Method for predicting the economy of a multi-grade fluorite combined production of hydrofluoric acid and related equipment

Abstract

This invention belongs to the field of mineral processing and chemical technology. It provides an economic prediction method and related equipment for the co-production of hydrofluoric acid from multiple grades of fluorite. The method includes: determining a benchmark model between the production cost and yield of hydrofluoric acid from each grade of fluorite concentrate based on CaF2 content and impurity content; constructing an interaction effect model for the co-production of hydrofluoric acid from multiple grades of fluorite concentrate based on the mixing ratio of the multiple grades and the benchmark model; constructing an objective function for maximizing the economic benefits of hydrofluoric acid based on the selling price of hydrofluoric acid and the interaction effect model; and solving the objective function using a nonlinear programming algorithm to obtain the mixing ratio of the multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized. This invention provides a systematic method for quantifying the relationship between fluorite concentrate grade and the production cost and product value of hydrofluoric acid, thereby improving the economic efficiency of the co-production of hydrofluoric acid from multiple grades of fluorite.

Description

Technical Field

[0001] This invention relates to the fields of mineral processing and chemical technology, and in particular to an economic prediction method and related equipment for the combined production of hydrofluoric acid from multiple grades of fluorite. Background Technology

[0002] Fluorite (calcium fluoride) is a core raw material for the production of hydrofluoric acid. Its grade (CaF2 content) and impurity composition directly determine the difficulty of beneficiation, chemical conversion efficiency, and final product cost. In existing technologies, fluorite beneficiation and hydrofluoric acid production are typically optimized as independent processes, lacking a comprehensive economic model linking the entire process from raw materials to end products. When faced with fluorite resources of different grades, enterprises struggle to scientifically assess their development value, leading to blind raw material procurement decisions, mismatches between production processes and raw material characteristics, and ultimately, resource waste or poor economic returns. In particular, the economic feasibility of low- to medium-grade fluorite (CaF2 content below 95%) is often underestimated, while the added value of high-quality fluorite (CaF2 content above 95%) is not fully realized through product grading.

[0003] The reason for this is that the CaF2 content and impurity composition (SiO2, CaCO3, etc.) in fluorite concentrate directly affect the consumption of sulfuric acid, conversion reaction efficiency, equipment lifespan, product quality, and waste generation during hydrofluoric acid production. In existing technologies, enterprises typically face the following problems: (1) Limitations of using fluorite raw materials for the production of hydrofluoric acid: High-grade fluorite concentrate (CaF2≥95%) is expensive and has high procurement costs, but has good reaction efficiency and less interference from impurities; medium and low-grade fluorite concentrate (CaF2 85-95%) is cheap, but has high impurity content, which leads to increased sulfuric acid consumption, decreased reaction yield, and increased waste residue treatment costs.

[0004] (2) Lack of synergistic optimization methods between mineral processing product quality and hydrofluoric acid production raw material demand: Fluorite beneficiation enterprises and hydrofluoric acid production enterprises are often independent, lacking sufficient communication and connection between the product supply side and the demand side. This forces hydrofluoric acid production enterprises to either purchase as much high-grade raw material as possible to ensure stable production, or be forced to use medium and low-grade raw material to reduce costs. They have failed to achieve a balance between cost and benefit through the scientific ratio of high and low grades.

[0005] (3) The interaction of impurities in different grades of fluorite concentrate has not been quantified: The types and contents of impurities in different grades of fluorite concentrate are different. Direct mixing and use for hydrofluoric acid production may produce synergistic or antagonistic effects. Production enterprises often cannot accurately predict the reaction characteristics and economics of mixed fluorite concentrate on-site. Summary of the Invention

[0006] Aimed at at least in solving one of the technical problems existing in the prior art, the present invention provides an economic prediction method and related equipment for the joint production of hydrofluoric acid from multiple grades of fluorite.

