A method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics and related equipment.

Abstract

A method and related equipment for constructing a multi-stage flash evaporation model based on self-evaporation characteristics are disclosed, relating to the field of flash evaporator modeling technology. This method establishes a consistent flash evaporation model for the flash evaporator based on the principle of material balance, and cascades these consistent flash evaporation models based on a preset number of flash evaporation stages to obtain a multi-stage consistent flash evaporation model. A simplified function is constructed to ignore volume changes caused by mixing solutions of different densities. A relational function is constructed, in which the amount of water evaporated is positively correlated with the pressure drop and negatively correlated with the density of the feed liquid. The multi-stage consistent flash evaporation model, the simplified function, and the relational function are combined to obtain the multi-stage flash evaporation model. The multi-stage flash evaporation model is then output, allowing industrial sites to refer to it to regulate the flash evaporation process, accurately describe the self-evaporation behavior of the feed liquid within each stage of the flash evaporator, precisely reflect the dynamic characteristics of the multi-stage flash evaporation process, improve the accuracy of the multi-stage flash evaporation model, and provide a reliable decision-making basis for optimized control in industrial settings.

Description

Technical Field

[0001] This application relates to the field of flash evaporator flash model technology, and in particular to a method and related equipment for constructing a multi-stage flash evaporation model based on self-evaporation characteristics. Background Technology

[0002] Flash evaporation is a unit operation that concentrates a solution by partially vaporizing a superheated liquid through the pressure reduction effect of a throttling valve. This operation is widely used in non-ferrous metallurgy, chemical industry, energy utilization, food and other fields.

[0003] Flash evaporation models can accurately reflect the dynamic characteristics of the liquid in the flash evaporator, laying the foundation for the optimized control of the flash evaporation process.

[0004] However, in some factories, in order to save production costs, improve energy efficiency, and ensure product quality, industrial sites often adopt multi-stage flash evaporation processes consisting of multiple flash evaporators connected in series (see reference). Figure 2 Each flash evaporator depressurizes the feed liquid through a throttling valve, lowering its boiling point. This results in a feed liquid temperature higher than its boiling point after depressurization, transforming it into a superheated liquid. The superheated liquid then rapidly vaporizes in the separation chamber, undergoing gas-liquid separation to concentrate the feed liquid. The separated steam can be used to heat other processes for energy reuse, while the separated liquid is discharged to the next flash evaporator for further concentration.

[0005] However, the relevant technologies all establish a consistent model of a single flash evaporator and obtain a consistent cascade model of the multi-stage flash evaporation process by connecting them in series. Therefore, there is no flash evaporation model that can accurately reflect the self-evaporation characteristics of the liquid in each flash evaporator in a multi-stage flash evaporator.

[0006] In a multi-stage flash evaporator, the flash feed liquid enters from the first-stage flash evaporator, passes through the second, third, and fourth-stage flash evaporators sequentially, and exits from the fifth-stage flash evaporator. Along the flow direction of the feed liquid, the density increases, the temperature decreases, and the pressure in each flash evaporator decreases progressively. Therefore, the density, water volume, saturation temperature, and steam chamber pressure—states closely related to flash self-evaporation—differ at each stage of the flash evaporation process. This leads to individual differences in the self-evaporation state of each flash evaporator. However, the consistent flash cascade model in related technologies cannot accurately reflect the self-evaporation phenomenon within each flash evaporator, and thus cannot accurately describe the input-output relationship of the flash process. This may result in significant deviations between model predictions and actual conditions, affecting the reliability of decisions based on the consistent model, and even leading to resource waste, production instability, and system failures. Summary of the Invention

[0007] This application provides a method and related equipment for constructing a multi-stage flash evaporation model based on self-evaporation characteristics. This method accurately describes the self-evaporation behavior of the liquid in each stage of the flash evaporator, precisely reflects the dynamic characteristics of the multi-stage flash evaporation process, improves the accuracy of the multi-stage flash evaporation model, and provides a reliable decision-making basis for the optimized control of industrial sites.

[0008] Firstly, this application provides a method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics, including:

[0009] A consistent flash evaporation model for the flash evaporator is established based on the principle of material balance, and a multi-stage consistent flash evaporation model is obtained by cascading the consistent flash evaporation model based on the preset number of flash evaporation levels.

[0010] Construct a simplified function that ignores volume changes caused by mixing solutions of different densities;

[0011] Construct a relational function in which the amount of water evaporated is positively correlated with the pressure drop and negatively correlated with the density of the liquid.

[0012] The multi-stage flash evaporation model is obtained by simultaneously combining the multi-stage consistent flash evaporation model, the simplified function, and the relational function.

[0013] Output a multi-stage flash evaporation model, enabling industrial sites to control the flash evaporation process by referring to the multi-stage flash evaporation model.

[0014] In the above embodiments, a quantitative relationship was established by constructing a relational function, clarifying that the water vapor volume is positively correlated with the pressure drop and negatively correlated with the feed liquid density. This relational function fully considers the differences in the self-evaporation state of each stage of the flash evaporator during the multi-stage flash evaporation process, accurately describing the self-evaporation behavior of the feed liquid in each stage of the flash evaporator and precisely reflecting the dynamic characteristics of the multi-stage flash evaporation process. Based on this relational function, a refined description and prediction of the multi-stage flash evaporation process can be achieved, providing a reliable decision-making basis for the optimized control in industrial settings. Furthermore, a simplified function was constructed to ignore the volume changes caused by mixing solutions of different densities, which can reduce computational complexity and improve the practicality of the model while ensuring its accuracy.

[0015] In conjunction with some embodiments of the first aspect, in some embodiments, the step of constructing a relational function in which the amount of water evaporated is positively correlated with the pressure drop and negatively correlated with the density of the liquid feed specifically includes:

[0016] Construct a relational function in which the water distillation rate is the ratio of the product of pressure drop and pressure drop factor to the product of the density of the liquid and the density factor of the liquid.

[0017] In the above embodiments, the steaming rate is expressed as the ratio of the product of pressure drop and pressure drop factor to the product of liquid density and liquid density factor. This quantitatively describes the influence of pressure drop and liquid density on the steaming rate, reflecting the correlation between them. This representation can more accurately reflect the intrinsic relationship between various influencing factors in the multi-stage flash evaporation process. By reasonably setting the values ​​of pressure drop factor and liquid density factor, the weights of pressure drop and liquid density in the relationship function can be flexibly adjusted, enabling the model to more accurately reflect the actual multi-stage flash evaporation process.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after obtaining the multi-level flash model by simultaneously establishing the multi-level consistent flash model, the simplification function, and the relational function, the method further includes:

[0019] Within a preset number of iterations, adjust the values ​​of all pressure drop factors and liquid density factors, and obtain the difference between the simulated data calculated by the multi-stage flash evaporation model and the actual data.

[0020] Determine the values ​​of all pressure drop factors and feed density factors when the differences are minimal.

[0021] In the above embodiments, by adjusting the values ​​of the pressure drop factor and the feed density factor within a preset number of iterations and comparing the differences between the model calculation results and the actual data, dynamic optimization of the multi-stage flash evaporation model parameters is achieved. This iterative optimization method can adaptively search for the optimal combination of model parameters, making the simulation results of the model as close as possible to the actual situation, reaching the global optimum. This iterative optimization process can improve the accuracy of the multi-stage flash evaporation model, enabling it to more accurately reflect / describe the behavior of the feed liquid during the flash evaporation process.

