Optimization method and device for industrial silicon smelting flue gas heat exchange efficiency

Abstract

The invention provides an optimization method and device for industrial silicon smelting flue gas heat exchange efficiency, and relates to the technical field of industrial silicon smelting smoke.The optimization method comprises the steps that a main flue gas pipe geometric model is obtained according to first design information, a smelting associated information set is obtained, the smelting associated information set is adopted to conduct dust deposition attachment simulation on the main flue gas pipe geometric model, and a dust deposition distribution model is obtained; and analyzing and positioning a plurality of ash deposition high-risk areas in the ash deposition distribution model, taking the plurality of ash deposition high-risk areas as first heat exchange optimization information, and performing graphene material layout on the target main smoke pipe by adopting the first heat exchange optimization information to complete smelting flue gas heat exchange efficiency optimization of the industrial silicon smelting scene. The technical problem that in the prior art, the ash removal effect is poor, the cleaning difficulty is large, and consequently the heat exchange efficiency of the industrial silicon smelting waste heat boiler is reduced is solved. The technical effects that the heat exchange efficiency of the boiler in the industrial silicon smelting process is effectively improved, the influence of dust deposition on the heat exchange performance is reduced, the equipment maintenance cost is reduced, and the production efficiency is improved are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of industrial silicon smelting smoke, and in particular to a method and a device for optimizing the heat exchange efficiency of industrial silicon smelting smoke. Background Art

[0002] Industrial silicon waste heat boilers and conventional waste heat boilers are significantly different in the process of treating smelting flue gas, mainly due to the characteristics of dust generated by industrial silicon smelting. The microsilicon powder produced during the industrial silicon smelting process is very fine in particle size, and tiny SiO particles account for 80%-90% of the smoke components. Most of the particle sizes are less than 1 micron, and the surface area of ​​the dust wall is about 20 square meters / gram. Due to the strong adhesion of microsilicon powder, during the operation of the boiler, these tiny particles are very likely to generate static electricity and adsorb on the outer surface of the boiler tube wall, making it difficult to clean.

[0003] Microsilica powder has low thermal conductivity. If it is not cleaned in time, the heat exchange efficiency of the waste heat boiler will be significantly reduced. Traditional steel ball or shock wave cleaning methods can only clean partially, with poor results and difficulty in completely removing accumulated dust. This requires regular shutdown of the furnace for manual cleaning, which increases equipment maintenance costs and downtime, affecting production efficiency.

[0004] The existing technology has the technical problems of poor dust removal effect and great cleaning difficulty, which leads to reduced heat exchange efficiency of industrial silicon smelting waste heat boiler. Summary of the invention

[0005] The present application provides a method and device for optimizing the heat exchange efficiency of industrial silicon smelting flue gas, which is used to solve the technical problems in the prior art that the dust cleaning effect is poor and the cleaning difficulty is great, resulting in a decrease in the heat exchange efficiency of the industrial silicon smelting waste heat boiler.

[0006] In view of the above problems, the present application provides a method and device for optimizing the heat exchange efficiency of industrial silicon smelting flue gas.

[0007] In a first aspect of the present application, a method for optimizing the heat exchange efficiency of industrial silicon smelting flue gas is provided, the method comprising: interactively obtaining first design information of a target main smoke duct, and obtaining a main smoke duct geometric model based on the first design information; interactively accessing an industrial silicon smelting log to obtain a smelting-related information set, wherein the smelting-related information set comprises a microsilicon powder information set and a smelting flue gas information set; using the smelting-related information set to perform ash adhesion simulation on the main smoke duct geometric model to obtain an ash distribution model; analyzing and locating multiple high-risk ash areas in the ash distribution model, and using the multiple high-risk ash areas as first heat exchange optimization information; using the first heat exchange optimization information to execute graphene material layout on the target main smoke duct to complete the optimization of the smelting flue gas heat exchange efficiency of the industrial silicon smelting scenario.