[0007] One aspect of the present invention provides an economic prediction method for the co-production of hydrofluoric acid from multiple grades of fluorite, comprising: The CaF2 content and impurity content of multiple grades of fluorite concentrate were obtained, and a benchmark model between the hydrofluoric acid production cost and yield of each grade of fluorite concentrate was determined based on the CaF2 content and impurity content. Based on the mixing ratio and benchmark model of multiple grades of fluorite concentrate in the joint production of hydrofluoric acid, an interaction effect model for the joint production of hydrofluoric acid from multiple grades of fluorite is constructed. Based on the sales price and interaction effect model of hydrofluoric acid, an objective function for maximizing the economic benefits of hydrofluoric acid is constructed. The objective function for maximizing economic benefits was solved using a nonlinear programming algorithm to obtain the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized.

[0008] According to the aforementioned economic prediction method for the joint production of hydrofluoric acid from multi-grade fluorite, the baseline model includes the theoretical yield of hydrofluoric acid per unit of fluorite concentrate, the actual yield correction factor, the sulfuric acid consumption per unit of hydrofluoric acid production, and the comprehensive cost per unit of hydrofluoric acid production. The theoretical yield of hydrofluoric acid per unit of fluorite concentrate... The calculation method is as follows , The CaF2 content of the fluorite concentrate; the actual yield correction coefficient is a preset value determined by experiments; the sulfuric acid consumption per unit of hydrofluoric acid produced is determined based on the impurity content of the fluorite concentrate; the comprehensive cost of per unit of hydrofluoric acid production includes the fluorite concentrate purchase cost, sulfuric acid cost, energy consumption cost, and environmental protection cost.

[0009] According to the aforementioned economic prediction method for the co-production of hydrofluoric acid from multiple grades of fluorite, an interaction effect model for the co-production of hydrofluoric acid from multiple grades of fluorite concentrate is constructed based on the mixing ratio of multiple grades of fluorite concentrate and the benchmark model, including: Determine the actual yield correction factor for the mixed fluorite concentrate based on the aforementioned actual yield correction factor. for:

[0010] in, ,in The proportion of high-grade concentrate. The proportion of medium-grade concentrate. The proportion of low-grade concentrate, and ; This is the actual yield correction factor; The synergistic effect coefficient between high-grade concentrate and low-grade concentrate; The sulfuric acid consumption per unit of mixed fluorite concentrate is determined based on the sulfuric acid consumption per unit of hydrofluoric acid produced. for:

[0011] in, The amount of sulfuric acid consumed per unit of hydrofluoric acid produced; This represents the coefficient of interaction between impurities. The impurity interaction coefficient between high-grade concentrate and low-grade concentrate; Based on the actual yield correction factor of mixed fluorite concentrate Unit sulfuric acid consumption of mixed fluorite concentrate Determine the comprehensive cost of mixed fluorite concentrate. for:

[0012] in, The cost of purchasing fluorite concentrate; Cost of sulfuric acid; Energy consumption cost; This indicates the environmental treatment costs for different grades of fluorite concentrate. Determined by the total amount and types of impurities in fluorite concentrate; The theoretical yield of hydrofluoric acid produced from mixed fluorite concentrate is calculated, and ,in This indicates the CaF2 content of different fluorite concentrates.

[0013] According to the aforementioned economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite, an objective function for maximizing the economic benefits of hydrofluoric acid is constructed based on the sales price of hydrofluoric acid and an interaction effect model, including: The objective function for maximizing the economic benefits of hydrofluoric acid The calculation method is as follows:

[0014] in, ; Let be the price of hydrofluoric acid; and let be the objective function for maximizing the economic benefits of hydrofluoric acid. The impurity content of the mixed fluorite concentrate must not exceed the upper limit allowed by the process, and the preset quality requirements of hydrofluoric acid must be met.

[0015] According to the aforementioned economic prediction method for the co-production of hydrofluoric acid from multiple grades of fluorite, a nonlinear programming algorithm is used to solve the objective function for maximizing economic benefits, yielding the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized, including: This study employs a method combining sequential quadratic programming and genetic algorithms to maximize the economic benefits of hydrofluoric acid. Calculations were performed to obtain The proportion of mixed fluorite concentrate when the value is maximum According to the proportion of mixed fluorite concentrate The process involves the combined production of hydrofluoric acid from multiple grades of fluorite.