[0022] In conjunction with some embodiments of the first aspect, in some embodiments, the step of constructing a relational function in which the amount of water evaporated is positively correlated with the pressure drop and negatively correlated with the density of the liquid feed specifically includes:

[0023] Construct a relational function where the amount of water evaporated is the ratio of the pressure drop function to the density function of the liquid. The pressure drop function is determined by multiplying the pressure drop by the pressure drop coefficient and adding a pressure drop constant to the product. The density function of the liquid is determined by multiplying the density of the liquid by the density coefficient of the liquid and adding a density constant to the product.

[0024] In the above embodiments, adding a constant term to the original pressure drop coefficient and liquid density coefficient allows for fine-tuning of the output results of the pressure drop function and liquid density function without changing the overall form of the function. This fine-tuning can compensate for errors caused by model simplification and parameter estimation, enabling the relationship function to more accurately describe the relationship between water distillation, pressure drop, and liquid density during multi-stage flash evaporation.

[0025] In conjunction with some embodiments of the first aspect, in some embodiments, after obtaining the multi-level flash model by simultaneously establishing the multi-level consistent flash model, the simplification function, and the relational function, the method further includes:

[0026] Within a preset number of iterations, adjust the values ​​of all pressure drop coefficients, pressure drop constants, liquid density coefficients, and liquid density constants, and obtain the difference between the simulated data calculated by the multi-stage flash evaporation model and the actual data;

[0027] Determine the values ​​of all pressure drop coefficients, pressure drop constants, liquid density coefficients, and liquid density constants when the differences are minimal.

[0028] In the above embodiments, by adjusting the values ​​of pressure drop coefficient, pressure drop constant, liquid density coefficient, and liquid density constant within a preset number of iterations, and comparing the differences between the model calculation results and actual data, the parameters in the relational function are optimized. Compared with optimizing a single type of parameter, this comprehensive optimization method can search for the optimal parameter combination in a larger parameter space, fully considering the mutual influence and constraint relationships between the parameters, minimizing the difference between the model's simulation results and actual data, achieving overall optimization, and improving the accuracy of the multi-stage flash evaporation model.

[0029] In conjunction with some embodiments of the first aspect, in some embodiments, the step of establishing a consistent flash evaporation model for the flash evaporator based on the material balance principle specifically includes:

[0030] Based on the feed volume, inlet feed mass flow rate, outlet feed mass flow rate, and distillation water volume, a balance equation is constructed as follows:

[0031]

[0032] In the formula, M i S The volume of liquid in the i-th stage flash evaporator. Let be the inlet liquid mass flow rate of the i-th stage flash evaporator. Let be the mass flow rate of the liquid feed at the outlet of the i-th stage flash evaporator. The amount of water evaporated in the i-th stage flash evaporator;

[0033] Construct analytical equations for the feed volume, inlet feed mass flow rate, and outlet feed mass flow rate. The analytical equations are as follows:

[0034]

[0035] In the formula, The volume of liquid in the i-th stage flash evaporator. Let be the feed liquid density of the i-th stage flash evaporator. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let i be the liquid level of the i-th stage flash evaporator. Let be the inlet liquid mass flow rate of the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. Let be the mass flow rate of the liquid feed at the outlet of the i-th stage flash evaporator. Let i be the outlet liquid volume flow rate of the i-th stage flash evaporator;

[0036] Combining the analytical equations and the equilibrium equations, we obtain the uniform flash evaporation model, which is as follows:

[0037]

[0038] In the formula, in the formula, Let be the feed liquid density of the i-th stage flash evaporator, and t be the time. Let i be the liquid level of the i-th stage flash evaporator. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. V is the outlet liquid volume flow rate of the i-th stage flash evaporator. i S The amount of water evaporated in the i-th stage flash evaporator.

[0039] In the above embodiments, the balance equation, based on the law of conservation of mass, accurately describes the dynamic balance relationship of materials within the multi-stage flash evaporator. By introducing the feed liquid volume, the real-time changes in material inventory within the flash evaporator can be reflected; the inlet and outlet feed liquid mass flow rates reflect the material input and output processes; and the introduction of the water distillation rate considers the impact of the flash evaporation process on the material balance. The analytical equation introduces key parameters such as feed liquid density, effective cross-sectional area of ​​the flash evaporator, liquid level, and feed liquid volumetric flow rate to describe the material characteristics of the multi-stage flash evaporation process. Specifically, the introduction of feed liquid density and liquid level reflects the influence of feed liquid properties and flash evaporator geometry on material inventory; the inlet feed liquid density and volumetric flow rate determine the material input rate; and the outlet feed liquid volumetric flow rate reflects the material output process.

[0040] In conjunction with some embodiments of the first aspect, in some embodiments, the simplified function is:

[0041]

[0042] In the formula, Let t be the liquid level of the i-th stage flash evaporator, and t be the time. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. V is the outlet liquid volume flow rate of the i-th stage flash evaporator. i S Let ρ be the steam volume of the i-th stage flash evaporator. w The density of water;

[0043] The multi-stage flash evaporation model is as follows:

[0044]

[0045] In the formula, Let be the feed liquid density of the i-th stage flash evaporator, and t be the time. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let i be the liquid level of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. Let the outlet liquid density of the i-th stage flash evaporator be . Let be the pressure drop of the i-th stage flash evaporator. Let be the pressure drop coefficient of the i-th stage flash evaporator. Let be the pressure drop constant of the i-th stage flash evaporator. Let be the density coefficient of the liquid feed in the i-th stage flash evaporator. The feed density constant of the i-th stage flash evaporator, ρ w This is the density of water.

[0046] In the above embodiments, a simplification process of ignoring the density difference of the feed liquid is further introduced based on the consistent flash evaporation model. Considering that the feed liquid density may differ between different stages of the flash evaporator, directly using these feed liquid volumetric flow rates for material balance calculations may introduce errors. To simplify the model complexity and improve computational efficiency, the volume change caused by this density difference is appropriately ignored during the modeling process. Although this simplification sacrifices some accuracy, it highlights the main research problem of the model, making the material balance relationship clearer and easier to solve. Through reasonable simplification assumptions, the computational load and time cost can be greatly reduced while ensuring the practicality of the model.

[0047] Secondly, embodiments of this application provide a multi-stage flash evaporation model construction system based on self-evaporation characteristics, the system comprising: one or more processors and a memory;

[0048] The memory is coupled to the one or more processors and is used to store computer program code, which includes computer instructions that the one or more processors call to cause the multi-stage flash evaporation model construction system based on self-evaporation characteristics to perform the methods described in the first aspect and any possible implementation thereof.

[0049] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a server, cause the server to perform the method described in the first aspect and any possible implementation thereof.

[0050] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a multi-stage flash evaporation model construction system based on self-evaporation characteristics, cause the multi-stage flash evaporation model construction system based on self-evaporation characteristics to perform the method described in the first aspect and any possible implementation thereof.