[0008] In a second aspect of the present application, a device for optimizing the heat exchange efficiency of flue gas in industrial silicon smelting is provided, the device comprising: a main flue pipe geometric model acquisition module, the main flue pipe geometric model acquisition module is used to interactively obtain first design information of a target main flue pipe, and obtain a main flue pipe geometric model according to the first design information; a smelting associated information acquisition module, the smelting associated information acquisition module is used to interactively obtain an industrial silicon smelting log, and obtain a smelting associated information set, wherein the smelting associated information set includes a microsilica powder information set and a smelting flue gas information set; an ash accumulation distribution model acquisition module, the ash accumulation distribution model acquisition module The obtaining module is used to use the smelting associated information set to perform ash adhesion simulation on the main smoke pipe geometric model to obtain an ash distribution model; the ash high-risk area positioning module is used to analyze and locate multiple ash high-risk areas in the ash distribution model, and use the multiple ash high-risk areas as the first heat exchange optimization information; the smelting flue gas heat exchange efficiency optimization module is used to use the first heat exchange optimization information to execute graphene material layout on the target main smoke pipe, and complete the smelting flue gas heat exchange efficiency optimization for the industrial silicon smelting scenario.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] The method provided in the embodiment of the present application obtains the first design information of the target main smoke pipe through interaction, and obtains the main smoke pipe geometric model according to the first design information; interacts with the industrial silicon smelting log to obtain a smelting-related information set, wherein the smelting-related information set includes a microsilicon powder information set and a smelting flue gas information set; uses the smelting-related information set to simulate the ash deposition adhesion in the main smoke pipe geometric model to obtain an ash deposition distribution model; analyzes and locates multiple high-risk areas for ash deposition in the ash deposition distribution model, and uses the multiple high-risk areas for ash deposition as the first heat exchange optimization information; uses the first heat exchange optimization information to perform graphene material layout on the target main smoke pipe, and completes the optimization of the smelting flue gas heat exchange efficiency in the industrial silicon smelting scene. The technical effect of effectively improving the heat exchange efficiency of the boiler in the industrial silicon smelting process, reducing the impact of ash deposition on heat exchange performance, reducing equipment maintenance costs, and improving production efficiency is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1A schematic flow chart of a method for optimizing heat exchange efficiency of industrial silicon smelting flue gas provided in this application;

[0013] Figure 2 A schematic diagram of the structure of a device for optimizing the heat exchange efficiency of industrial silicon smelting flue gas provided in this application.

[0014] Explanation of the reference numerals: main smoke pipe geometric model acquisition module 11, smelting related information acquisition module 12, ash accumulation distribution model acquisition module 13, ash accumulation high risk area positioning module 14, smelting flue gas heat exchange efficiency optimization module 15. DETAILED DESCRIPTION

[0015] The present application provides a method and device for optimizing the heat exchange efficiency of flue gas in industrial silicon smelting, which is used to solve the technical problem in the prior art that the dust cleaning effect is poor and the cleaning is difficult, resulting in reduced heat exchange efficiency of waste heat boilers in industrial silicon smelting. The technical effect of effectively improving the heat exchange efficiency of boilers in the process of industrial silicon smelting, reducing the impact of dust accumulation on heat exchange performance, reducing equipment maintenance costs, and improving production efficiency is achieved.

[0016] Below, the technical solutions in the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention are shown in the accompanying drawings, rather than all of them.

[0017] Embodiment 1, as Figure 1 As shown, the present application provides a method for optimizing the heat exchange efficiency of industrial silicon smelting flue gas, the method comprising:

[0018] The first design information of the target main smoke pipe is interactively obtained, and the main smoke pipe geometric model is obtained according to the first design information.

[0019] Specifically, by interacting with the main smoke pipe design information, the first design information of the target main smoke pipe is obtained, and the first design information refers to various parameters and data of the target main smoke pipe in the design stage, including key data such as geometric parameters, material properties, design pressure, temperature range, etc. of the main smoke pipe, among which geometric parameters are length, diameter, wall thickness, etc. After obtaining the first design information, the first design information is input into the design software, and the main smoke pipe geometric model is generated by the design software according to the input design information. The main smoke pipe geometric model is obtained according to the design information of the target main smoke pipe, which provides reliable data support for the subsequent optimization process.

[0020] Interact with industrial silicon smelting logs to obtain a smelting-related information set, wherein the smelting-related information set includes a microsilica powder information set and a smelting flue gas information set.

[0021] Furthermore, the microsilica fume information set includes a microsilica fume physical property set and a microsilica fume chemical property set.

[0022] Furthermore, the smelting flue gas information set includes a flue gas chemical property set and a flue gas physical property set.