[0016] According to the aforementioned method for predicting the economic viability of multi-grade fluorite co-production of hydrofluoric acid, the method further includes: Based on fluctuations in fluorite concentrate procurement costs, sulfuric acid costs, and hydrofluoric acid prices, a dynamic optimization model is used to dynamically adjust the proportion of mixed fluorite concentrate and the unit sulfuric acid consumption of mixed fluorite concentrate.

[0017] According to the aforementioned method for predicting the economic viability of multi-grade fluorite co-production of hydrofluoric acid, the method further includes: Online detection data was obtained during the joint production of hydrofluoric acid from multiple grades of fluorite. The online detection data included CaF2 content, impurity composition, hydrofluoric acid yield, and sulfuric acid consumption. Combining online detection data with the objective function of maximizing economic benefits The difference between the predicted values ​​is calculated. If the difference exceeds a preset threshold, the objective function for maximizing economic benefits is affected. The model parameters are automatically corrected and the proportion of mixed fluorite concentrate is recalculated.

[0018] Another aspect of the present invention provides an economic prediction device for the co-production of hydrofluoric acid from multiple grades of fluorite, comprising: The first module is used to obtain the CaF2 content and impurity content of multiple grades of fluorite concentrate, and to determine the benchmark model between the hydrofluoric acid production cost and yield of each grade of fluorite concentrate based on the CaF2 content and impurity content. The second module is used to construct an interaction effect model for the joint production of hydrofluoric acid from multiple grades of fluorite concentrate based on the mixing ratio and benchmark model of multiple grades of fluorite concentrate during the joint production of hydrofluoric acid. The third module is used to construct an objective function for maximizing the economic benefits of hydrofluoric acid based on the sales price and interaction effect model of hydrofluoric acid. The fourth module is used to solve the objective function of maximizing economic benefits using a nonlinear programming algorithm, so as to obtain the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized.

[0019] Another aspect of the present invention provides an electronic device, including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method as described above.

[0020] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the methods described above.

[0021] The beneficial effects of this invention are as follows: By scientifically proportioning high and low grade fluorite concentrates, the invention maximizes the utilization of low-priced, low-grade resources while ensuring the quality of hydrofluoric acid products, thereby reducing overall raw material costs and increasing production profit margins; it enables the synergistic utilization of medium and low grade fluorite concentrates, which were previously difficult to use alone, with high grade fluorite concentrates, expanding the sources of fluorite concentrates and reducing the excessive consumption of high-quality fluorite concentrates, thus achieving tiered resource utilization; through economic model analysis, it can quickly respond to changes in the prices of different grades of fluorite concentrates, the prices of auxiliary materials such as sulfuric acid, and the prices of hydrofluoric acid products, adjusting the optimal proportions in a timely manner, dynamically adapting to the market, and maintaining the competitive advantage of production enterprises in market fluctuations; it can provide enterprises' raw material procurement departments with scientific suggestions on the procurement ratios and prices of different grades of fluorite concentrates, and provide production scheduling departments with precise raw material blending instructions, which helps to achieve full-process digital and intelligent management and decision-making. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the economic prediction process for the combined production of hydrofluoric acid from multiple grades of fluorite according to an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram of an economic prediction device for the combined production of hydrofluoric acid from multiple grades of fluorite, according to an embodiment of the present invention. Detailed Implementation

[0024] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings. Throughout the description, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions. In the following description, suffixes such as "module," "part," or "unit" used to denote elements are used only for the purpose of illustrative purposes and have no specific meaning in themselves. Therefore, "module," "part," or "unit" can be used interchangeably. Terms such as "first," "second," etc., are used only to distinguish technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the sequential relationship of the indicated technical features. In the following description, the consecutive reference numerals for method steps are for ease of review and understanding. Adjusting the implementation order of steps, in conjunction with the overall technical solution of the present invention and the logical relationship between the various steps, will not affect the technical effect achieved by the technical solution of the present invention. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0025] refer to Figure 1 , Figure 1 This is a schematic diagram of the economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to an embodiment of the present invention, which includes, but is not limited to, steps S100~S400: S100: Obtain the CaF2 content and impurity content of multiple grades of fluorite concentrate, and determine the benchmark model between the hydrofluoric acid production cost and yield of each grade of fluorite concentrate based on the CaF2 content and impurity content.