[0051] Understandably, the multi-stage flash evaporation model construction system based on self-evaporation characteristics provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the multi-stage flash evaporation model construction method based on self-evaporation characteristics provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0052] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0053] 1. The multi-stage flash evaporation model construction method based on self-evaporation characteristics provided in this application expresses the amount of water evaporated as the ratio of the product of pressure drop and pressure drop factor to the product of liquid density and liquid density factor. This quantitatively describes the influence of pressure drop and liquid density on the amount of water evaporated, reflecting the correlation between them. This representation can more accurately reflect the intrinsic relationship between various influencing factors in the multi-stage flash evaporation process. By reasonably setting the values ​​of pressure drop factor and liquid density factor, the weights of pressure drop and liquid density in the relationship function can be flexibly adjusted, enabling the model to more accurately reflect the actual multi-stage flash evaporation process.

[0054] 2. The multi-stage flash evaporation model construction method based on self-evaporation characteristics provided in this application achieves dynamic optimization of the multi-stage flash evaporation model parameters by adjusting the values ​​of the pressure drop factor and the feed density factor within a preset number of iterations and comparing the differences between the model calculation results and actual data. This iterative optimization method can adaptively search for the optimal combination of model parameters, making the simulation results of the model as close as possible to the actual situation and reaching the global optimum. This iterative optimization process can improve the accuracy of the multi-stage flash evaporation model, enabling it to more accurately reflect / describe the behavior of the feed liquid during the flash evaporation process.

[0055] 3. The multi-stage flash evaporation model construction method based on self-evaporation characteristics provided in this application optimizes various parameters in the relational function by adjusting the values ​​of pressure drop coefficient, pressure drop constant, feed liquid density coefficient, and feed liquid density constant within a preset number of iterations and comparing the differences between the model calculation results and actual data. Compared with optimizing a single type of parameter, this comprehensive optimization method can search for the optimal parameter combination in a larger parameter space, fully considering the mutual influence and constraint relationships between various parameters, minimizing the difference between the model simulation results and actual data, achieving overall optimization, and improving the accuracy of the multi-stage flash evaporation model. Attached Figure Description

[0056] Figure 1 A flowchart illustrating the method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0057] Figure 2 A schematic diagram of the five-stage flash evaporation process provided in this application.

[0058] Figure 3 The working principle diagram of the flash evaporator provided in this application.

[0059] Figure 4 A comparative diagram showing the construction of relevant multi-stage flash evaporation models and the multi-stage flash evaporation model provided in this application.

[0060] Figure 5 This is a schematic diagram of a lower-level process for constructing a multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0061] Figure 6 This is another lower-level process diagram illustrating the method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0062] Figure 7 A schematic diagram of the physical device for constructing a multi-stage flash evaporation model system based on self-evaporation characteristics provided in this application. Detailed Implementation

[0063] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0064] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0065] To facilitate understanding, the technical terms used in the text will be explained below:

[0066] 1. Self-evaporation characteristic: Self-evaporation refers to the phenomenon where a liquid partially flashes into vapor due to a sudden drop in pressure. When a liquid is pumped or flows through a throttling device (such as a valve or orifice plate), the liquid pressure drops suddenly, and a portion of the liquid spontaneously flashes into vapor. This phenomenon typically occurs in hot liquids, such as water or other process fluids under high temperature and pressure.

[0067] 2. Multistage Flash Evaporator: A multistage flash evaporator is a device that utilizes the principle of self-evaporation for liquid flashing and condensation. It consists of multiple flash chambers connected in series, with the pressure in each chamber decreasing sequentially. High-temperature, high-pressure liquid first enters the first-stage flash chamber; due to the sudden pressure drop, some of the liquid evaporates into vapor. The remaining liquid enters the next-stage flash chamber, where, due to the further pressure reduction, self-evaporation occurs again. This process is repeated sequentially in each stage of the flash chamber until the final stage.

[0068] To facilitate understanding, the following will explain the application scenarios of the multi-stage flash evaporation model construction method based on self-evaporation characteristics provided in this application, as well as the shortcomings of related models in these scenarios.

[0069] This factory needs to utilize a multi-stage flash evaporation model to regulate the pressure of the flash evaporator. The common practice is to select the discharge density of a specific flash evaporator (obtained through model calculations) as the control target and adjust the flash evaporator pressure based on its deviation from the theoretical value. However, related technologies typically establish consistent models for individual flash evaporators, which are then connected in series to obtain a consistent cascade model for the multi-stage flash evaporation process. Therefore, control based on this model is difficult to precisely manage on-site, leading to increased energy consumption and even waste or inefficient use of resources and energy (electrical, chemical, or thermal energy, as well as the flash evaporation device). This can range from increasing production costs to damaging the flash evaporation equipment and even posing safety hazards.

[0070] To facilitate understanding, the reasons for the aforementioned defects will be further explained below.

[0071] Taking a five-stage flash process as an example (reference) Figure 2The raw liquid enters the first-stage flash evaporator, where a sudden pressure drop causes some of the liquid to evaporate into steam. The remaining liquid enters the next-stage flash evaporator, where a further pressure drop causes it to evaporate again. This process is repeated sequentially in each stage of the flash evaporator until the fifth-stage flash evaporator. For liquids, the flash evaporation raw liquid enters the first-stage flash evaporator, passes through the second, third, and fourth stages, and exits at the fifth stage.

[0072] However, in a multi-stage flash evaporator, the density of the liquid increases progressively along the flow direction, the temperature decreases progressively, and the pressure of each flash evaporator also decreases progressively. Therefore, the density of the liquid, the amount of water evaporated, the saturation temperature, and the pressure in the steam chamber, which are closely related to flash self-evaporation, are different in each stage of the flash process. This leads to individual differences in the self-evaporation state of each stage of the flash evaporator.

[0073] Taking the outlet liquid density of the fifth-stage flash evaporator as an example, this paper illustrates the problems existing in relevant multi-stage flash evaporation models. In actual multi-stage flash evaporation processes, there is a sequential series relationship between each stage: the high-temperature, high-pressure feed liquid first enters the first-stage flash evaporator, the liquid exiting the first stage then enters the second-stage flash evaporator, the liquid exiting the second stage enters the third-stage flash evaporator, and so on, until the liquid exiting the fourth stage enters the fifth-stage flash evaporator. However, relevant models usually directly use the feed liquid as the feed to each stage of the flash evaporator, ignoring the cascading transfer process in the intermediate stages; therefore, the flash cascade models in related technologies cannot accurately reflect the self-evaporation phenomenon within each stage of the flash evaporator, and thus cannot accurately describe the input-output relationship of the flash evaporation process. This may lead to a large deviation between the model prediction results and the actual situation, thereby affecting the reliability of decisions made based on the model, and even causing problems such as resource waste, production instability, and system failures.

[0074] The application scenarios, defects, and problems of the multi-stage flash evaporation model construction method based on self-evaporation characteristics have been described and derived above. The following describes the multi-stage flash evaporation model construction method based on self-evaporation characteristics in this embodiment:

[0075] like Figure 1 As shown, Figure 1 A flowchart illustrating the method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0076] S101. Establish a consistent flash evaporation model for the flash evaporator based on the principle of material balance, and obtain a multi-level consistent flash evaporation model by cascading the consistent flash evaporation model based on the preset number of flash evaporation levels.