[0023] Specifically, by interacting with the log data of industrial silicon smelting, smelting-related data information is collected. The industrial silicon smelting log refers to a detailed record file that records all relevant data and events in the industrial silicon smelting process. The smelting-related data information includes a microsilica powder information set and a smelting flue gas information set. The microsilica powder information set includes a microsilica powder physical property set and a microsilica powder chemical property set, wherein the microsilica powder physical property set includes the particle size distribution, specific surface area, density and other physical properties of microsilica powder, and the microsilica powder chemical property set includes the chemical composition, chemical reaction activity, oxygen content and other chemical properties of microsilica powder. The smelting flue gas information set includes a flue gas chemical property set and a flue gas physical property set, wherein the flue gas chemical property set includes component analysis in the flue gas, such as chemical components such as silicon dioxide, carbon monoxide, carbon dioxide, and nitrogen oxides. The flue gas physical property set includes physical properties such as temperature, pressure, and flow rate of the flue gas. By obtaining smelting-related data, the adhesion process of microsilica powder on the inner wall of the main smoke pipe can be simulated more accurately, thereby effectively predicting and controlling the ash accumulation and optimizing the heat exchange efficiency.

[0024] The smelting-related information set is used to simulate ash deposition on the main smoke pipe geometric model to obtain an ash deposition distribution model.

[0025] Furthermore, the smelting-related information set is used to simulate ash adhesion on the main smoke pipe geometric model to obtain an ash distribution model. The method includes: using the first design information as modeling information, and using CFD software to establish the main smoke pipe geometric model; interactively obtaining the operating condition information of the industrial silicon smelting scene, and constructing simulation boundary conditions based on the operating condition information; after inputting the smelting-related information set into the main smoke pipe geometric model, running the CFD software with the simulation boundary conditions as constraints, simulating the adhesion process of microsilica powder on the inner wall of the main smoke pipe in the main smoke pipe geometric model, and obtaining the ash distribution model.

[0026] Specifically, first, the first design information obtained is used as modeling information, and the geometric model of the main smoke duct is established using computational fluid dynamics software (CFD). CFD software is a software tool used to simulate fluid flow, heat transfer and other related physical phenomena. The main smoke duct geometric model is established using CFD software, so that the main smoke duct geometric model can accurately reflect the main smoke duct structure in the actual design, thereby ensuring the accuracy of subsequent simulations.

[0027] Then, by interacting with the industrial silicon smelting scene, detailed working condition information in the industrial silicon smelting scene is obtained, including parameters such as temperature, pressure, flue gas flow rate, etc. during the smelting process. Based on the obtained working condition information, the simulation boundary conditions are constructed, that is, the velocity, temperature, pressure and other parameters of the main flue gas inlet and outlet are set, as well as the thermal boundary conditions of the solid wall, such as the convection heat transfer coefficient, temperature, etc. The simulation boundary conditions refer to the boundary restriction conditions used to define fluid flow and heat transfer in CFD simulation to ensure that the simulation environment is consistent with the actual working conditions.

[0028] Finally, the smelting-related information set including the physical property set of microsilica powder, the chemical property set of microsilica powder, the chemical property set of flue gas and the physical property set of flue gas is input into the main flue pipe geometric model, and the CFD software is run for simulation with the simulation boundary conditions as constraints. During the simulation process, the adhesion process of microsilica powder on the inner wall of the main flue pipe is calculated and analyzed by CFD software to generate an ash distribution model, which shows the ash accumulation of microsilica powder on the inner wall of the main flue pipe. Based on the ash accumulation, corresponding cleaning and optimization measures can be formulated to improve the flue gas heat exchange efficiency and reduce the impact of ash accumulation on the heat exchange performance. For example, if it is found in the simulation that the ash accumulation in certain areas of the inner wall of the main flue pipe is particularly serious, graphene materials can be used to cover these areas to reduce ash adhesion. At the same time, the heat exchange efficiency of the smelting flue gas can be further improved by optimizing the design and operating conditions of the main flue pipe.