[0026] In some embodiments, the baseline model includes the theoretical yield of hydrofluoric acid per unit fluorite concentrate, the actual yield correction factor, the sulfuric acid consumption per unit of hydrofluoric acid produced, and the overall cost of producing hydrofluoric acid per unit of fluorite concentrate, wherein the theoretical yield of hydrofluoric acid per unit fluorite concentrate... The calculation method is as follows , The CaF2 content of fluorite concentrate is used; the actual yield correction factor is a preset value determined by experiments; the sulfuric acid consumption per unit of hydrofluoric acid production is determined based on the impurity content of fluorite concentrate; the comprehensive cost of per unit of hydrofluoric acid production includes the purchase cost of fluorite concentrate, sulfuric acid cost, energy consumption cost, and environmental protection cost.

[0027] In some embodiments, the high grade of fluorite concentrate includes: high grade H: CaF2≥97%, low impurities; medium grade M: CaF293%-97%, medium impurities; low grade L: CaF285-93%, high impurities.

[0028] It should be noted that in the calculation of CaF2 content... (Calcium fluoride molecular weight 78.08, hydrogen fluoride molecular weight 20.01, theoretical conversion coefficient 0.513).

[0029] The actual yield correction coefficient is lower than the theoretical value due to factors such as impurity interference and incomplete reaction, and is determined by experiments; the sulfuric acid consumption per unit of hydrofluoric acid production is affected by the content of impurities such as CaCO3 and SiO2 in fluorite concentrate.

[0030] S200, based on the mixing ratio of multiple grades of fluorite concentrate and the benchmark model in the joint production of hydrofluoric acid, constructs an interaction effect model for the joint production of hydrofluoric acid from multiple grades of fluorite.

[0031] It is understood that, in the embodiments of the present invention, when different grades of fluorite concentrate are mixed in a certain proportion, the reaction characteristics and costs are not simply a weighted average of the components, but require the introduction of an interaction effect coefficient. Therefore, the mass proportion of high-grade concentrate in the mixed fluorite concentrate is... Medium grade Low grade is ,and Then, the following steps were taken to construct an interaction effect model for the production of hydrofluoric acid from fluorite concentrate.

[0032] In some embodiments, the actual yield correction factor for mixed fluorite concentrate is determined based on the actual yield correction factor. for:

[0033] in, ,in Indicated as high-grade concentrate Medium-grade concentrate and high-grade concentrate One of them, in which The proportion of high-grade concentrate. The proportion of medium-grade concentrate. The proportion of low-grade concentrate, and ; This is the actual yield correction factor; Let be the synergistic effect coefficient between high-grade and low-grade fluorite concentrates. For example, if high-grade fluorite concentrate can promote the exposure and reaction of fluorite in low-grade fluorite concentrate, then... If the impurities in the fluorite concentrate interact and have an inhibitory effect, then Experimental design for producing hydrofluoric acid by mixing fluorite concentrate in different proportions was used to determine... value.

[0034] The unit sulfuric acid consumption of mixed fluorite concentrate is determined based on the sulfuric acid consumption per unit of hydrofluoric acid production. for:

[0035] in, The amount of sulfuric acid consumed per unit of hydrofluoric acid produced; Let be the impurity interaction coefficient. For example, if high-grade fluorite concentrate has a "dilution" and "buffering" effect on acidic impurities in low-grade fluorite concentrate, thus reducing overall sulfuric acid consumption, then... ; This represents the interaction coefficient of impurities between high-grade and low-grade concentrates.