[0077] It is worth noting that the preset number of flash stages refers to the number of flash evaporators in a multi-stage flash system, which is commonly referred to as the "stage".

[0078] In multi-stage flash evaporation, each flash evaporator follows the principle of material balance, meaning the total amount of material entering the flash evaporator equals the total amount of material leaving the flash evaporator. Based on this principle, a mathematical model of a single-stage flash evaporator can be established to describe its internal material flow and phase change processes.

[0079] In a simplified embodiment, for a single-stage flash evaporator, based on the principle of material balance, the following consistent flash evaporation model can be established:

[0080] F i =V i +L i

[0081] In the formula, F i V is the feed flow rate of the i-th stage flash evaporator. i L represents the steam volume of the i-th stage flash evaporator. i denoted as the discharge flow rate of the i-th stage flash evaporator.

[0082] It should be noted that the above embodiments are merely a conventional implementation method provided to simply illustrate the general process of establishing a consistent flash evaporation model for a flash evaporator based on the principle of material balance, and are not limited here.

[0083] Continuing from the previous example, taking the 3-stage flash evaporation model as an example, based on the actual number of stages in the multi-stage flash evaporation system (i.e., the number of flash evaporators), multiple single-stage models are connected in the order of material flow to form the overall mathematical model of the multi-stage flash evaporation system.

[0084] F1 = V1 + L1

[0085] L1 = F2

[0086] F2 = V2 + L2

[0087] L2 = F3

[0088] F3 = V3 + L3

[0089] In the formula, F1 is the feed flow rate of the first-stage flash evaporator, V1 is the steaming water flow rate of the first-stage flash evaporator, L1 is the discharge flow rate of the first-stage flash evaporator, F2 is the feed flow rate of the second-stage flash evaporator, V2 is the steaming water flow rate of the second-stage flash evaporator, L2 is the discharge flow rate of the second-stage flash evaporator, F3 is the feed flow rate of the third-stage flash evaporator, V3 is the steaming water flow rate of the third-stage flash evaporator, and L3 is the discharge flow rate of the third-stage flash evaporator.

[0090] In a preferred embodiment, a balance equation is constructed based on the feed volume, inlet feed mass flow rate, outlet feed mass flow rate, and distillation water volume. The balance equation is as follows:

[0091]

[0092] In the formula, Mi S The volume of liquid in the i-th stage flash evaporator. Let be the inlet liquid mass flow rate of the i-th stage flash evaporator. Let be the mass flow rate of the liquid feed at the outlet of the i-th stage flash evaporator. The amount of water evaporated in the i-th stage flash evaporator;

[0093] As can be seen, based on the principle of material balance, a balance equation was constructed that includes the feed liquid volume, inlet feed liquid mass flow rate, outlet feed liquid mass flow rate, and steaming water volume. This equation, based on the law of conservation of mass, accurately describes the dynamic balance relationship of materials within the multi-stage flash evaporator. Introducing the feed liquid volume reflects the real-time changes in the material's inventory within the flash evaporator; the inlet and outlet feed liquid mass flow rates reflect the material's input and output processes; and the introduction of steaming water volume considers the impact of the flash evaporation process on the material balance.

[0094] Construct analytical equations for the feed volume, inlet feed mass flow rate, and outlet feed mass flow rate. The analytical equations are as follows:

[0095]

[0096] In the formula, The volume of liquid in the i-th stage flash evaporator. Let be the feed liquid density of the i-th stage flash evaporator. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let i be the liquid level of the i-th stage flash evaporator. Let be the inlet liquid mass flow rate of the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. Let be the mass flow rate of the liquid feed at the outlet of the i-th stage flash evaporator. Let i be the outlet liquid volume flow rate of the i-th stage flash evaporator;

[0097] As can be seen, analytical equations were constructed for the feed volume, inlet feed mass flow rate, and outlet feed mass flow rate. These equations incorporate key parameters such as feed density, effective cross-sectional area of ​​the flash evaporator, liquid level, and feed volumetric flow rate to describe the material characteristics of the multi-stage flash evaporation process. Specifically, the inclusion of feed density and liquid level reflects the influence of feed properties and flash evaporator geometry on the material inventory; inlet feed density and volumetric flow rate determine the material input rate; and outlet feed volumetric flow rate reflects the material output process.

[0098] Combining the analytical equations and the equilibrium equations, we obtain the uniform flash evaporation model, which is as follows:

[0099]

[0100] In the formula, Let be the feed liquid density of the i-th stage flash evaporator, and t be the time. Let i be the liquid level of the i-th stage flash evaporator. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. V is the outlet liquid volume flow rate of the i-th stage flash evaporator. i S The amount of water evaporated in the i-th stage flash evaporator.

[0101] Continuing with the previous example, taking the 5-stage flash model as an example, a multi-stage consistent flash model is obtained based on the cascaded consistent flash model with a preset number of flash stages. The multi-stage consistent flash model is as follows:

[0102]

[0103] In the formula, The density of the liquid in the first-stage flash evaporator is given by t, where t is the time. The liquid level of the first-stage flash evaporator. The effective cross-sectional area of ​​the first-stage flash evaporator. The inlet liquid density of the first-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the first-stage flash evaporator. This refers to the outlet liquid volume flow rate of the first-stage flash evaporator. This refers to the steam volume of the first-stage flash evaporator; The feed liquid density of the second-stage flash evaporator. The liquid level of the second-stage flash evaporator. The effective cross-sectional area of ​​the second-stage flash evaporator. The inlet liquid density of the second-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the second-stage flash evaporator. This refers to the outlet liquid volume flow rate of the second-stage flash evaporator. This refers to the steam volume of the second-stage flash evaporator. The feed liquid density of the third-stage flash evaporator. The liquid level of the third-stage flash evaporator. The effective cross-sectional area of ​​the third-stage flash evaporator. The inlet liquid density of the third-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the third-stage flash evaporator. This refers to the outlet liquid volume flow rate of the third-stage flash evaporator. This refers to the water volume of the third-stage flash evaporator. The feed liquid density of the fourth-stage flash evaporator. This refers to the liquid level in the fourth-stage flash evaporator. The effective cross-sectional area of ​​the fourth-stage flash evaporator. The inlet liquid density of the fourth-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the fourth-stage flash evaporator. This refers to the outlet liquid volume flow rate of the fourth-stage flash evaporator. This refers to the water volume of the fourth-stage flash evaporator. The feed liquid density of the fifth-stage flash evaporator. The liquid level of the fifth-stage flash evaporator. The effective cross-sectional area of ​​the fifth-stage flash evaporator. The inlet liquid density of the fifth-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the fifth-stage flash evaporator. This refers to the outlet liquid volume flow rate of the fifth-stage flash evaporator. This refers to the water volume of the fifth-stage flash evaporator.

[0104] In practical applications, a problem arises: the density of the liquid feed may differ between different stages. When these liquid feeds of different densities are mixed, the volume changes, thus affecting the material balance. To simplify the model's complexity and improve computational efficiency, the impact of this volume change can be appropriately ignored during modeling.

[0105] S102. Construct a simplified function that ignores the volume change caused by mixing solutions of different densities.

