlet velocity and angle deviation, and the nozzle structure adjustment data is generated; Dynamically control the fuel mixing field of the fuel mixing parameters in the three-dimensional initial model through the air-fuel ratio deviation to generate fuel dynamic mixing field control data; The geometric characteristics of the combustion chamber are used to adjust the ratio of the expansion section and the contraction section of the combustion chamber by using the geometric thermal hysteresis zone characteristics, and the local geometric reconstruction data of the combustion chamber is generated; The nozzle structure adjustment data, fuel dynamic mixing field control data, and combustion chamber local geometry reconstruction data are coupled and integrated for simulation, and the three-dimensional initial model is optimized using the simulation results to obtain a three-dimensional optimized model.

6. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 5, characterized in that: The nozzle structure adjustment data, fuel dynamic mixing field control data, and combustion chamber local geometry reconstruction data are coupled and integrated for simulation, and the three-dimensional initial model is optimized based on the simulation results, including: Perform multi-scale parameter extraction on the nozzle structure adjustment data to generate injection boundary constraint data; Conduct time-series segmented modeling of fuel dynamic mixing field control data to generate time-segmented turbulence distribution field data; Perform topological slicing and local feature mapping on the local geometric reconstruction data of the combustion chamber to generate structural analysis domain data; The injection boundary constraint data, time segmented turbulence distribution field data, and structure analysis domain data are uniformly projected into a master coordinate system for spatial alignment, unit normalization, and scale adjustment to form unified simulation domain coordinate data; Based on the cross-domain coupling boundary, multi-field variable coupling integration simulation mapping is performed on the unified simulation domain coordinate data to construct the coupled integrated simulation results; The 3D initial model is optimized by coupling the integrated simulation results.

7. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: Integrate the three-dimensional optimization model into the combustion control system to perform actual combustion testing; Step S42: monitoring the flame morphology and temperature field distribution in the actual combustion test using a high-temperature thermal imager to obtain combustion feedback data; Step S43: Analyze the combustion performance of the combustion feedback data, and perform dynamic effect error calibration on the three-dimensional optimization model based on the combustion performance to generate a high-precision three-dimensional simulation model of the natural gas burner.

8. The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 7, characterized in that: Step S41 includes the following steps: Step S411: Start the combustion control system and create an actual combustion test project; import the three-dimensional optimization model into the combustion control system, and input the natural gas fuel characteristic data into the three-dimensional optimization model to generate integrated combustion control model data; Step S412: Setting combustion test parameters in the combustion control system, wherein the fuel flow rate is set to 10–30 m³ / h, the air flow rate is set to 20–100 m³ / h, the combustion chamber temperature is set to 900–1500°C, and the combustion duration is set to 600–1800 seconds; generating combustion test parameter setting data; Step S413: Setting ignition and preheating parameters in the combustion control system, wherein the ignition energy is set to 1000–1500 J, the preheating temperature is set to 300–600° C., and the preheating time is set to 60–180 seconds; generating ignition and preheating control data; Step S414: Start the combustion control system and begin the actual combustion test process; continuously monitor and record key data in the combustion system every 10 seconds, including combustion temperature, combustion pressure, fuel / air mixture ratio, and CO / CO2 / NOx concentrations in the flue gas, to generate a real-time combustion monitoring data sequence; Step S415: continuously analyzing the feedback signal of the combustion control system; when it is detected that all test parameters meet the set combustion test parameter range and the emission concentration is lower than the set threshold, it is determined that the actual combustion test process is completed.

9. An integrated design system for a three-dimensional simulation model of a natural gas burner, characterized in that: The integrated design method for a three-dimensional simulation model of a natural gas burner according to claim 1 is used to implement the integrated design system for a three-dimensional simulation model of a natural gas burner, comprising: The initial modeling module is used to collect the geometric parameters and operating parameters of the natural gas burner to obtain initial equipment parameter information; perform laser micro-texturing on the combustion chamber surface of the natural gas burner to generate periodic micro-groove array data; and construct a 3D initial model of the natural gas burner using 3D modeling software based on the initial equipment parameter information and periodic micro-groove array data. The combustion simulation module is used to obtain natural gas fuel characteristic data, input the fuel characteristic data into the three-dimensional initial model to simulate the combustion process, and perform multi-dimensional evaluation of the simulated combustion process to generate the combustion process evaluation results; The model optimization module is used to optimize the 3D initial model based on the combustion process evaluation results. If the combustion process evaluation results do not meet the preset combustion efficiency threshold, the nozzle structure, fuel mixing parameters and combustion chamber geometric characteristics are coordinated to generate a 3D optimized model; The parameter calibration module is used to integrate the 3D optimization model into the combustion control system for actual combustion testing. The module monitors the flame morphology and temperature field distribution through a high-temperature thermal imager to obtain combustion feedback data. The module dynamically calibrates the parameters of the 3D optimization model based on the combustion feedback data to generate a high-precision 3D simulation model of the natural gas burner.

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