[0036] Based on the actual yield correction factor of mixed fluorite concentrate Unit sulfuric acid consumption of mixed fluorite concentrate Determine the comprehensive cost of mixed fluorite concentrate. for:

[0037] in, The cost of purchasing fluorite concentrate; Cost of sulfuric acid; Energy consumption cost; This indicates the environmental treatment costs for different grades of fluorite concentrate. Determined by the total amount and types of impurities in fluorite concentrate; The theoretical yield of hydrofluoric acid produced from mixed fluorite concentrate is calculated, and ,in This indicates the CaF2 content of different fluorite concentrates.

[0038] S300, based on the sales price and interaction effect model of hydrofluoric acid, constructs an objective function to maximize the economic benefits of hydrofluoric acid.

[0039] In some embodiments, the objective function for maximizing the economic benefits of hydrofluoric acid is... The calculation method is as follows:

[0040] in, ; Let be the price of hydrofluoric acid; and let be the objective function for maximizing the economic benefits of hydrofluoric acid. The impurity content of the mixed fluorite concentrate must not exceed the upper limit allowed by the process (such as CaCO3, SiO2), and must meet the preset quality requirements of hydrofluoric acid (such as heavy metal content, acidity, etc.).

[0041] in, The selling price of hydrofluoric acid is given (which can be graded according to product quality, such as industrial grade and electronic grade). If the quality of hydrofluoric acid produced from mixed fluorite concentrate falls between different grades, a correlation model between product quality and proportion needs to be established, along with a corresponding price function.

[0042] S400 uses a nonlinear programming algorithm to solve the objective function of maximizing economic benefits, and obtains the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized.

[0043] In some embodiments, a method for maximizing the economic benefits of hydrofluoric acid, employing a sequential quadratic programming or genetic algorithm, is used. Calculations were performed to obtain The proportion of mixed fluorite concentrate when the value is maximum According to the proportion of mixed fluorite concentrate The process involves the combined production of hydrofluoric acid from multiple grades of fluorite.

[0044] In some embodiments, the proportion of mixed fluorite concentrate and the unit sulfuric acid consumption of mixed fluorite concentrate are dynamically adjusted through a dynamic optimization model based on fluctuations in the procurement cost of fluorite concentrate, sulfuric acid cost, and hydrofluoric acid price.

[0045] For example, when the price of high-grade concentrate rises, the model automatically decreases. The model tends to increase the proportion of low- and medium-grade sulfuric acid when sulfuric acid prices rise, and to increase the proportion of high-grade sulfuric acid when prices rise to reduce the proportion of low-grade sulfuric acid. When the price of hydrofluoric acid products falls, the model prioritizes using low-cost raw materials to maintain a small profit.

[0046] In some embodiments, online detection data is acquired during the co-production of hydrofluoric acid from multiple grades of fluorite. This online detection data includes CaF2 content, impurity composition, hydrofluoric acid yield, and sulfuric acid consumption. The online detection data is then compared with an objective function that maximizes economic benefits. The difference between the predicted values ​​is calculated. If the difference exceeds a preset threshold, the objective function for maximizing economic benefits is affected. The model parameters are automatically corrected and the proportion of mixed fluorite concentrate is recalculated.

[0047] In some embodiments, the model parameters include Through the technical solutions of the embodiments of the present invention, online feedback and adaptive adjustment of the hydrofluoric acid production process are realized.

[0048] For example, taking a hydrofluoric acid production enterprise as an example, the specific application of the method of the present invention is illustrated as follows: (1) Basic data collection: A hydrofluoric acid production enterprise can purchase three types of fluorite concentrate. High grade H: CaF2 98.5%, CaCO3 0.8%, SiO2 0.5%, purchase price 3200 yuan / ton; Medium grade M: CaF2 94.0%, CaCO3 2.5%, SiO2 1.8%, purchase price 2600 yuan / ton; Low grade L: CaF2 88.0%, CaCO3 5.0%, SiO2 3.5%, purchase price 2000 yuan / ton.

[0049] (2) Hydrofluoric acid production test of single-grade fluorite concentrate: Production parameters for hydrofluoric acid production from each grade of fluorite concentrate were determined through laboratory small-scale reactor experiments. High grade H: Actual yield coefficient sulfuric acid consumption Environmental costs per ton of HF Yuan / ton HF; Medium grade M: , tons / ton HF, Yuan / ton HF; Low grade L: , tons / ton HF, Yuan / ton of HF. In addition, fixed costs... Price of HF per ton, sulfuric acid Price of hydrofluoric acid per ton Yuan / ton (industrial grade).