[0106] It should be noted that the volumes before and after mixing are considered equal, thus eliminating the influence of volume changes from the model.

[0107] In some preferred embodiments, the simplified function is:

[0108]

[0109] In the formula, Let t be the liquid level of the i-th stage flash evaporator, and t be the time. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. V is the outlet liquid volume flow rate of the i-th stage flash evaporator. i S Let ρ be the steam volume of the i-th stage flash evaporator. w The density of water;

[0110] It should be noted that the simplified function described above is only a preferred embodiment. In other embodiments, other methods may be adopted, which are not limited here.

[0111] As can be seen, a simplification approach of ignoring density differences in the feed liquid was further introduced based on the consistent flash evaporation model. Considering the potential differences in feed liquid density between different stages of the flash evaporator, directly using these feed liquid volumetric flow rates for material balance calculations might introduce errors. To simplify the model's complexity and improve computational efficiency, the volume changes caused by these density differences were appropriately ignored during the modeling process. While this simplification sacrifices some accuracy, it highlights the model's main research question, making the material balance relationship clearer and easier to solve. Through reasonable simplification assumptions, the computational load and time cost can be significantly reduced while ensuring the model's practicality.

[0112] S103. Construct a relational function in which the amount of water evaporated is positively correlated with the pressure drop and negatively correlated with the density of the liquid.

[0113] refer to Figure 3 , Figure 3 The working principle diagram of the flash evaporator provided in this application is shown below. In order to accurately characterize the individual self-evaporation behavior of the liquid in each stage of the flash evaporator, the working principle of the flash evaporator is explained below.

[0114] Flash evaporation processes often employ methods such as Figure 3 The flash evaporator shown achieves liquid concentration. It consists of a throttling valve and a separation chamber, enabling rapid boiling and vaporization of high-temperature and high-pressure liquids.

[0115] The working principle of flash evaporation is as follows: First, the high-temperature, high-pressure liquid feed undergoes a sudden pressure reduction through a throttling valve, causing the boiling point of the liquid to decrease and placing it in a superheated state. Subsequently, the superheated liquid enters the separation chamber, where it rapidly boils and vaporizes, undergoing vapor-liquid two-phase separation to achieve self-evaporation. The steam exits from the top of the separation chamber, while the concentrated liquid exits from the bottom. Multi-stage flash evaporation is based on the principle of single-stage flash evaporation, allowing the liquid feed to pass sequentially through multiple flash evaporators connected in series. In each flash evaporator, the liquid undergoes pressure reduction, self-evaporation, and vapor-liquid separation, achieving progressive concentration of the liquid feed.

[0116] Analysis of the flash evaporator's working principle reveals that: the greater the pressure drop, the lower the boiling point of the feed liquid after pressure reduction. The more sensible heat released by the superheated feed liquid to reach saturation after pressure reduction, the more heat absorbed by the liquid in the form of latent heat, resulting in a greater amount of water vapor produced through self-evaporation. Therefore, the water vapor production of the flash evaporator is positively correlated with its pressure drop. Conversely, the higher the density of the feed liquid, the more latent heat is required to evaporate a unit mass of water, which is equivalent to greater resistance to the self-evaporation process, resulting in a relatively lower amount of water vapor produced. Therefore, the water vapor production of the flash evaporator is negatively correlated with the density of the feed liquid.

[0117] In some embodiments, the relational function is:

[0118]

[0119] In the formula, Let i be the water volume of the i-th stage flash evaporator. The pressure drop of the i-th stage flash evaporator is... Let the outlet liquid density of the i-th stage flash evaporator be . is a coefficient.

[0120] In some other preferred embodiments, the relational function is:

[0121]

[0122] In the formula, Let i be the water volume of the i-th stage flash evaporator. The pressure drop of the i-th stage flash evaporator is... Let the outlet liquid density of the i-th stage flash evaporator be . For coefficients, It is a constant.

[0123] It should be noted that the above relational functions only provide a few examples. In other examples, other methods may be adopted, which are not limited here.

[0124] S104. By combining the multi-level consistency flash evaporation model, the simplified function, and the relational function, the multi-level flash evaporation model is obtained.

[0125] Simultaneous equations refer to combining multiple equations or inequalities together to form a single equation.

[0126] It should be noted that steps S101 to S103 provide multiple implementation methods. This step is just an example of selecting one of the preferred combinations of steps S101 to S103, but it is not limited to the only implementation path.

[0127] Preferred uniform flash evaporation model:

[0128]

[0129] Preferred simplified function:

[0130]

[0131] Preferred relational function:

[0132]

[0133] The multi-stage flash evaporation model is as follows:

[0134]

[0135] In the formula, Let be the feed liquid density of the i-th stage flash evaporator, and t be the time. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let i be the liquid level of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. The pressure drop of the i-th stage flash evaporator is... Let be the pressure drop coefficient of the i-th stage flash evaporator. Let be the pressure drop constant of the i-th stage flash evaporator. Let be the density coefficient of the liquid feed in the i-th stage flash evaporator. The feed density constant of the i-th stage flash evaporator, ρ w This is the density of water.

[0136] refer to Figure 2 It should be noted that the above model is just a general notation. In actual use, the model should be determined based on the number of flash stages. For example, a 5-stage flash model is used as follows:

[0137] For the feed liquid, the flash evaporation raw liquid enters from the first-stage flash evaporator, passes through the second-stage flash evaporator, the third-stage flash evaporator, the fourth-stage flash evaporator in sequence, and exits from the fifth-stage flash evaporator.

[0138] Therefore, the 5-stage flash evaporation model is:

[0139]

[0140] In the formula, F1 is the inlet liquid volume flow rate of the first-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the second-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the third-stage flash evaporator. This refers to the inlet liquid volumetric flow rate of the fourth-stage flash evaporator. ρ1 is the inlet liquid volumetric flow rate of the 5th stage flash evaporator, and ρ1 is the inlet liquid density of the 1st stage flash evaporator.

[0141] S105. Output a multi-stage flash evaporation model, enabling industrial sites to control the flash evaporation process by referring to the multi-stage flash evaporation model.

[0142] refer to Figure 4 , Figure 4 A comparative diagram showing the construction of relevant multi-stage flash evaporation models and the multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0143] Figure 4The upper wavy line segment represents the actual outlet liquid density of the 5-stage flash evaporator and the outlet liquid density predicted by the multi-stage flash evaporation model based on self-evaporation characteristics provided in this application, respectively. The lower wavy line segment represents the outlet liquid density predicted by the multi-stage flash evaporation model provided by related technologies. It can be seen that the predicted average outlet liquid density of the 5-stage flash evaporator by the multi-stage flash evaporation model provided in this application is consistently 1347.9 kg / m³. 3 The predicted average outlet liquid density of a 5-stage flash evaporator, based on the multi-stage flash evaporation model provided by relevant technologies, is consistently around 1303.5 kg / m³. 3 The actual outlet liquid density of the 5-stage flash evaporator was approximately 1348.2 kg / m³. 3 It is clear that the data predicted by the multi-stage flash evaporation model provided in this application is more accurate than the data predicted by the multi-stage flash evaporation model provided by related technologies, and can more accurately describe the concentration behavior of the liquid.