[0029] Furthermore, after the smelting-related information set is input into the main smoke pipe geometric model, the CFD software is run with the simulation boundary conditions as constraints, and the adhesion process of microsilica powder on the inner wall of the main smoke pipe is simulated in the main smoke pipe geometric model to obtain the ash distribution model. The method also includes: presetting an ash tracking window and an ash step length; taking the ash step length as a constraint, using the ash tracking window to extract and obtain multiple stage ash distribution models from the CFD software; according to the extraction order, serializing and overlapping the multiple stage ash distribution models, performing ash distribution stability analysis, and obtaining stability analysis results; if the stability analysis result is that the ash distribution is stable, extracting the terminal stage ash distribution model from the multiple stage ash distribution models as the ash distribution model.

[0030] Specifically, in CFD simulation, the ash accumulation tracking window and ash accumulation step length are preset. The ash accumulation tracking window indicates the range of monitoring ash accumulation distribution in a specific time period, such as a specific time period of one month, two months, or half a year. The ash accumulation step length refers to the step length unit of the simulation time, which determines the time interval for extracting the ash accumulation distribution model each time, such as extracting the ash accumulation distribution model every 5 days, 7 days, etc. Then, with the ash accumulation step length as a constraint, multiple stage ash accumulation distribution models are extracted from the CFD software through the ash accumulation tracking window. The multiple stage ash accumulation distribution models show the ash accumulation distribution on the inner wall of the main smoke pipe in different periods.

[0031] According to the order of extraction, the ash accumulation distribution models of multiple stages are serialized and overlapped to form a continuous ash accumulation change process. By comparing and analyzing the law of ash accumulation distribution changes over time, it is judged whether the ash accumulation tends to be stable, and the stability analysis results are obtained. If the stability analysis results show that the ash accumulation steps tend to be stable, the ash accumulation distribution model of the last stage when the ash accumulation steps tend to be stable is extracted from the ash accumulation distribution models of multiple stages as the ash accumulation distribution model, and the ash accumulation distribution model is used to reflect the simulation results of the ash accumulation of microsilica powder on the inner wall of the main smoke pipe. If the stability analysis results show that the ash accumulation steps are not stable, the ash accumulation tracking window and ash accumulation step length are reset, and the above steps are repeated to observe the changes of ash accumulation distribution over time until the ash accumulation distribution tends to be stable. The ash accumulation distribution model of the last stage when the ash accumulation steps tend to be stable is extracted from the ash accumulation distribution models of multiple stages as the ash accumulation distribution model. By obtaining the ash accumulation distribution model at the stable terminal stage of the ash accumulation distribution, the ash accumulation distribution model has high accuracy and stability, providing reliable data support for subsequent optimization measures.

[0032] The dust accumulation distribution model is used to analyze and locate multiple dust accumulation high risk areas, and the multiple dust accumulation high risk areas are used as the first heat exchange optimization information.

[0033] Specifically, after obtaining the ash accumulation distribution model, the integral distribution model is analyzed in detail to identify areas with more serious ash accumulation in the smoke pipe, that is, high-risk areas for ash accumulation. The high-risk areas for ash accumulation refer to areas with concentrated ash accumulation due to fluid dynamic characteristics and flue gas composition. The ash layer is thicker and may affect the flow and heat transfer efficiency of the flue gas. The multiple high-risk areas for ash accumulation identified are used as the first heat exchange optimization information. The first heat exchange optimization information refers to key data obtained based on the analysis of the ash accumulation distribution model and used to guide the optimization of heat exchange efficiency. The first heat exchange optimization information includes detailed data such as the specific location of the ash accumulation area, ash thickness, and coverage area, which provides a reliable basis and effective method for optimizing the heat exchange efficiency of flue gas during industrial silicon smelting.

[0034] The first heat exchange optimization information is used to execute graphene material layout on the target main smoke pipe to optimize the heat exchange efficiency of smelting flue gas in the industrial silicon smelting scenario.

[0035] Furthermore, the first heat exchange optimization information is used to execute graphene material layout on the target main smoke pipe. After that, the method also includes: interactively obtaining second design information of the target boiler smoke pipe, and constructing a boiler smoke pipe geometric model based on the second design information; using the smelting flue gas information set to perform heat exchange process simulation on the boiler smoke pipe geometric model to obtain a temperature distribution map inside the tube; locating multiple auxiliary heat dissipation areas according to the temperature distribution map inside the tube, and using the multiple auxiliary heat dissipation areas as the second heat exchange optimization information; using the second heat exchange optimization information to execute heat dissipation fin layout on the target boiler smoke pipe to complete the global heat exchange efficiency optimization of the industrial silicon smelting scenario.