[0050] (3) Experiments were conducted to prepare hydrofluoric acid from fluorite concentrates of different grades to determine the interaction effect. Different ratios of fluorite concentrates of different grades were mixed to carry out hydrofluoric acid preparation experiments, and the interaction coefficient was measured. It was found that when the proportion of high-grade fluorite concentrate was 30-50%, the reaction efficiency of low-grade concentrate was significantly improved. When high- and low-grade fluorite concentrates are mixed to prepare hydrofluoric acid, it has a synergistic effect in reducing sulfuric acid consumption. .

[0051] (4) Construct an economic analysis model for preparing hydrofluoric acid from different grades of fluorite and solve for the optimal ratio. Substitute the data obtained above into the objective function and use a genetic algorithm to solve for the optimal ratio: , , .at this time: Theoretical yield of mixed fluorite concentrate ton HF / ton concentrate; Actual yield correction factor ; Actual yield = 0.476 × 0.941 = 0.448 tons of HF / ton of concentrate; Comprehensive procurement cost of mixed fluorite concentrate Yuan / ton; Cost of raw materials per ton of HF = 2710 / 0.448 = 6050 yuan; Sulfuric acid consumption during the preparation of hydrofluoric acid from mixed fluorite concentrate tons / ton HF; The cost of sulfuric acid is 2.41 × 500 = 1205 yuan; Environmental costs Yuan; Total cost Yuan / ton HF; profit Yuan / ton HF (slight loss).

[0052] (5) Sensitivity analysis of the economic benefit model and dynamic adjustment and optimization of production parameters: The current optimal ratio still results in a slight loss, requiring further optimization. Sensitivity analysis revealed that if the purchase price of low-grade fluorite concentrate could be reduced to 1800 yuan / ton (e.g., through a long-term contract), then: after the new ratio optimization... The total cost was reduced to 10,420 yuan / ton of HF, resulting in a profit of 80 yuan / ton of HF. If the price of sulfuric acid rises to 600 yuan / ton, the economic benefit model will automatically increase the proportion of high-grade sulfuric acid. This is to reduce sulfuric acid consumption and maintain a small profit.

[0053] Figure 2 This is a schematic diagram of an economic prediction device for the combined production of hydrofluoric acid from multiple grades of fluorite according to an embodiment of the present invention. The device includes a first module 210, a second module 220, a third module 230, and a fourth module 240.

[0054] The system comprises four modules: The first module obtains the CaF2 and impurity contents of multiple grades of fluorite concentrate and determines a benchmark model for the hydrofluoric acid production cost and yield of each grade based on these contents; the second module constructs an interaction effect model for the joint production of hydrofluoric acid from multiple grades of fluorite concentrate, based on the mixing ratio of these grades and the benchmark model; the third module constructs an objective function for maximizing the economic benefits of hydrofluoric acid, based on the sales price and the interaction effect model; and the fourth module solves the objective function using a nonlinear programming algorithm to obtain the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized.