[0144] As can be seen, by constructing the relationship function, a quantitative relationship was clearly established: a positive correlation between the water vaporization rate and the pressure drop, and a negative correlation with the feed liquid density. This relationship function fully considers the differences in the self-evaporation state of each stage of the flash evaporator during the multi-stage flash evaporation process, accurately describing the self-evaporation behavior of the feed liquid within each stage of the flash evaporator and precisely reflecting the dynamic characteristics of the multi-stage flash evaporation process. Based on this relationship function, a refined description and prediction of the multi-stage flash evaporation process can be achieved, providing a reliable decision-making basis for optimized control in industrial settings. Furthermore, a simplified function was constructed to ignore the volume changes caused by mixing solutions of different densities, which reduces computational complexity and improves the model's practicality while maintaining model accuracy.

[0145] The following is a specific example:

[0146] refer to Figure 5 , Figure 5 This is a schematic diagram of a lower-level process for constructing a multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0147] S501. Establish a consistent flash evaporation model for the flash evaporator based on the principle of material balance, and obtain a multi-level consistent flash evaporation model by cascading the consistent flash evaporation model based on the preset number of flash evaporation levels.

[0148] The uniform flash evaporation model is as follows:

[0149]

[0150] It should be noted that the principle and process of this step have been specifically disclosed in step S101. The relevant principle and process can be referred to in step S101, and will not be repeated here.

[0151] S502. Construct a simplified function that ignores the volume change caused by mixing solutions of different densities.

[0152] The simplified function is:

[0153]

[0154] It should be noted that the principle and process of this step have been specifically disclosed in step S102. The relevant principle and process can be referred to in step S102, and will not be repeated here.

[0155] S503. Construct a relational function in which the water distillation rate is the ratio of the product of pressure drop and pressure drop factor to the product of the density of the liquid and the density factor of the liquid.

[0156] The relational function is:

[0157]

[0158] It should be noted that the principle and process of this step have been specifically disclosed in step S103. The relevant principle and process can be referred to in step S103, and will not be repeated here.

[0159] As can be seen, expressing the steam generation rate as the ratio of the product of pressure drop and pressure drop factor to the product of liquid density and liquid density factor quantitatively describes the influence of pressure drop and liquid density on the steam generation rate, reflecting the correlation between them. This representation can more accurately reflect the intrinsic relationship between various influencing factors in the multi-stage flash evaporation process. By reasonably setting the values ​​of pressure drop factor and liquid density factor, the weights of pressure drop and liquid density in the relationship function can be flexibly adjusted, enabling the model to more accurately reflect the actual multi-stage flash evaporation process.

[0160] S504. By combining the multi-level consistency flash evaporation model, simplifying the function, and the relational function, the multi-level flash evaporation model is obtained.

[0161] The multi-stage flash evaporation model is as follows:

[0162]

[0163] S505. Within the preset number of iterations, adjust the values ​​of all pressure drop factors and liquid density factors, and obtain the difference between the simulated data calculated by the multi-stage flash evaporation model and the actual data.

[0164] It should be noted that the principle and process of this step have been specifically disclosed in step S605. The relevant principle and process can be referred to in step S605, and will not be repeated here.

[0165] S506. When the difference is minimal, determine the values ​​of all pressure drop factors and feed density factors.

[0166] As can be seen, by adjusting the values ​​of the pressure drop factor and the feed density factor within a preset number of iterations and comparing the differences between the model calculation results and the actual data, dynamic optimization of the parameters of the multi-stage flash evaporation model is achieved. This iterative optimization method can adaptively search for the optimal combination of model parameters, making the simulation results of the model as close as possible to the actual situation and reaching the global optimum. This iterative optimization process can improve the accuracy of the multi-stage flash evaporation model, enabling it to more accurately reflect / describe the behavior of the feed liquid during the flash evaporation process.

[0167] S507 outputs a multi-stage flash evaporation model, enabling industrial sites to control the flash evaporation process by referring to the multi-stage flash evaporation model.

[0168] The following is a preferred embodiment:

[0169] refer to Figure 6 , Figure 6 This is another lower-level process diagram illustrating the method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics provided in this application.

[0170] S601. Establish a consistent flash evaporation model for the flash evaporator based on the principle of material balance, and obtain a multi-level consistent flash evaporation model by cascading the consistent flash evaporation model based on the preset number of flash evaporation levels.

[0171] The uniform flash evaporation model is as follows:

[0172]

[0173] It should be noted that the principle and process of this step have been specifically disclosed in step S101. The relevant principle and process can be referred to in step S101, and will not be repeated here.

[0174] S602. Construct a simplified function that ignores the volume change caused by mixing solutions of different densities.

[0175] The simplified function is:

[0176]

[0177] It should be noted that the principle and process of this step have been specifically disclosed in step S102. The relevant principle and process can be referred to in step S102, and will not be repeated here.

[0178] S603. Construct a relational function. In the relational function, the amount of water evaporated is the ratio of the pressure drop function to the density function of the liquid. The pressure drop function is determined by the product of the pressure drop and the pressure drop coefficient, with a pressure drop constant added to the product. The density function of the liquid is determined by the product of the density of the liquid and the density coefficient of the liquid, with a density constant added to the product.

[0179] The relational function is:

[0180]

[0181] It should be noted that the principle and process of this step have been specifically disclosed in step S103. The relevant principle and process can be referred to in step S103, and will not be repeated here.

[0182] It is evident that adding constant terms to the original pressure drop coefficient and liquid density coefficient allows for fine-tuning of the output results of the pressure drop function and liquid density function without altering the overall form of the function. This fine-tuning compensates for errors caused by model simplification and parameter estimation, enabling the relationship function to more accurately describe the relationship between water distillation, pressure drop, and liquid density during multi-stage flash evaporation.

[0183] S604. By combining the multi-level consistency flash evaporation model, simplifying the function, and the relational function, the multi-level flash evaporation model is obtained.

[0184] The multi-stage flash evaporation model is as follows:

[0185]

[0186] S605. Within the preset number of iterations, adjust the values ​​of all pressure drop coefficients, pressure drop constants, liquid density coefficients, and liquid density constants, and obtain the difference between the simulated data calculated by the multi-stage flash evaporation model and the actual data.

[0187] Taking a 5-stage flash evaporation model as an example, this step will be described in detail.

[0188] The 5-stage flash evaporation model is as follows:

[0189]

[0190] The parameter identification problem of the flash evaporation process can be transformed into an optimization problem to be solved, with the goal of minimizing the difference between the simulated data obtained from the estimated parameters and the actual data.

[0191] The parameter identification and optimization problem for a multi-stage flash evaporation process is as follows:

[0192]

[0193] The error function between each pair of simulated and actual data is defined by the following formula:

[0194]

[0195] In the formula, The root mean square error between the simulated discharge density and the actual discharge density obtained from the N sample data used is the objective function of the parameter identification optimization problem. x represents the self-evaporation parameter to be identified in the multi-stage flash evaporation process, i.e., the decision variable of the parameter identification optimization problem, and N is the number of data pairs used to identify the parameters. Let be the error value between the simulated data and the actual data obtained from the i-th data pair. The kinetic model for the above 5-stage flash evaporation process is as follows: This represents the feed liquid density of the i-th data pair. This represents the discharge liquid density of the i-th data pair; To perform an integration operation on the above 5-stage flash evaporation model within period T1, the resulting product liquid density corresponding to the i-th data pair in the 5-stage flash evaporation process is obtained based on the identified parameter x. The simulated value; The density ρ of the effluent liquid in the 5th stage flash evaporation process corresponding to the i-th data pair is obtained based on the parameter x obtained from the identification. 1,i The difference between the simulated value and the actual value.