[0036] Specifically, according to the first heat exchange optimization information, that is, according to the specific location of the dust accumulation area, the dust accumulation thickness, the coverage area and other information, the graphene material is accurately arranged on the target main smoke pipe. Graphene has excellent thermal conductivity and anti-dust properties, which can significantly reduce the amount of microsilica powder attached to the inner wall of the main smoke pipe and improve the heat exchange efficiency.

[0037] Then, the second design information of the target boiler smoke tube is interactively obtained. According to the second design information, the geometric model of the boiler smoke tube is constructed using CFD software. The geometric model of the boiler smoke tube includes parameters such as the length, diameter, wall thickness, and material of the boiler smoke tube. The heat exchange process of the boiler smoke tube geometric model is simulated using the smelting flue gas information set. The flow and heat transfer process of the flue gas in the boiler smoke tube are simulated in the model using CFD software, and the temperature distribution diagram in the tube is obtained by simulating the temperature distribution at different positions in the boiler smoke tube.

[0038] Next, according to the temperature distribution map in the tube, multiple auxiliary heat dissipation areas in the boiler smoke tube are analyzed and located. The auxiliary heat dissipation areas refer to places in the boiler smoke tube where the temperature is high and the heat exchange effect is poor, and these auxiliary heat dissipation areas are used as the second heat exchange optimization information, which is obtained based on the temperature distribution map analysis and is used to optimize the heat exchange efficiency of the boiler smoke tube.

[0039] Finally, the second heat exchange optimization information is used to arrange the heat dissipation fins for the target boiler smoke pipe. The heat dissipation fin is a structure used to enhance heat transfer, which has the function of enhancing heat transfer, forming strong turbulence to reduce soot accumulation, increasing the heat exchange surface area, and improving the heat exchange efficiency between the flue gas and the tube wall, thereby optimizing the overall heat exchange effect. Through the detailed optimization of the main smoke pipe and the boiler smoke pipe, the global heat exchange efficiency in the industrial silicon smelting scenario is significantly improved by using graphene materials and heat dissipation fins. The use of graphene materials reduces ash accumulation and improves the thermal conductivity of the main smoke pipe. The layout of heat dissipation fins increases the heat exchange surface area of ​​the boiler smoke pipe and improves the heat transfer effect. Finally, the comprehensive optimization of the heat exchange efficiency of industrial silicon smelting flue gas is achieved, the impact of ash accumulation on heat exchange performance is reduced, the equipment maintenance cost is reduced, and the overall efficiency of the smelting process is improved.

[0040] Furthermore, the smelting flue gas information set is used to perform a heat exchange process simulation on the boiler smoke tube geometric model to obtain a temperature distribution diagram inside the tube. The method also includes: interactively obtaining the equipment connection relationship of the industrial silicon smelting scene; connecting the main smoke tube geometric model and the boiler smoke tube geometric model according to the equipment connection relationship to obtain a boiler flue gas path model; and using the smelting flue gas information set to perform a heat exchange process simulation on the boiler flue gas path model to obtain a temperature distribution diagram inside the tube.

[0041] Specifically, the human-computer interaction system collects information from the operators of the industrial silicon smelting scene to obtain the equipment connection relationship in the smelting scene. The equipment connection relationship includes detailed information such as the connection method between the main smoke pipe and the boiler smoke pipe, the pipeline layout, and the valve position. According to the obtained equipment connection relationship, the main smoke pipe geometric model and the boiler smoke pipe geometric model are connected according to the equipment connection relationship. After the geometric model connection is completed, a complete boiler flue gas path model is formed. The boiler flue gas path model covers the entire flow path of the flue gas from the main smoke pipe to the boiler smoke pipe, including all key nodes and turning points. During the connection process, the matching and continuity between the geometric models are ensured to truly reflect the actual flue gas flow path. The smelting flue gas information set is input into the boiler flue gas path model, and the heat exchange process of the model is simulated using CFD software. During the simulation process, the CFD software will calculate the flow and heat transfer of the flue gas in the path model and generate a temperature distribution map in the tube. The temperature distribution map shows the temperature distribution of each position in the boiler flue gas path model, reflecting the effect of the flue gas flow and heat transfer in the path. By obtaining the equipment connection relationship and building a boiler flue gas path model, the heat exchange process can be completely simulated, and ultimately an accurate and reliable temperature distribution map inside the tube can be obtained, providing accurate and reliable data support for the optimization of heat exchange efficiency in industrial silicon smelting scenarios.