[0055] For example, with the cooperation of the first, second, third, and fourth modules in the device, the embodiment device can implement any of the aforementioned methods for predicting the economic benefits of multi-grade fluorite co-production of hydrofluoric acid. Specifically, it involves obtaining the CaF2 content and impurity content of multiple grades of fluorite concentrate; determining a benchmark model between the hydrofluoric acid production cost and yield of each grade of fluorite concentrate based on the CaF2 and impurity content; constructing an interaction effect model for multi-grade fluorite co-production of hydrofluoric acid based on the mixing ratio of multiple grades of fluorite concentrate and the benchmark model; constructing an objective function for maximizing the economic benefits of hydrofluoric acid based on the sales price of hydrofluoric acid and the interaction effect model; and solving the objective function for maximizing economic benefits using a nonlinear programming algorithm to obtain the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized. The beneficial effects of this invention are as follows: By scientifically proportioning high and low grade fluorite concentrates, the invention maximizes the utilization of low-priced, low-grade resources while ensuring the quality of hydrofluoric acid products, thereby reducing overall raw material costs and increasing production profit margins; it enables the synergistic utilization of medium and low grade fluorite concentrates, which were previously difficult to use alone, with high grade fluorite concentrates, expanding the sources of fluorite concentrates and reducing the excessive consumption of high-quality fluorite concentrates, thus achieving tiered resource utilization; through economic model analysis, it can quickly respond to changes in the prices of different grades of fluorite concentrates, the prices of auxiliary materials such as sulfuric acid, and the prices of hydrofluoric acid products, adjusting the optimal proportions in a timely manner, dynamically adapting to the market, and maintaining the competitive advantage of production enterprises in market fluctuations; it can provide enterprises' raw material procurement departments with scientific suggestions on the procurement ratios and prices of different grades of fluorite concentrates, and provide production scheduling departments with precise raw material blending instructions, which helps to achieve full-process digital and intelligent management and decision-making.

[0056] This invention also provides an electronic device, which includes a processor and a memory; The memory stores the program; The processor executes a program to perform the aforementioned economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite; the electronic device has the function of carrying and running the software system for economic prediction of the co-production of hydrofluoric acid from multi-grade fluorite provided in the embodiments of the present invention, such as a personal computer, minicomputer, mainframe, workstation, network or distributed computing environment, standalone or integrated computer platform, or communicating with charged particle tools or other imaging devices, etc.

[0057] This invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement the economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite as described above.

[0058] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented in the embodiments of this invention. Alternative embodiments are contemplated, in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0059] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned method for predicting the economics of multi-grade fluorite co-production of hydrofluoric acid.

[0060] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the described functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, considering the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed in the embodiments of the invention, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0061] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0062] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can include, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0063] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0064] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0065] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0066] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0067] The above is a detailed description of the preferred embodiments of the present invention, but the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. An economic prediction method for the co-production of hydrofluoric acid from multiple grades of fluorite, characterized in that, include: The CaF2 content and impurity content of multiple grades of fluorite concentrate were obtained, and a benchmark model between the hydrofluoric acid production cost and yield of each grade of fluorite concentrate was determined based on the CaF2 content and impurity content. Based on the mixing ratio and benchmark model of multiple grades of fluorite concentrate in the joint production of hydrofluoric acid, an interaction effect model for the joint production of hydrofluoric acid from multiple grades of fluorite is constructed. Based on the sales price and interaction effect model of hydrofluoric acid, an objective function for maximizing the economic benefits of hydrofluoric acid is constructed. The objective function for maximizing economic benefits was solved using a nonlinear programming algorithm to obtain the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized.

2. The economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to claim 1, characterized in that, The benchmark model includes the theoretical yield of hydrofluoric acid per unit of fluorite concentrate, the actual yield correction factor, the sulfuric acid consumption per unit of hydrofluoric acid produced, and the comprehensive cost of producing hydrofluoric acid per unit of fluorite concentrate. The theoretical yield of hydrofluoric acid per unit of fluorite concentrate is... The calculation method is as follows , The CaF2 content of the fluorite concentrate; the actual yield correction coefficient is a preset value determined by experiments; the sulfuric acid consumption per unit of hydrofluoric acid produced is determined based on the impurity content of the fluorite concentrate; the comprehensive cost of per unit of hydrofluoric acid production includes the fluorite concentrate purchase cost, sulfuric acid cost, energy consumption cost, and environmental protection cost.