[0196] It should be noted that the above embodiments are merely exemplary in providing a specific implementation method. In other embodiments, other methods may also be adopted, which are not limited here.

[0197] In other specific embodiments, further technical solutions are provided to solve the parameter identification problem of the above-mentioned flash evaporation process;

[0198] The specific steps are as follows:

[0199] S1. Randomly generate an initial population within the decision space, where each individual represents a solution (decision variable);

[0200] The decision space refers to the set of all feasible solutions in an optimization problem, and each solution consists of a set of values ​​for decision variables.

[0201] The initial population refers to the set of feasible solutions in an optimization problem, where each solution consists of a set of values ​​for decision variables.

[0202] This step is the starting point of the CJAYA algorithm, aiming to provide initial search points for subsequent optimization processes. In parameter identification problems, decision variables typically correspond to the model parameters to be identified. Randomly generating the initial population means randomly selecting a certain number of points within the decision space as starting search positions. This increases population diversity and prevents the algorithm from prematurely getting trapped in local optima.

[0203] S2. For each solution in the population, calculate the fitness value based on its corresponding decision variable. The fitness value is calculated by the objective function of the defined optimization problem. The optimization objective of parameter identification is:

[0204]

[0205] The fitness value refers to the objective function value corresponding to each candidate solution.

[0206] For parameter identification problems, the goal is to find a set of parameters that make the model's output as close as possible to the actual measurement data. Therefore, the fitness function should be designed as a measure of the error between the simulated and measured values.

[0207] S3. Set the number of iterations or other termination conditions so that the algorithm stops when certain conditions are met;

[0208] S4. For each individual in the population, generate a new individual and calculate the fitness value (objective function) of the new individual.

[0209] However, in the decision space of parameter identification problems, different dimensions have different search ranges, leading to a complex and variable decision space. When optimization algorithms solve such problems, they may over-search some decision dimensions while under-searching others. This imbalance in the search affects the convergence speed and solution quality of the algorithm, making it difficult for the algorithm to find the global optimum.

[0210] Therefore, step S4 can be: S41. For each individual in the population, generate a new individual according to the "dynamic clustering weight strategy" and calculate the fitness value (objective function) of the new individual.

[0211] In some specific implementations, the CJAYA algorithm employs a dynamic clustering weight strategy to generate new individuals. Specifically, CJAYA divides the population into several subgroups through a clustering learning model and determines the intra-class best and worst values ​​for each class. Other individuals within a class learn from the intra-class best, intra-class worst, globally best, and globally worst individuals with a certain probability to determine the evolutionary direction. Simultaneously, the algorithm introduces dynamic weights to adaptively adjust the learning intensity of individuals within a class, allowing individuals of different classes to have different learning strategies and learning step sizes. In this way, the algorithm can conduct effective searches across various dimensions of the decision variables, finding high-quality solutions that satisfy the optimization objective by exploring different parameter combinations. The dynamic clustering weight strategy balances the algorithm's global exploration and local development capabilities, improving the search efficiency and solution quality in complex decision spaces.

[0212] However, taking the multi-stage flash evaporation model as an example, it consists of five cascaded differential equations. For a single sample data pair, calculating the simulated output density based on the feed density and the parameters to be identified requires solving all five differential equations consecutively. This process is not only highly nonlinear but also involves a large number of parameters; changes in any one parameter can significantly impact the results. Therefore, solving such highly nonlinear optimization problems is extremely difficult. Traditional optimization algorithms often struggle to escape local optima or have slow convergence speeds when dealing with this type of problem, resulting in poor optimization performance.

[0213] Therefore, step S4 can be: S42. For each individual in the population, generate a new individual according to the "multi-experience learning strategy" and calculate the fitness value (objective function) of the new individual.

[0214] In some specific implementations, the CJAYA algorithm employs a multi-experience learning strategy to generate new individuals. To address this issue, the algorithm clusters the entire population into several subspaces. Within each subspace, the current individual learns from other individuals within the cluster to varying degrees, including learning from the best individual within the cluster, learning from randomly selected high-quality individuals, and learning from the globally optimal individual. By comprehensively utilizing multiple learning experiences, individuals can escape local optima and accelerate convergence towards the globally optimal solution. This not only promotes information exchange among individuals within the population but also draws upon the evolutionary experience of other individuals, fully utilizing their strengths and avoiding their weaknesses. The multi-experience learning strategy, by rationally scheduling different learning modes, enhances the algorithm's ability to handle highly nonlinear problems, facilitating more accurate convergence to the globally optimal solution and thus achieving good solution performance.

[0215] In other embodiments, step S4 can be: S43, for each individual in the population, generate a new individual according to the "dynamic clustering weight strategy" and the "multi-experience learning strategy", and calculate the fitness value (objective function) of the new individual. This simultaneously addresses the above-mentioned problems.

[0216] S5. Update the corresponding individuals in the current population based on the fitness value of the newly produced individuals;

[0217] In the parameter identification search process, the optimal solution plays a crucial role because it guides and attracts other individuals to converge towards its region. However, for the parameter identification problem of flash evaporation processes with multimodal characteristics, the optimal solution is likely located near a local optimum. In this case, other individuals are easily attracted to this local optimum, causing the algorithm to converge prematurely and fail to find the global optimum. This phenomenon severely impacts the algorithm's optimization performance and solution quality.

[0218] Therefore, in some embodiments, it also includes: S6, updating the optimal solution of the population according to the designed "chaotic elite strategy";

[0219] A chaotic elite learning strategy is introduced to adjust the quality of the optimal solution. The randomness and ergodicity of chaotic sequences are beneficial for generating new elite individuals to improve the quality of the solution.

[0220] The implementation process of the chaotic elite learning strategy is as follows: First, a chaotic sequence is generated based on the best individual in the current population. Then, this chaotic sequence is used to perturb the decision variables of the best individual, generating several new elite individuals. Next, these new elite individuals are compared with the original best individual, and the individual with the best fitness value is selected as the new optimal solution. In this way, the algorithm can continuously generate new solutions of higher quality while retaining the original optimal solution, effectively escaping local optima.

[0221] S7. Based on the predefined stopping condition (maximum number of iterations), determine whether to terminate the algorithm. If the stopping condition is met, the algorithm ends and the parameters to be identified are obtained. Otherwise, return to steps S4, S5, and S6.

[0222] S606. When the difference is minimal, determine the values ​​of all pressure drop coefficients, pressure drop constants, liquid density coefficients, and liquid density constants.