[0042] Furthermore, the smelting flue gas information set is used to perform a heat exchange process simulation on the boiler smoke tube geometric model to obtain a temperature distribution diagram inside the tube. The method also includes: after inputting the smelting-related information set into the boiler smoke gas path model, running the CFD software with the simulation boundary conditions as constraints to simulate the heat exchange process of the flue gas in the boiler smoke tube in the boiler smoke tube in the boiler smoke gas path model; presetting the heat exchange duration, and extracting the temperature distribution model of the boiler smoke gas path model in the CFD software according to the heat exchange duration; and performing temperature data collection and visualization processing based on the temperature distribution model to obtain the temperature distribution diagram inside the tube.

[0043] Specifically, in order to simulate more completely and accurately, the smelting related information set is used as input data and input into the boiler flue gas path model. The CFD software is run with the simulation boundary conditions as constraints. In the boiler flue gas path model, the heat exchange process of flue gas in the boiler smoke pipe is simulated, and the flow and heat transfer of flue gas in the path are calculated and analyzed by CFD software. The duration of heat exchange is preset. The duration of heat exchange refers to the length of time for simulating the heat exchange of flue gas in the boiler smoke pipe. According to the duration of heat exchange, the temperature distribution model of the boiler flue gas path model is extracted from the CFD software. The temperature distribution model shows the simulation results of the temperature distribution of each position in the boiler flue gas path model. Finally, based on the extracted temperature distribution model, the temperature data is collected and visualized by means of charts, thermal maps, etc., to obtain the temperature distribution map in the tube, so as to more intuitively analyze and understand the heat exchange process. By obtaining the temperature distribution map in the tube, the area with higher temperature can be intuitively and accurately displayed, providing support for the optimization of the heat exchange efficiency of industrial silicon smelting flue gas.

[0044] Embodiment 2, based on the same inventive concept as the method for optimizing the heat exchange efficiency of industrial silicon smelting flue gas in the above embodiment, Figure 2 As shown, the present application provides a device for optimizing the heat exchange efficiency of industrial silicon smelting flue gas, wherein the device comprises:

[0045] A main smoke pipe geometric model acquisition module 11, the main smoke pipe geometric model acquisition module 11 is used to interactively obtain the first design information of the target main smoke pipe, and obtain the main smoke pipe geometric model according to the first design information; a smelting associated information acquisition module 12, the smelting associated information acquisition module 12 is used to interact with the industrial silicon smelting log to obtain a smelting associated information set, wherein the smelting associated information set includes a microsilica powder information set and a smelting flue gas information set; an ash accumulation distribution model acquisition module 13, the ash accumulation distribution model acquisition module 13 is used to use the smelting associated information set in the The main smoke duct geometric model is used to simulate ash adhesion to obtain an ash distribution model; an ash high-risk area positioning module 14 is used to locate multiple ash high-risk areas in the ash distribution model analysis, and use the multiple ash high-risk areas as the first heat exchange optimization information; a smelting flue gas heat exchange efficiency optimization module 15 is used to use the first heat exchange optimization information to execute graphene material layout on the target main smoke duct, and complete the smelting flue gas heat exchange efficiency optimization for the industrial silicon smelting scenario.

[0046] Furthermore, the smelting related information acquisition module 12 is used to perform the following steps: the microsilica fume information set includes a microsilica fume physical property set and a microsilica fume chemical property set.

[0047] Furthermore, the smelting associated information obtaining module 12 is also used to perform the following steps: the smelting flue gas information set includes a flue gas chemical characteristic set and a flue gas physical characteristic set.

[0048] Furthermore, the smelting flue gas heat exchange efficiency optimization module 15 is also used to perform the following steps: interactively obtain the second design information of the target boiler smoke tube, and construct a boiler smoke tube geometric model based on the second design information; use the smelting flue gas information set to perform a heat exchange process simulation on the boiler smoke tube geometric model to obtain a temperature distribution map inside the tube; locate multiple auxiliary heat dissipation areas according to the temperature distribution map inside the tube, and use the multiple auxiliary heat dissipation areas as the second heat exchange optimization information; use the second heat exchange optimization information to execute heat dissipation fin layout on the target boiler smoke tube to complete the global heat exchange efficiency optimization of the industrial silicon smelting scenario.