3. The economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to claim 2, characterized in that, The interaction effect model for the co-production of hydrofluoric acid from multiple grades of fluorite concentrate, based on the mixing ratio and benchmark model of multiple grades of fluorite concentrate, is constructed, including: Determine the actual yield correction factor for the mixed fluorite concentrate based on the aforementioned actual yield correction factor. for: in, ,in The proportion of high-grade concentrate. The proportion of medium-grade concentrate. The proportion of low-grade concentrate, and ; This is the actual yield correction factor; The synergistic effect coefficient between high-grade concentrate and low-grade concentrate; The sulfuric acid consumption per unit of mixed fluorite concentrate is determined based on the sulfuric acid consumption per unit of hydrofluoric acid produced. for: in, The amount of sulfuric acid consumed per unit of hydrofluoric acid produced; This represents the coefficient of interaction between impurities. The impurity interaction coefficient between high-grade concentrate and low-grade concentrate; Based on the actual yield correction factor of mixed fluorite concentrate Unit sulfuric acid consumption of mixed fluorite concentrate Determine the comprehensive cost of mixed fluorite concentrate. for: in, The cost of purchasing fluorite concentrate; Cost of sulfuric acid; Energy consumption cost; This indicates the environmental treatment costs for different grades of fluorite concentrate. Determined by the total amount and types of impurities in fluorite concentrate; The theoretical yield of hydrofluoric acid produced from mixed fluorite concentrate is calculated, and ,in This indicates the CaF2 content of different fluorite concentrates.

4. The economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to claim 3, characterized in that, The objective function for maximizing the economic benefits of hydrofluoric acid, based on the sales price and interaction effect model, includes: The objective function for maximizing the economic benefits of hydrofluoric acid The calculation method is as follows: in, ; Let be the price of hydrofluoric acid; and let be the objective function for maximizing the economic benefits of hydrofluoric acid. The impurity content of the mixed fluorite concentrate must not exceed the upper limit allowed by the process, and the preset quality requirements of hydrofluoric acid must be met.

5. The economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to claim 4, characterized in that, The objective function for maximizing economic benefits is solved using a nonlinear programming algorithm to obtain the mixing ratios of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized, including: This study employs a method combining sequential quadratic programming and genetic algorithms to maximize the economic benefits of hydrofluoric acid. Calculations were performed to obtain The proportion of mixed fluorite concentrate when the value is maximum According to the proportion of mixed fluorite concentrate The process involves the combined production of hydrofluoric acid from multiple grades of fluorite.

6. The economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to claim 5, characterized in that, The method further includes: Based on fluctuations in fluorite concentrate procurement costs, sulfuric acid costs, and hydrofluoric acid prices, a dynamic optimization model is used to dynamically adjust the proportion of mixed fluorite concentrate and the unit sulfuric acid consumption of mixed fluorite concentrate.

7. The economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite according to claim 5, characterized in that, The method further includes: Online detection data was obtained during the joint production of hydrofluoric acid from multiple grades of fluorite. The online detection data included CaF2 content, impurity composition, hydrofluoric acid yield, and sulfuric acid consumption. Combining online detection data with the objective function of maximizing economic benefits The difference between the predicted values ​​is calculated. If the difference exceeds a preset threshold, the objective function for maximizing economic benefits is affected. The model parameters are automatically corrected and the proportion of mixed fluorite concentrate is recalculated.

8. An economic prediction device for the co-production of hydrofluoric acid from multiple grades of fluorite, characterized in that, include: The first module is used to obtain the CaF2 content and impurity content of multiple grades of fluorite concentrate, and to determine the benchmark model between the hydrofluoric acid production cost and yield of each grade of fluorite concentrate based on the CaF2 content and impurity content. The second module is used to construct an interaction effect model for the joint production of hydrofluoric acid from multiple grades of fluorite concentrate based on the mixing ratio and benchmark model of multiple grades of fluorite concentrate during the joint production of hydrofluoric acid. The third module is used to construct an objective function for maximizing the economic benefits of hydrofluoric acid based on the sales price and interaction effect model of hydrofluoric acid. The fourth module is used to solve the objective function of maximizing economic benefits using a nonlinear programming algorithm, so as to obtain the mixing ratio of multiple grades of fluorite concentrate when the economic benefits of hydrofluoric acid are maximized.

9. An electronic device, characterized in that, Including the processor and memory; The memory is used to store programs; The processor executes the program to implement the economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a program that is executed by a processor to implement the economic prediction method for the co-production of hydrofluoric acid from multi-grade fluorite as described in any one of claims 1-7.

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