[0223] As can be seen, by adjusting the values ​​of pressure drop coefficient, pressure drop constant, liquid density coefficient, and liquid density constant within a preset number of iterations, and comparing the differences between the model calculation results and actual data, the parameters in the relational function are optimized. Compared with optimizing a single type of parameter, this comprehensive optimization method can search for the optimal parameter combination in a larger parameter space, fully considering the mutual influence and constraint relationships between the parameters, minimizing the difference between the model's simulation results and actual data, achieving overall optimization, and improving the accuracy of the multi-stage flash evaporation model.

[0224] S607 outputs a multi-stage flash evaporation model, enabling industrial sites to control the flash evaporation process by referring to the multi-stage flash evaporation model.

[0225] This application also discloses a system for constructing a multi-stage flash evaporation model based on self-evaporation characteristics. (Refer to...) Figure 7 This is a schematic diagram of the physical apparatus of the multi-stage flash evaporation model construction system based on self-evaporation characteristics provided in this application. The computer 700 may include: at least one processor 701, at least one network interface 704, a user interface 703, a memory 705, and at least one communication bus 702.

[0226] The communication bus 702 is used to enable communication between these components.

[0227] The user interface 703 may include a display screen and a camera. Optionally, the user interface 703 may also include a standard wired interface and a wireless interface.

[0228] The network interface 704 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0229] The processor 701 may include one or more processing cores. The processor 701 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 705, and by calling data stored in memory 705. Optionally, the processor 701 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 701 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 701 and may be implemented as a separate chip.

[0230] The memory 705 may include random access memory (RAM) or read-only memory. Optionally, the memory 705 may include non-transitory computer-readable storage medium. The memory 705 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 705 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 705 may also be at least one storage device located remotely from the aforementioned processor 701. (Refer to...) Figure 7The memory 705, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program built based on a multi-stage flash evaporation model with self-evaporation characteristics.

[0231] exist Figure 7 In the computer 700 shown, the user interface 703 is mainly used to provide an input interface for the user and to acquire user input data; while the processor 701 can be used to call the application program built based on the multi-stage flash evaporation model with self-evaporation characteristics stored in the memory 705. When executed by one or more processors 701, the computer 700 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0232] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0233] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0234] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0235] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0236] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory 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 of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0237] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0238] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any changes or modifications made to the level of the subject matter in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0239] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics, characterized in that, include: A consistent flash evaporation model for the flash evaporator is established based on the material balance principle, and a multi-stage consistent flash evaporation model is obtained by cascading the consistent flash evaporation model based on a preset number of flash evaporation stages; wherein: a balance equation is constructed based on the feed liquid volume, inlet feed liquid mass flow rate, outlet feed liquid mass flow rate, and distillation water volume, and the balance equation is: In the formula, M i S The volume of liquid in the i-th stage flash evaporator. Let be the inlet liquid mass flow rate of the i-th stage flash evaporator. Let be the mass flow rate of the liquid feed at the outlet of the i-th stage flash evaporator. The amount of water evaporated in the i-th stage flash evaporator; Construct analytical equations for the feed volume, the inlet feed mass flow rate, and the outlet feed mass flow rate. The analytical equations are as follows: In the formula, Let be the feed liquid density of the i-th stage flash evaporator. Let i be the effective cross-sectional area of ​​the i-th stage flash evaporator. Let i be the liquid level of the i-th stage flash evaporator. Let be the inlet liquid density of the i-th stage flash evaporator. Let be the inlet liquid volumetric flow rate of the i-th stage flash evaporator. Let i be the outlet liquid volume flow rate of the i-th stage flash evaporator; Combining the analytical equations and the equilibrium equations, we obtain the uniform flash evaporation model, which is as follows: In the formula, t represents time; Construct a simplified function that ignores volume changes caused by mixing solutions of different densities; Construct a relational function in which the amount of water evaporated is positively correlated with the pressure drop and negatively correlated with the density of the liquid. The multi-level flash evaporation model is obtained by combining the multi-level consistent flash evaporation model, the simplified function, and the relational function. The multi-stage flash evaporation model is output so that the flash evaporation process can be controlled in the industrial field by referring to the multi-stage flash evaporation model.

2. The method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics according to claim 1, characterized in that, The step of constructing the relationship function, wherein the water distillation rate is positively correlated with the pressure drop and negatively correlated with the density of the liquid, specifically includes: Construct a relational function, in which the water distillation amount is the ratio of the product of pressure drop and pressure drop factor to the product of the density of the liquid and the density factor of the liquid.

3. The method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics according to claim 2, characterized in that, After the step of obtaining the multi-level flash model by combining the multi-level consistent flash model, the simplified function, and the relational function, the method further includes: Within a preset number of iterations, adjust the values ​​of all the pressure drop factors and the liquid density factors, and obtain the difference between the simulated data calculated by the multi-stage flash evaporation model and the actual data; When the difference is minimized, the values ​​of all the pressure drop factors and the feed density factors are determined.

4. The method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics according to claim 1, characterized in that, The step of constructing the relationship function, wherein the water distillation rate is positively correlated with the pressure drop and negatively correlated with the density of the liquid, specifically includes: Construct a relational function in which the amount of water evaporated is the ratio of the pressure drop function to the density function of the liquid. The pressure drop function is determined by multiplying the pressure drop by the pressure drop coefficient and adding a pressure drop constant to the product. The density function of the liquid is determined by multiplying the density of the liquid by the density coefficient of the liquid and adding a density constant to the product.

5. The method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics according to claim 4, characterized in that, After the step of obtaining the multi-level flash model by combining the multi-level consistent flash model, the simplified function, and the relational function, the method further includes: Within a preset number of iterations, adjust the values ​​of all the pressure drop coefficients, pressure drop constants, liquid density coefficients, and liquid density constants, and obtain the difference between the simulated data calculated by the multi-stage flash evaporation model and the actual data; When the difference is minimized, the values ​​of all the pressure drop coefficients, the pressure drop constants, the liquid density coefficients, and the liquid density constants are determined.

6. The method for constructing a multi-stage flash evaporation model based on self-evaporation characteristics according to claim 1, characterized in that, The simplified function is: In the formula, ρ w The density of water; The multi-stage flash evaporation model is as follows: In the formula, The pressure drop of the i-th stage flash evaporator is... Let be the pressure drop coefficient of the i-th stage flash evaporator. Let be the pressure drop constant of the i-th stage flash evaporator. Let be the density coefficient of the liquid feed in the i-th stage flash evaporator. The feed liquid density constant of the i-th stage flash evaporator.

7. A multi-stage flash evaporation model construction system based on self-evaporation characteristics, characterized in that, include: One or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, and the one or more processors calling the computer instructions to cause the multi-stage flash evaporation model construction system based on self-evaporation characteristics to perform the method as described in any one of claims 1-6.

8. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on a multi-stage flash evaporation model building system based on self-evaporation characteristics, one or more processors in the multi-stage flash evaporation model building system based on self-evaporation characteristics call the instructions to cause the multi-stage flash evaporation model building system based on self-evaporation characteristics to perform the method as described in any one of claims 1-6.

9. A computer program product, characterized in that, When the computer program product is run on a multi-stage flash evaporation model building system based on self-evaporation characteristics, one or more processors in the multi-stage flash evaporation model building system based on self-evaporation characteristics invoke the computer program product to cause the multi-stage flash evaporation model building system based on self-evaporation characteristics to perform the method as described in any one of claims 1-6.

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