[0049] Furthermore, the ash distribution model acquisition module 13 is used to perform the following steps: using the first design information as modeling information, and using CFD software to establish the main smoke pipe geometric model; interactively obtaining the operating condition information of the industrial silicon smelting scenario, and constructing simulation boundary conditions based on the operating condition information; after inputting the smelting-related information set into the main smoke pipe geometric model, running the CFD software with the simulation boundary conditions as constraints, simulating the adhesion process of microsilica powder on the inner wall of the main smoke pipe in the main smoke pipe geometric model, and obtaining the ash distribution model.

[0050] Furthermore, the dust accumulation distribution model acquisition module 13 is also used to perform the following steps: presetting a dust accumulation tracking window and a dust accumulation step; taking the dust accumulation step as a constraint, using the dust accumulation tracking window to extract and obtain multiple stage dust accumulation distribution models from the CFD software; according to the extraction order, serializing and overlapping the multiple stage dust accumulation distribution models, performing dust accumulation distribution stability analysis, and obtaining stability analysis results; if the stability analysis result is that the dust accumulation distribution is stable, extracting the terminal stage dust accumulation distribution model from the multiple stage dust accumulation distribution models as the dust accumulation distribution model.

[0051] Furthermore, the smelting flue gas heat exchange efficiency optimization module 15 is also used to perform the following steps: interactively obtain the equipment connection relationship of the industrial silicon smelting scene; connect the main smoke pipe geometric model and the boiler smoke pipe geometric model according to the equipment connection relationship to obtain the boiler flue gas path model; use the smelting flue gas information set to perform heat exchange process simulation on the boiler flue gas path model to obtain the temperature distribution diagram inside the pipe.

[0052] Furthermore, the smelting flue gas heat exchange efficiency optimization module 15 is also used to perform the following steps: after inputting the smelting related information set into the boiler flue gas path model, running the CFD software with the simulation boundary conditions as constraints, and simulating the heat exchange process of the flue gas in the boiler smoke pipe in the boiler flue gas path model; presetting the heat exchange duration, and extracting the temperature distribution model of the boiler flue gas path model in the CFD software according to the heat exchange duration; performing temperature data collection and visualization processing based on the temperature distribution model to obtain the temperature distribution diagram inside the tube.

[0053] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0054] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for optimizing the heat exchange efficiency of industrial silicon smelting flue gas, characterized in that: The method comprises: interactively obtaining first design information of a target main smoke pipe, and obtaining a main smoke pipe geometric model according to the first design information; Interact with industrial silicon smelting logs to obtain a smelting-related information set, wherein the smelting-related information set includes a microsilica powder information set and a smelting flue gas information set; The smelting related information set is used to simulate the ash deposition on the main smoke pipe geometric model to obtain an ash deposition distribution model; Analyzing and locating a plurality of high-risk areas for dust accumulation in the dust accumulation distribution model, and using the plurality of high-risk areas for dust accumulation as first heat exchange optimization information; The first heat exchange optimization information is used to execute graphene material layout on the target main smoke pipe to optimize the heat exchange efficiency of smelting flue gas in the industrial silicon smelting scenario.

2. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 1, characterized in that: The microsilica fume information set includes a microsilica fume physical property set and a microsilica fume chemical property set.

3. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 2, characterized in that: The smelting flue gas information set includes a flue gas chemical characteristic set and a flue gas physical characteristic set.

4. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 3, characterized in that: The first heat exchange optimization information is used to perform graphene material layout on the target main smoke pipe, and then the method further includes: Interactively obtaining second design information of a target boiler smoke tube, and constructing a boiler smoke tube geometric model according to the second design information; Using the smelting flue gas information set to simulate the heat exchange process of the boiler smoke tube geometric model, and obtain a temperature distribution diagram inside the tube; Locating a plurality of auxiliary heat dissipation areas according to the temperature distribution diagram in the tube, and using the plurality of auxiliary heat dissipation areas as second heat exchange optimization information; The second heat exchange optimization information is used to execute heat dissipation fin layout on the target boiler smoke tube, thereby completing the global heat exchange efficiency optimization of the industrial silicon smelting scenario.

5. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 4, characterized in that: The smelting-related information set is used to perform ash deposition simulation on the main smoke pipe geometric model to obtain an ash deposition distribution model, and the method includes: Using the first design information as modeling information, and using CFD software to establish a geometric model of the main smoke pipe; Interactively obtain the working condition information of the industrial silicon smelting scene, and construct simulation boundary conditions based on the working condition information; After inputting the smelting-related information set into the main smoke pipe geometric model, CFD software is run with the simulation boundary conditions as constraints, and the adhesion process of microsilica powder on the inner wall of the main smoke pipe is simulated in the main smoke pipe geometric model to obtain the ash accumulation distribution model.

6. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 5, characterized in that: After the smelting-related information set is input into the main smoke pipe geometric model, CFD software is run with the simulation boundary conditions as constraints, and the adhesion process of microsilica powder on the inner wall of the main smoke pipe is simulated in the main smoke pipe geometric model to obtain the ash accumulation distribution model. The method further includes: Preset dust accumulation tracking window and dust accumulation step length; Taking the dust accumulation step length as a constraint, using the dust accumulation tracking window to extract and obtain a multi-stage dust accumulation distribution model from the CFD software; According to the extraction order, the dust accumulation distribution models of the plurality of stages are serialized and overlapped, and the dust accumulation distribution stability analysis is performed to obtain the stability analysis result; If the stability analysis result shows that the dust accumulation distribution is stable, a terminal stage dust accumulation distribution model is extracted from the multiple stage dust accumulation distribution models as the dust accumulation distribution model.

7. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 5, characterized in that: The smelting flue gas information set is used to perform a heat exchange process simulation on the boiler smoke tube geometric model to obtain a temperature distribution diagram inside the tube, and the method further includes: Interactively obtain the equipment connection relationship of the industrial silicon smelting scene; Connecting the main smoke pipe geometric model and the boiler smoke pipe geometric model according to the equipment connection relationship to obtain a boiler smoke path model; The smelting flue gas information set is used to perform a heat exchange process simulation on the boiler flue gas path model to obtain a temperature distribution diagram inside the tube.

8. The method for optimizing heat exchange efficiency of industrial silicon smelting flue gas according to claim 7, characterized in that: The smelting flue gas information set is used to perform a heat exchange process simulation on the boiler smoke tube geometric model to obtain a temperature distribution diagram inside the tube, and the method further includes: After the smelting related information set is input into the boiler flue gas path model, CFD software is run with the simulation boundary conditions as constraints to simulate the heat exchange process of flue gas in the boiler flue pipe in the boiler flue gas path model; Preset the duration of heat exchange, and extract the temperature distribution model of the boiler flue gas path model in CFD software according to the duration of heat exchange; Temperature data collection and visualization processing are performed based on the temperature distribution model to obtain the temperature distribution diagram inside the pipe.

9. An optimization device for the heat exchange efficiency of industrial silicon smelting flue gas, characterized in that: The steps for implementing the method according to any one of claims 1 to 8 include: a main smoke pipe geometric model obtaining module, the main smoke pipe geometric model obtaining module being used to interactively obtain first design information of a target main smoke pipe, and obtain a main smoke pipe geometric model according to the first design information; A smelting-related information acquisition module, which is used to interact with industrial silicon smelting logs to obtain a smelting-related information set, wherein the smelting-related information set includes a microsilica powder information set and a smelting fume information set; An ash accumulation distribution model acquisition module, the ash accumulation distribution model acquisition module is used to use the smelting associated information set to perform ash adhesion simulation on the main smoke pipe geometric model to obtain an ash accumulation distribution model; A dust accumulation high risk area positioning module, the dust accumulation high risk area positioning module is used to analyze and locate multiple dust accumulation high risk areas in the dust accumulation distribution model, and use the multiple dust accumulation high risk areas as the first heat exchange optimization information; A smelting flue gas heat exchange efficiency optimization module, wherein the smelting flue gas heat exchange efficiency optimization module is used to use the first heat exchange optimization information to perform graphene material layout on the target main smoke pipe, thereby completing the optimization of the smelting flue gas heat exchange efficiency in the industrial silicon smelting scenario.

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